Subjects -> TRANSPORTATION (Total: 214 journals)
    - AIR TRANSPORT (9 journals)
    - AUTOMOBILES (26 journals)
    - RAILROADS (10 journals)
    - ROADS AND TRAFFIC (9 journals)
    - SHIPS AND SHIPPING (43 journals)
    - TRANSPORTATION (117 journals)

TRANSPORTATION (117 journals)                     

Showing 1 - 53 of 53 Journals sorted by number of followers
Journal of Navigation     Hybrid Journal   (Followers: 203)
Accident Analysis & Prevention     Hybrid Journal   (Followers: 111)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 38)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 38)
Urban, Planning and Transport Research     Open Access   (Followers: 33)
Transportation     Hybrid Journal   (Followers: 32)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 29)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 29)
Journal of Transport and Land Use     Open Access   (Followers: 28)
Transportation Science     Full-text available via subscription   (Followers: 26)
Journal of Transport Geography     Hybrid Journal   (Followers: 22)
European Transport Research Review     Open Access   (Followers: 22)
Public Transport     Hybrid Journal   (Followers: 18)
Nonlinear Dynamics     Hybrid Journal   (Followers: 18)
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 18)
Cities in the 21st Century     Open Access   (Followers: 17)
Economics of Transportation     Partially Free   (Followers: 16)
Open Journal of Safety Science and Technology     Open Access   (Followers: 16)
Transportation Journal     Full-text available via subscription   (Followers: 16)
Transport     Open Access   (Followers: 16)
Journal of Transportation Technologies     Open Access   (Followers: 13)
IET Electrical Systems in Transportation     Open Access   (Followers: 13)
Case Studies on Transport Policy     Hybrid Journal   (Followers: 13)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 13)
Journal of Supply Chain Management Science (JSCMS)     Open Access   (Followers: 13)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 12)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 12)
Journal of Transport & Health     Hybrid Journal   (Followers: 12)
European Journal of Transport and Infrastructure Research (EJTIR)     Open Access   (Followers: 12)
Journal of Transport History     Hybrid Journal   (Followers: 12)
EURO Journal of Transportation and Logistics     Open Access   (Followers: 12)
Sport, Education and Society     Hybrid Journal   (Followers: 12)
Transport Reviews: A Transnational Transdisciplinary Journal     Hybrid Journal   (Followers: 11)
IET Intelligent Transport Systems     Open Access   (Followers: 11)
Modern Transportation     Open Access   (Followers: 11)
International Journal of Physical Distribution & Logistics Management     Hybrid Journal   (Followers: 11)
Proceedings of the Institution of Mechanical Engineers Part F: Journal of Rail and Rapid Transit     Hybrid Journal   (Followers: 11)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 10)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 10)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 9)
Travel Behaviour and Society     Full-text available via subscription   (Followers: 9)
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 9)
International Journal of Transportation Science and Technology     Open Access   (Followers: 9)
Pervasive and Mobile Computing     Hybrid Journal   (Followers: 8)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 8)
International Journal of Mobile Communications     Hybrid Journal   (Followers: 8)
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 8)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 7)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 7)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 7)
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 7)
IEEE Vehicular Technology Magazine     Full-text available via subscription   (Followers: 7)
Mobility in History     Full-text available via subscription   (Followers: 7)
Transportation Research Procedia     Open Access   (Followers: 6)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 6)
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 6)
Applied Mobilities     Hybrid Journal   (Followers: 5)
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 5)
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 5)
Logistics & Sustainable Transport     Open Access   (Followers: 4)
Journal of Traffic and Transportation Engineering (English Edition)     Open Access   (Followers: 4)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 4)
Transport and Telecommunication     Open Access   (Followers: 4)
Vehicular Communications     Full-text available via subscription   (Followers: 4)
IEEE Open Journal of Intelligent Transportation Systems     Open Access   (Followers: 4)
Research in Transportation Business and Management     Partially Free   (Followers: 4)
Transport Problems     Open Access   (Followers: 4)
Transactions on Transport Sciences     Open Access   (Followers: 4)
World Electric Vehicle Journal     Open Access   (Followers: 3)
Journal of Transportation and Logistics     Open Access   (Followers: 3)
Journal of Public Transportation     Open Access   (Followers: 3)
TRANSPORTES     Open Access   (Followers: 3)
Journal of Transportation Security     Hybrid Journal   (Followers: 3)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 2)
Packaging, Transport, Storage & Security of Radioactive Material     Hybrid Journal   (Followers: 2)
Sport, Ethics and Philosophy     Hybrid Journal   (Followers: 2)
Streetnotes     Open Access   (Followers: 2)
Journal of Big Data Analytics in Transportation     Hybrid Journal   (Followers: 2)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 2)
International Journal of Transportation Engineering     Open Access   (Followers: 2)
Transportation Research Interdisciplinary Perspectives     Open Access   (Followers: 2)
Journal of Intelligent and Connected Vehicles     Open Access   (Followers: 1)
Open Transportation Journal     Open Access   (Followers: 1)
eTransportation     Open Access   (Followers: 1)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 1)
Transportation Safety and Environment     Open Access   (Followers: 1)
Danish Journal of Transportation Research / Dansk Tidsskrift for Transportforskning     Open Access   (Followers: 1)
Asian Transport Studies     Open Access   (Followers: 1)
Transportation Engineering     Open Access   (Followers: 1)
International Journal of Ocean Systems Management     Hybrid Journal   (Followers: 1)
Decision Making : Applications in Management and Engineering     Open Access   (Followers: 1)
Transportation Geotechnics     Full-text available via subscription   (Followers: 1)
Romanian Journal of Transport Infrastructure     Open Access   (Followers: 1)
International Journal of Services Technology and Management     Hybrid Journal   (Followers: 1)
Les Dossiers du Grihl     Open Access   (Followers: 1)
Logistics     Open Access   (Followers: 1)
Synthesis Lectures on Mobile and Pervasive Computing     Full-text available via subscription   (Followers: 1)
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Emission Control Science and Technology     Hybrid Journal   (Followers: 1)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Maritime Transport Research     Open Access  
Communications in Transportation Research     Open Access  
IET Smart Cities     Open Access  
Journal on Vehicle Routing Algorithms     Hybrid Journal  
Transportation in Developing Economies     Hybrid Journal  
Vehicles     Open Access  
Periodica Polytechnica Transportation Engineering     Open Access  
Transportation Systems and Technology     Open Access  
LOGI ? Scientific Journal on Transport and Logistics     Open Access  
Promet : Traffic &Transportation     Open Access  
IFAC-PapersOnLine     Open Access  
Revista Transporte y Territorio     Open Access  
Транспортні системи та технології перевезень     Open Access  
Geosystem Engineering     Hybrid Journal  
Logistique & Management     Hybrid Journal  
IATSS Research     Open Access  
Transport in Porous Media     Hybrid Journal  

           

Similar Journals
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Vehicles
Number of Followers: 0  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2624-8921
Published by MDPI Homepage  [84 journals]
  • Vehicles, Vol. 4, Pages 639-662: Battery Management System for Unmanned
           Electric Vehicles with CAN BUS and Internet of Things

    • Authors: Ngoc Nam Pham, Jan Leuchter, Khac Lam Pham, Quang Huy Dong
      First page: 639
      Abstract: In recent decades, the trend of using zero-emission vehicles has been constantly evolving. This trend brings about not only the pressure to develop electric vehicles (EVs) or hybrid electric vehicles (HEVs) but also the demand for further developments in battery technologies and safe use of battery systems. Concerning the safe usage of battery systems, Battery Management Systems (BMS) play one of the most important roles. A BMS is used to monitor operating temperature and State of Charge (SoC), as well as protect the battery system against cell imbalance. The paper aims to present hardware and software designs of a BMS for unmanned EVs, which use Lithium multi-cell battery packs. For higher modularity, the designed BMS uses a distributed topology and contains a master module with more slave modules. Each slave module is in charge of monitoring and protecting a multi-cell battery pack. All information about the state of each battery pack is sent to the master module which saves and sends all data to the control station if required. Controlled Area Network (CAN) bus and Internet of Things technologies are designed for requirements from different applications for communications between slave modules and the master module, and between the master module and control station.
      Citation: Vehicles
      PubDate: 2022-06-25
      DOI: 10.3390/vehicles4030037
      Issue No: Vol. 4, No. 3 (2022)
       
  • Vehicles, Vol. 4, Pages 663-680: Artificial Intelligence-Based Machine
           Learning toward the Solution of Climate-Friendly Hydrogen Fuel Cell
           Electric Vehicles

    • Authors: Murphy M. Peksen
      First page: 663
      Abstract: The rapid conversion of conventional powertrain technologies to climate-neutral new energy vehicles requires the ramping of electrification. The popularity of fuel cell electric vehicles with improved fuel economy has raised great attention for many years. Their use of green hydrogen is proposed to be a promising clean way to fill the energy gap and maintain a zero-emission ecosystem. Their complex architecture is influenced by complex multiphysics interactions, driving patterns, and environmental conditions that put a multitude of power requirements and boundary conditions around the vehicle subsystems, including the fuel cell system, the electric motor, battery, and the vehicle itself. Understanding its optimal fuel economy requires a systematic assessment of these interactions. Artificial intelligence-based machine learning methods have been emerging technologies showing great potential for accelerated data analysis and aid in a thorough understanding of complex systems. The present study investigates the fuel economy peaks during an NEDC in fuel cell electric vehicles. An innovative approach combining traditional multiphysics analyses, design of experiments, and machine learning is an effective blend for accelerated data supply and analysis that accurately predicts the fuel consumption peaks in fuel cell electric vehicles. The trained and validated models show very accurate results with less than 1% error.
      Citation: Vehicles
      PubDate: 2022-07-04
      DOI: 10.3390/vehicles4030038
      Issue No: Vol. 4, No. 3 (2022)
       
  • Vehicles, Vol. 4, Pages 681-696: Optimal Deployment of Wireless Charging
           Infrastructure for Electric Tram with Dual Operation Policy

    • Authors: Young Kwan Ko, Yonghui Oh, Dae Young Ryu, Young Dae Ko
      First page: 681
      Abstract: The wireless charging electric tram system is presently receiving attention as an eco-friendly means of transportation. The conventional electric tram system has a similar advantage in regards to environmental pollution, but it has several problems that are caused by the overhead power supply line. The battery-type electric tram system should be considered carefully, because the battery itself is an environmentally harmful material. Therefore, the wireless charging electric tram system is regarded as an alternative means of transportation. The adequate battery capacity and the location of the wireless charging infrastructure are investigated in this study, which consider the dual operation policy, and the objective is to minimize the total investment cost. The variation of the battery capacity and the location of the wireless charging infrastructure are examined that compare Case 1, which involves the electric trams operating only in normal operations, and Case 2, which includes the electric trams operating in normal and express operations.
      Citation: Vehicles
      PubDate: 2022-07-16
      DOI: 10.3390/vehicles4030039
      Issue No: Vol. 4, No. 3 (2022)
       
  • Vehicles, Vol. 4, Pages 697-726: Precise Evaluation of Repetitive
           Transient Overvoltages in Motor Windings in Wide-Bandgap Drive Systems

    • Authors: Ashkan Barzkar, Mona Ghassemi
      First page: 697
      Abstract: The increasing interest in employing wide-bandgap (WBG) drive systems has brought about very high power, high-frequency inverters enjoying switching frequencies up to hundreds of kilohertz. However, voltage surges with steep fronts, caused by turning semiconductor switches on/off in inverters, travel through the cable and are reflected at interfaces due to impedance mismatches, giving rise to overvoltages at motor terminals and in motor windings. The phenomena typically associated with these repetitive overvoltages are partial discharges and heating in the insulation system, both of which contribute to insulation system degradation and may lead to premature failures. In this article, taking the mentioned challenges into account, the repetitive transient overvoltage phenomenon in WBG drive systems is evaluated at motor terminals and in motor windings by implementing a precise multiconductor transmission line (MCTL) model in the time domain considering skin and proximity effects. In this regard, first, a finite element method (FEM) analysis is conducted in COMSOL Multiphysics to calculate parasitic elements of the motor; next, the vector fitting approach is employed to properly account for the frequency dependency of calculated elements, and, finally, the model is developed in EMTP-RV to assess the transient overvoltages at motor terminals and in motor windings. As shown, the harshest situation occurs in turns closer to motor terminals and/or turns closer to the neutral point depending on whether the neutral point is grounded or floating, how different phases are connected, and how motor phases are excited by pulse width modulation (PWM) voltages.
      Citation: Vehicles
      PubDate: 2022-07-19
      DOI: 10.3390/vehicles4030040
      Issue No: Vol. 4, No. 3 (2022)
       
  • Vehicles, Vol. 4, Pages 727-743: Driving Robot for Reproducible Testing: A
           Novel Combination of Pedal and Steering Robot on a Steerable Vehicle Test
           Bench

    • Authors: Philip Rautenberg, Clemens Kurz, Martin Gießler, Frank Gauterin
      First page: 727
      Abstract: Shorter development times, increased standards for vehicle emissions and a greater number of vehicle variants result in a higher level of complexity in the vehicle development process. Efficient development of powertrain and driver assistance functions under comparable and reproducible operating conditions is possible on vehicle test benches. Yet, the realistic simulation of real driving environments on test benches is a challenge. Current test procedures and new technologies, such as Real Driving Emission tests and Autonomous Driving, require a reproducible and even more detailed simulation of the driving environment. Due to this, the simulation of curve driving in particular is gaining in importance. This results from its significant influence on energy consumption and Autonomous Driving functions with lateral guidance, such as lane departure and evasion assistance. Reproducibility can be additionally increased by using a driving robot. At today’s vehicle test benches, pedal and shift robots are predominantly used for longitudinal dynamic tests in the performed test procedures. In order to meet these new test automation requirements for vehicle test benches, the cooperative operation of pedal and steering robots is needed on a test bench setup suitable for this purpose. In this publication, the authors present the setup of a vehicle test bench to be used in automated and reproducible vehicle-in-the-loop tests during steering events. The focus is on the test-bench-specific setup with steerable front wheels, the actuators for simulating the wheel steering torque around the steering axle and the robots used for pedals and steering wheel. Results from various test series are presented and the potential of the novel test environment is shown. The results are reproducible in various test series due to the closed-loop operation without human driving influences at the test bench.
      Citation: Vehicles
      PubDate: 2022-07-22
      DOI: 10.3390/vehicles4030041
      Issue No: Vol. 4, No. 3 (2022)
       
  • Vehicles, Vol. 4, Pages 744-765: Exploring Smart Tires as a Tool to Assist
           Safe Driving and Monitor Tire–Road Friction

    • Authors: Maria Pomoni
      First page: 744
      Abstract: Road surface friction, or in other words, a pavement’s skid resistance, is an essential attribute of highway safety, acting as a liaison between the infrastructure condition and the driver’s response to it through proper vehicle maneuvering. The present study reviews aspects related to the tire–road friction, including affecting factors, monitoring systems and related practices, and demonstrates the efficacy of using smart tires, or tires embedded with sensors, for the purpose of evaluating roadway friction levels in real-time while traveling. Such an approach is expected to assist drivers in adjusting their behavior (i.e., lowering their speed) in the event that signs of reduced skid resistance are observed in favor of road safety. The current challenges and research prospects are highlighted in terms of tire manufacturers’ perspectives as well as future mobility patterns with autonomous driving modes. Overall, smart tires are commented as a tool able to enhance drivers’ safety for both current and future mobility patterns, help to control pavement deterioration and complement existing practices for infrastructure condition assessment.
      Citation: Vehicles
      PubDate: 2022-07-26
      DOI: 10.3390/vehicles4030042
      Issue No: Vol. 4, No. 3 (2022)
       
  • Vehicles, Vol. 4, Pages 766-779: Severity Analysis of Large-Truck
           Wrong-Way Driving Crashes in the State of Florida

    • Authors: Salwa Anam, Ghazaleh Azimi, Alireza Rahimi, Xia Jin
      First page: 766
      Abstract: Wrong-way driving (WWD) crashes lead to severe injuries and fatalities, especially when a large truck is involved. This study investigates the factors associated with crash-injury severity in large-truck WWD crashes in Florida. Various driver, roadway, weather, and traffic characteristics were explored as explanatory variables through a random parameter ordered logit model. The study also accounted for heterogeneity by identifying random parameters in the model and introducing interaction effects as potential sources of such heterogeneity. The findings indicate that not using a seatbelt, driving under the influence of drugs, and a driving speed of 50–74 mph were more likely to result in fatal crashes. On the contrary, female drivers, private roadways, and sideswipe collisions showed negative impacts on crash-injury severity. The model identified two random parameters, including a speed of 25–49 mph and early-morning crashes. The interaction effects showed that when driving at a speed of 25–49 mph, young drivers (under 20 years old) and middle-aged drivers (36–50 years old) were the sources of heterogeneity, decreasing crash-injury severity. Understanding the contributing factors of large-truck WWD crashes can help policymakers develop safety countermeasures to reduce the associated injury severity and improve truck safety.
      Citation: Vehicles
      PubDate: 2022-07-30
      DOI: 10.3390/vehicles4030043
      Issue No: Vol. 4, No. 3 (2022)
       
  • Vehicles, Vol. 4, Pages 780-807: Off-Road Construction and Agricultural
           Equipment Electrification: Review, Challenges, and Opportunities

    • Authors: Fuad Un-Noor, Guoyuan Wu, Harikishan Perugu, Sonya Collier, Seungju Yoon, Mathew Barth, Kanok Boriboonsomsin
      First page: 780
      Abstract: Though the current wave of electric vehicles is transforming the on-road passenger and commercial vehicle fleets, similar attempts in the off-road equipment sector appear to be lacking. Because of the diverse equipment categories and varied applications, electrifying off-road equipment requires significant research and development. A successful electrification of such equipment can offer an array of benefits, including reduced air and noise pollution, higher energy efficiency, and increased productivity. This paper provides a review of the current state of technology in off-road equipment electrification, with a focus on the equipment used in construction and agricultural applications. The paper also discusses advantages of, and challenges associated with, electrifying off-road construction and agricultural equipment. In addition, potential solutions for overcoming these challenges as well as opportunities to facilitate the electrification of off-road construction and agricultural equipment are identified.
      Citation: Vehicles
      PubDate: 2022-08-06
      DOI: 10.3390/vehicles4030044
      Issue No: Vol. 4, No. 3 (2022)
       
  • Vehicles, Vol. 4, Pages 808-824: Velocity Prediction Based on Map Data for
           Optimal Control of Electrified Vehicles Using Recurrent Neural Networks
           (LSTM)

    • Authors: Felix Deufel, Purav Jhaveri, Marius Harter, Martin Gießler, Frank Gauterin
      First page: 808
      Abstract: In order to improve the efficiency of electrified vehicle drives, various predictive energy management strategies (driving strategies) have been developed. This article presents the extension of a generic prediction approach already proposed in a previous paper, which allows a robust forecasting of all traction torque-relevant variables for such strategies. The extension primarily includes the proper utilization of map data in the case of an a priori known route. Approaches from Artificial Intelligence (AI) have proven to be effective for such proposals. With regard to this, Recurrent Neural Networks (RNN) are to be preferred over Feed-Forward Neural Networks (FNN). First, preprocessing is described in detail including a wide overview of both calculating the relevant quantities from global navigation satellite system (GNSS) data in several steps and matching these with data from the chosen map provider. Next, an RNN including Long Short-Term Memory (LSTM) cells in an Encoder–Decoder configuration and a regular FNN are trained and applied. The models are used to forecast real driving profiles over different time horizons, both including and excluding map data in the model. Afterwards, a comparison is presented, including a quantitative and a qualitative analysis. The accuracy of the predictions is therefore assessed using Root Mean Square Error (RMSE) computations and analyses in the time domain. The results show a significant improvement in velocity prediction with LSTMs including map data.
      Citation: Vehicles
      PubDate: 2022-08-11
      DOI: 10.3390/vehicles4030045
      Issue No: Vol. 4, No. 3 (2022)
       
  • Vehicles, Vol. 4, Pages 825-842: Using Active Seat Belt Retractions to
           Mitigate Motion Sickness in Automated Driving

    • Authors: Christina Kremer, Markus Tomzig, Nora Merkel, Alexandra Neukum
      First page: 825
      Abstract: The introduction of automated-driving functions provides passengers with the opportunity to engage in non-driving related tasks during the ride. However, this benefit might be compromised by an increased incidence of motion sickness. Therefore, we investigated the effectiveness of active seat belt retractions as a countermeasure against motion sickness during inattentive automated driving. We hypothesized that seat belt retractions would mitigate motion sickness by supporting passengers to anticipate upcoming braking maneuvers, by actively tensioning their neck muscles and, thereby, reducing the extent of forward head movement while braking. In a motion base driving simulator, 26 participants encountered two 30 min automated drives in slow-moving traffic: one drive with active seat belt retractions before each braking maneuver and a baseline drive without. The results revealed that there was no difference in perceived motion sickness between both experimental conditions. Seat belt retractions resulted in an increased activity of the lateral neck muscles and supported drivers to anticipate braking maneuvers. However, at the same time, the retractions led to an increased magnitude of head movement in response to braking. This research lays the groundwork for future research on active seat belt retractions as a countermeasure against motion sickness and provides directions for future work.
      Citation: Vehicles
      PubDate: 2022-08-11
      DOI: 10.3390/vehicles4030046
      Issue No: Vol. 4, No. 3 (2022)
       
  • Vehicles, Vol. 4, Pages 314-325: A Refined-Line-Based Method to Estimate
           Vanishing Points for Vision-Based Autonomous Vehicles

    • Authors: Shengyao Shen, Shanshan Wang, Luping Wang, Hui Wei
      First page: 314
      Abstract: Helping vehicles estimate vanishing points (VPs) in traffic environments has considerable value in the field of autonomous driving. It has multiple unaddressed issues such as refining extracted lines and removing spurious VP candidates, which suffers from low accuracy and high computational cost in a complex traffic environment. To address these two issues, we present in this study a new model to estimate VPs from a monocular camera. Lines that belong to structured configuration and orientation are refined. At that point, it is possible to estimate VPs through extracting their corresponding vanishing candidates through optimal estimation. The algorithm requires no prior training and it has better robustness to color and illumination on the base of geometric inferences. Through comparing estimated VPs to the ground truth, the percentage of pixel errors were evaluated. The results proved that the methodology is successful in estimating VPs, meeting the requirements for vision-based autonomous vehicles.
      Citation: Vehicles
      PubDate: 2022-03-22
      DOI: 10.3390/vehicles4020019
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 326-343: Transport Automation in Urban Mobility: A
           Case Study of an Autonomous Parking System

    • Authors: Jiri Plihal, Pavel Nedoma, Vladimir Sestak, Zdenek Herda, Andrei Aksjonov
      First page: 326
      Abstract: Parking road vehicles is one of the most tedious and challenging tasks a human driver performs. Despite the low speeds involved, parking manoeuvres are among the main causes of minor and sometimes major traffic accidents, especially in urban areas where limited parking spaces are available. Furthermore, searching for a parking space wastes time and contributes to unnecessary road occupancy and pollution. This paper is dedicated to the development of an autonomous parking system for on-street parking in urban areas. The system is capable of fully automated parking manoeuvres from drop-off to pick-up zones, thus removing human drivers from the vehicle control loop. The system autonomously navigates to the parking space and parks the vehicle without human intervention. The proposed system incorporates a communication protocol that connects automated vehicles, parking infrastructure, and drivers. Several convenient human–machine interface concepts for efficient system communication and state monitoring have been developed. A methodology for validating the system in real time is proposed, which includes functionality requirements and a description of parallel and perpendicular parking manoeuvres. The proposed pipeline is tested on an electric vehicle platform with automated functions, where successful technological functionality is demonstrated.
      Citation: Vehicles
      PubDate: 2022-04-05
      DOI: 10.3390/vehicles4020020
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 344-374: Motion Planning for Autonomous Vehicles
           Based on Sequential Optimization

    • Authors: Maksym Diachuk, Said M. Easa
      First page: 344
      Abstract: This study presents the development and analysis of a technique for planning the autonomous vehicle (AV) motion references using sequential optimization. The method determines the trajectory plan, speed and acceleration distributions, and other AV kinematic parameters. The approach combines the basics of the finite element method (FEM) and nonlinear optimization with nonlinear constraints. First, we briefly described the generalization of representing an arbitrary function by finite elements (FE) within a road segment. We chose a one-dimensional FE with two nodes and three degrees of freedom (DOF) in a node corresponding to the 5th-degree polynomial. Next, we presented a method for defining the motion trajectory. The following are considered: the formation of a restricted space for the AV’s allowable maneuvering, the motion trajectory geometry and its relation with vehicle steerability parameters, cost functions and their influences on the desirable trajectory’s nature, and the compliance of nonlinear restrictions of the node parameters with the motion area boundaries. In the second stage, we derived a technique for optimizing the AV’s speed and acceleration redistributions. The model considers possible combinations of objective functions, limiting the kinematic parameters by the tire slip critical speed, maximum speed level, maximum longitudinal acceleration, and critical lateral acceleration. In the simulation section, we compared several variants of trajectories and versions of distributing the longitudinal speed and acceleration curves. The advantages, drawbacks, and conclusions regarding the proposed technique are presented.
      Citation: Vehicles
      PubDate: 2022-04-12
      DOI: 10.3390/vehicles4020021
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 375-389: Research on Line Planning and Timetabling
           Optimization Model Based on Passenger Flow of Subway Network

    • Authors: Wenqing Mei, Yu Zhang, Miao Zhang, Guangming Qing, Zhaoyang Zhang
      First page: 375
      Abstract: In this paper, we propose a line planning and timetabling optimization model considering operation cost and passenger satisfaction based on passenger flow. By comprehensively considering the operation cost and passenger waiting cost, the comprehensive social benefits of the line network operation organization are evaluated from a unified perspective. The passenger flow model based on queuing theory is adopted, which can better describe the relationship between passenger flow change and passenger waiting time. The integrated optimization model of the line network is constructed, and mixed integer quadratic programming is adopted, which has the advantages of accurate results and fast convergence. Through the simulation case analysis, the correctness of the method proposed in this paper is verified.
      Citation: Vehicles
      PubDate: 2022-04-15
      DOI: 10.3390/vehicles4020022
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 390-408: Evolution of the Hybrid Aerial Underwater
           Robotic System (HAUCS) for Aquaculture: Sensor Payload and Extension
           Development

    • Authors: Casey J. Den Ouden, Paul S. Wills, Lucas Lopez, Joshua Sanderson, Bing Ouyang
      First page: 390
      Abstract: While robotics have been widely used in many agricultural practices such as harvesting, seeding, cattle monitoring, etc., aquaculture farming is an important, fast-growing sector of agriculture that has not seen significant adoption of advanced technologies such as robotics and the Internet of Things (IoT). In particular, dissolved oxygen (DO) monitoring, a practice in pond aquaculture essential to the health of the fish crops, remains labor-intensive and time-consuming. The Hybrid Aerial Underwater robotiCs System (HAUCS) is an IoT framework that aims to bring transformative changes to pond aquaculture. This paper focuses on the latest development in the HAUCS mobile sensing platform and field deployment. To address some shortcomings with the current implementation, the development of a novel rigid Kirigami-based robotic extension subsystem that can expand the functionality of the HAUCS platform is also being discussed.
      Citation: Vehicles
      PubDate: 2022-04-21
      DOI: 10.3390/vehicles4020023
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 409-419: Understanding the Motivation and
           Satisfaction of Private Vehicle Users in an Eastern European Country Using
           Heterogeneity Analysis

    • Authors: Karzan Ismael, Szabolcs Duleba
      First page: 409
      Abstract: Transport service provision in many urban areas is dominated by car users, resulting in several traffic externality issues (e.g., noise, pollution, accidents). This paper investigates the perception and satisfaction of private vehicle (PV) users, including micro-mobility users, during their commute by car in an Eastern European country context. The study used empirical data from a sample of 500 commuters in Budapest, Hungary, between October and November 2020. To achieve a deeper understanding of the motivation and explore the perception of PV users towards using sustainable transport services. For analysis in this study, descriptive statistics and segmentation techniques were applied. The key findings indicate that PV users can be attracted to using sustainable transport by designing the travel service quality to provide the level of service desired by customers. Moreover, the majority (73%) of PV commuters were satisfied or very satisfied with the quality attributes of the car service, assessed on a scale of 1 to 5; at the same time, PV users agreed that using public transport helps towards improving the environment and serves to reduce problems derived from traffic. In addition, various elements influence transport choice; for example, results from ordered logit models (OLMs) indicate that security, relaxation, flexibility and comfort are the main significant attributes influencing PV users’ overall satisfaction with cars. The results suggest the necessity for a segmentation technique in the analysis of travel attitudes and satisfaction aimed at reducing the frequency of existing car use to enhance sustainable transportation.
      Citation: Vehicles
      PubDate: 2022-04-27
      DOI: 10.3390/vehicles4020024
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 420-432: A Way Forward for Electric Vehicle in
           Greater Bay Area: Challenges and Opportunities for the 21st Century

    • Authors: Yui-Yip Lau, Andrew Yang Wu, Mak Wing Yan
      First page: 420
      Abstract: The Greater Bay Area (GBA) accounts for a high percentage of pollution due to the large number of internal combustion engines. In the past few decades, there has been a significant increase in internal combustion engines vehicles while electric vehicles have not taken off yet in GBA. To a certain extent, the acceptance of electric vehicles is still questionable from the industrial practitioners and local communities. As such, this research study aims to identify the challenges and opportunities of electric vehicles in GBA to address the future direction of electric vehicles in GBA. In this study, it identifies technology and economy as the main driving forces behind the development of electric vehicles. Furthermore, sustainability, safety, and the life of the batteries may induce the slow adoption of electric vehicles. As expected, the study develops a research agenda and contributes new knowledge in the field of electric vehicle.
      Citation: Vehicles
      PubDate: 2022-04-29
      DOI: 10.3390/vehicles4020025
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 433-444: Perceptions of Transport Automation
           amongst Small- and Medium-Sized Road Haulage Companies in Finland

    • Authors: Markus Pöllänen, Heikki Liimatainen, Erika Kallionpää, Roni Utriainen, Hanne Tiikkaja, Timo Liljamo, Riku Viri, Steve O'Hern
      First page: 433
      Abstract: Transport automation is increasingly being studied from different perspectives; however, the perceptions of road haulage companies have received less attention. This study explores the views of representatives of small- and medium-sized road haulage companies on transport automation in Finland. We conducted an online survey to gather perceptions of automation, which received 254 responses from representatives of a range of different transport industries. The respondents’ views towards automation were generally negative. The overall view was that automation may not be possible for heavy vehicles in Finland due to the adverse weather and driving conditions. The perception was that road haulage automation is unlikely to occur before 2050 in Finland. The results provide valuable insight for vehicle manufacturers, technology developers, policy makers, and haulage companies. As the road haulage industry is dominated by small- and medium-sized companies, hauliers should be supported in actively implementing new technologies.
      Citation: Vehicles
      PubDate: 2022-05-05
      DOI: 10.3390/vehicles4020026
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 445-463: Investigation on Robustness of Vehicle
           Localization Using Cameras and LiDAR

    • Authors: Christian Rudolf Albrecht, Jenny Behre, Eva Herrmann, Stefan Jürgens, Uwe Stilla
      First page: 445
      Abstract: Vehicle self-localization is one of the most important capabilities for automated driving. Current localization methods already provide accuracy in the centimeter range, so robustness becomes a key factor, especially in urban environments. There is no commonly used standard metric for the robustness of localization systems, but a set of different approaches. Here, we show a novel robustness score that combines different aspects of robustness and evaluate a graph-based localization method with the help of fault injections. In addition, we investigate the influence of semantic class information on robustness with a layered landmark model. By using the perturbation injections and our novel robustness score for test drives, system vulnerabilities or possible improvements are identified. Furthermore, we demonstrate that semantic class information allows early discarding of misclassified dynamic objects such as pedestrians, thus improving false-positive rates. This work provides a method for the robustness evaluation of landmark-based localization systems that are also capable of measuring the impact of semantic class information for vehicle self-localization.
      Citation: Vehicles
      PubDate: 2022-05-12
      DOI: 10.3390/vehicles4020027
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 464-481: Optimal Control of Electrified
           Powertrains in Offline and Online Application Concerning Dimensioning of
           Li-Ion Batteries

    • Authors: Felix Deufel, Martin Gießler, Frank Gauterin
      First page: 464
      Abstract: Various energy management systems (driving strategies) have been developed to improve the efficiency of electrified vehicle drives. These include strategies from the field of offline optimization to determine the theoretical optimum for a given system, as well as online strategies designed for an on-board application in the vehicle. In this paper, investigations are performed on an SUV electrified by a 48 V hybrid system in P14 topology regarding both offline and online strategies. To calculate the global optimum, the performance of Dynamic Programming (DP) compared to an Equivalent Consumption Minimization Strategy (ECMS) with an iteratively determined equivalence factor is shown. Furthermore, with regard to online energy management strategies (EMS), it is presented how a predictive Online ECMS achieves additional fuel savings compared to a robust, non-predictive implementation. The simulation-based vehicle development allows detailed investigations regarding interactions between battery requirements and EMS. In this context, it is shown how various battery capacities are exploited by the discussed EMS.
      Citation: Vehicles
      PubDate: 2022-05-19
      DOI: 10.3390/vehicles4020028
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 482-500: A Survey on Mobile Road Side Units in
           VANETs

    • Authors: Thenuka Karunathilake, Anna Förster
      First page: 482
      Abstract: The number of vehicles on the road increases daily, causing many fatal accidents and wasting much time for the average commuter every day due to congestion. Vehicular ad hoc networks (VANETs) were introduced to overcome these issues by enabling vehicle-to-vehicle communication and vehicle-to-infrastructure communication. The prime challenge in VANETs is the necessity of very low communication delays, especially for safety-related applications due to the high mobility nature of vehicles. The VANET architecture introduces a network component, the Road Side Unit (RSU), to meet the required delay limitations. Even though the RSU is a critical component in VANETs, as expected, the RSUs were not deployed throughout the world because of their high investment cost. As a solution, the idea of mobile RSU (mRSU) was introduced, and, ever since, several techniques of mRSU deployment strategies have been proposed. In this survey, we first analyze the importance of the RSU to the VANET architecture with real-world data incorporating the new 5G standard. Then, we investigate the research done in the areas of mRSU and exploit the pros and cons of each mRSU deployment strategy. Finally, we also discuss the future research directions of mRSU, and we explain the challenges connected to these future trends.
      Citation: Vehicles
      PubDate: 2022-05-20
      DOI: 10.3390/vehicles4020029
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 501-528: Modeling Combined Operation of Engine and
           Torque Converter for Improved Vehicle Powertrain’s Complex Control

    • Authors: Maksym Diachuk, Said M. Easa
      First page: 501
      Abstract: This paper proposes an alternative model for describing the hydro-mechanical drive operation of the automatic transmissions. The study is aimed at preparing a reliable model that meets the requirements of sufficient informativeness and rapidity to, basically, be used as a model for optimized control. The study relevance is stipulated by the need for simple and precise models ensuring minimal computational costs in model predictive control (MPC) procedures. The paper proposes a method for coordinating the engine’s control and operating modes, with the torque converter (TC) operating mode, based on the criteria of angular acceleration derivative (jerk), which fosters including the angular acceleration in the state vector for using the optimal control. The latter provides stronger prediction quality than using only the crankshaft angular speed criterion. This moment comprises a study novelty. Additionally, the proposed approach can be helpful in tasks of powertrain automation, autonomous vehicles’ integrated control, elaboration of control algorithms, co-simulations, and real-time applications. The paper material is structured by the modeling stages, including mathematics and simulations, data preparation, testing and validation, virtual experiments, analysis of results, and conclusions. The essence of the problem, goals, and objectives are first presented, followed by the overview of main approaches in modeling the automatic transmission elements. The internal combustion engine (ICE), torque converter, drivetrain, tires, and translational dynamics mathematical models are determined and discussed in detail. The proposed approach convergence on decomposing the indicators of powertrain aggregates by derivatives is demonstrated. The considered method was simulated by using the data of the Audi A4 Quattro. The gear shifting control algorithm was described in detail, and a series of virtual tests for the composed model were carried out. The comparative analysis of the results for the conventional and advanced models of the automatic transmission’s hydro-mechanical drive were performed. The differences of the model outputs were discussed. The approach advantages were noted, as well as the options for extending the proposed technique.
      Citation: Vehicles
      PubDate: 2022-05-23
      DOI: 10.3390/vehicles4020030
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 529-552: Where Am I' SLAM for Mobile Machines
           on a Smart Working Site

    • Authors: Yusheng Xiang, Dianzhao Li, Tianqing Su, Quan Zhou, Christine Brach, Samuel S. Mao, Marcus Geimer
      First page: 529
      Abstract: The current optimization approaches of construction machinery are mainly based on internal sensors. However, the decision of a reasonable strategy is not only determined by its intrinsic signals, but also very strongly by environmental information, especially the terrain. Due to the dynamic changing of the construction site and the consequent absence of a high definition map, the Simultaneous Localization and Mapping (SLAM) offering the terrain information for construction machines is still challenging. Current SLAM technologies proposed for mobile machines are strongly dependent on costly or computationally expensive sensors, such as RTK GPS and cameras, so that commercial use is rare. In this study, we proposed an affordable SLAM method to create a multi-layer grid map for the construction site so that the machine can have the environmental information and be optimized accordingly. Concretely, after the machine passes by the grid, we can obtain the local information and record it. Combining with positioning technology, we then create a map of the interesting places of the construction site. As a result of our research gathered from Gazebo, we showed that a suitable layout is the combination of one IMU and two differential GPS antennas using the unscented Kalman filter, which keeps the average distance error lower than 2m and the mapping error lower than 1.3% in the harsh environment. As an outlook, our SLAM technology provides the cornerstone to activate many efficiency improvement approaches.
      Citation: Vehicles
      PubDate: 2022-05-27
      DOI: 10.3390/vehicles4020031
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 553-566: A Fuzzy Logic Approach for Determining
           Driver Impatience and Stress Leveraging Internet of Vehicles
           Infrastructure

    • Authors: Kevin Bylykbashi, Ermioni Qafzezi, Phudit Ampririt, Makoto Ikeda, Keita Matsuo, Leonard Barolli
      First page: 553
      Abstract: Drivers are held responsible for the vast majority of traffic crashes. Although most of the errors causing these accidents are involuntary, a significant number of them are caused by irresponsible driving behaviors, which must be utterly preventable. Irresponsible driving, on the other hand, is often associated with driver stress and the impatience they show while driving. In this paper, we consider the factors that cause drivers to become impatient and experience stress and propose an integrated fuzzy logic system that determines the stress level in real time. Based on the stress level, the proposed system can take the appropriate action that improves the driving situation and consequently road safety. By using inputs, such as the unnecessary maneuvers that drivers make, the time pressure, and the number of times they are forced to stop, a fuzzy logic controller determines the driver’s impatience, which is then considered alongside other factors, such as the driving experience and history, the behavior of other drivers, and the traffic condition to determine the stress level. We show, through simulations, the feasibility of the proposed approach to accurately determine driver stress and demonstrate some actions that can be performed when stress exceeds certain levels.
      Citation: Vehicles
      PubDate: 2022-06-02
      DOI: 10.3390/vehicles4020032
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 567-585: A Novel Model to Predict Electric Vehicle
           Rapid Charging Deployment on the UK Motorway Network

    • Authors: Keith Chamberlain, Salah Al Majeed
      First page: 567
      Abstract: Recent transformations from internal combustion engines (ICE) to electric vehicles (EVs) are challenged by limited the driving range per charge, thereby requiring the improvement or substantial deployment of rapid charging infrastructure to stimulate sufficient confidence in EV drivers. This study aims to establish the necessary level of EV motorway service station infrastructure for the United Kingdom (UK) based market. The investigation is founded on increasing the appropriate rapid charger availability and shorter charging times. EV charging patterns are determined, focusing on two Volkswagen iD3 EV models by measuring power curves across field-based rapid chargers at one-minute intervals. Datasets are analysed throughout rapid charging field tests. Additionally, variance synthesis is applied to establish variables within this study’s assessment for rapid charger capacity requirements in the UK. The operational performance for the utilised rapid chargers is correspondingly recorded, whilst the EV range is calculated at 3 miles per kWh, revealing a mean power delivery rate of just 27 kW per hour using a 50 kW rapid charger. Time-of-day charging sessions are used to generate data that is then amalgamated into our previous study data, confirming that rapid charging points on UK motorways are used primarily for EV journey range extension. If fully utilised for an entire 24h period, 434 chargers (with a variance consolidation number of 81) are required to service the UK-based motorway EV user base. Moreover, this study establishes that simply replacing current fuel pumps with individual rapid chargers on a like-for-like basis reduces availability and support for novel and existing users and may impact short-term grid availability.
      Citation: Vehicles
      PubDate: 2022-06-10
      DOI: 10.3390/vehicles4020033
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 586-607: Smart Design: Application of an Automatic
           New Methodology for the Energy Assessment and Redesign of Hybrid Electric
           Vehicle Mechanical Components

    • Authors: Umberto Previti, Antonio Galvagno, Giacomo Risitano, Fabio Alberti
      First page: 586
      Abstract: This work aimed to develop an automatic new methodology based on establishing if a mechanical component, designed for a conventional propulsion system, is also suitable for hybrid electric propulsion. Change in propulsion system leads to different power delivery and vehicle dynamics, which will be reflected in different load conditions acting on the mechanical components. It has been shown that a workflow based on numerical simulations and experimental tests represents a valid approach for the evaluation of the cumulative fatigue damage of a mechanical component. In this work, the front half-shaft of a road car was analyzed. Starting from the acquisition of a speed profile and the definition of a reference vehicle, in terms of geometry and transmission, a numerical model, based on longitudinal vehicle dynamics, was developed for both conventional and hybrid electric transmission. After the validation of the model, the cumulative fatigue damage of the front half-shaft was evaluated. The new design methodology is agile and light; it has been dubbed “Smart Design”. The results show that changing propulsion led to greater fatigue damage, reducing the fatigue life component by 90%. Hence, it is necessary to redesign the mechanical component to make it also suitable for hybrid electric propulsion.
      Citation: Vehicles
      PubDate: 2022-06-12
      DOI: 10.3390/vehicles4020034
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 608-620: CFD Analysis of the Location of a Rear
           Wing on an Aston Martin DB7 in Order to Optimize Aerodynamics for
           Motorsports

    • Authors: Thomas P. O’Driscoll, Andrew R. Barron
      First page: 608
      Abstract: The purpose of this study is to identify the initial lateral and vertical location and angle of attack of a GT4-style rear wing on the rear downforce for an Aston Martin DB7 Vantage, prior to installation. The tests were completed with a two-dimensional model, using the Computational Fluid Dynamics (CFD) software, Fluent Ansys. The tests were completed using a range of velocities: 60–80 mph. Optimization of the position of the rear wing aerodynamic device was permitted under the Motorsport UK rules for multiple race series. The results show that while the drag decreases the farther back the wing is located, the desired configuration for the rear wing with regard to downforce is when it is positioned ca. 1850 mm back from the center point of the car, with an attack angle of 5°. Unusually, this is to the front of the boot/rear deck, but it is remarkably similar to where Aston Martin set the rear wing on their Le Mans car in 1995, above where the rear windscreen met the boot hinge, which was based upon wind tunnel studies using a scale model. Our results suggest that while 2D simulations of these types cannot give absolute values for downforce due to aerodynamic device location, they can provide low costs, fast simulation time, and a route for a wide range of cars, making the approach accessible to club motorsports, unlike complex 3D simulation and wind tunnel experimentation.
      Citation: Vehicles
      PubDate: 2022-06-13
      DOI: 10.3390/vehicles4020035
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 621-639: Energy Management Strategy in 12-Volt
           Electrical System Based on Deep Reinforcement Learning

    • Authors: Tan, Jerouschek, Kennel, Taskiran
      First page: 621
      Abstract: The increasing electrification in motor vehicles in recent decades can be attributed to higher comfort and safety demands. Strong steering and braking maneuvers reduce the vehicle’s electrical system voltage, which causes the vehicle electrical system voltage to drop below a critical voltage level. A sophisticated electrical energy management system (EEMS) is needed to coordinate the power flows within a 12-volt electrical system. To prevent the voltage supply from being insufficient for safety-critical consumers in such a case, the power consumption of several comfort consumers can be reduced or switched off completely. Rule-based (RB) energy management strategies are often used for this purpose, as they are easy to implement. However, this approach is subject to the limitation that it is vehicle-model-specific. For this reason, deep reinforcement learning (DRL) is used in the present work, which can intervene in a 12-volt electrical system, regardless of the type of vehicle, to ensure safety functions. A simulation-based study with a comprehensive model of a vehicle electric power system is conducted to show that the DRL-based strategy satisfies the main requirements of an actual vehicle. This method is tested in a simulation environment during driving scenarios that are critical for the system’s voltage stability. Finally, this is compared with the rule-based energy management system using actual vehicle measurements. Concluding measurements reveal that this method is able to increase the voltage at the most critical position of the 12-volt electrical system by approximately 0.6 V.
      Citation: Vehicles
      PubDate: 2022-06-20
      DOI: 10.3390/vehicles4020036
      Issue No: Vol. 4, No. 2 (2022)
       
  • Vehicles, Vol. 4, Pages 30-41: Numerical Study of Longitudinal
           Inter-Distance and Operational Characteristics for High-Speed Capsular
           Train Systems

    • Authors: Bruce W. Jo
      First page: 30
      Abstract: High-speed capsular vehicles are firstly suggested as an idea by Elon Musk of Tesla Company. Unlike conventional high-speed trains, capsular vehicles are individual vessels carrying passengers and freight with the expected maximum speed of near 1200 [km/h] in a near-vacuum tunnel. More individual vehicle speed, dispatch, and position control in the operational aspect are expected over connected trains. This numerical study and investigation evaluate and analyze inter-distance control and their characteristics for high-speed capsular vehicles and their operational aspects. Among many aspects of operation, the inter-distance of multiple vehicles is critical toward passenger/freight flow rate and infrastructural investment. In this paper, the system’s equation, equation of the motion, and various characteristics of the system are introduced, and in particular control design parameters for inter-distance control and actuation are numerically shown. As a conclusion, (1) Inter-distance between vehicles is a function of error rate and second car start time, the magnitude range is determined by second car start time, (2) Inter-distance fluctuation rate is a function of error rate and second car start time, however; it can be minimized by choosing the correct second car start time, and (3) If the second car start time is chosen an integer number of push-down cycle time at specific velocity error rate, the inter-distance fluctuation can be zero.
      Citation: Vehicles
      PubDate: 2022-01-05
      DOI: 10.3390/vehicles4010002
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 42-59: iLDM: An Interoperable Graph-Based Local
           Dynamic Map

    • Authors: Mikel García, Itziar Urbieta, Marcos Nieto, Javier González de Mendibil, Oihana Otaegui
      First page: 42
      Abstract: Local dynamic map (LDM) is a key component in the future of autonomous and connected vehicles. An LDM serves as a local database with the necessary tools to have a common reference system for both static data (i.e., map information) and dynamic data (vehicles, pedestrians, etc.). The LDM should have a common and well-defined input system in order to be interoperable across multiple data sources such as sensor detections or V2X communications. In this work, we present an interoperable graph-based LDM (iLDM) using Neo4j as our database engine and OpenLABEL as a common data format. An analysis on data insertion and querying time to the iLDM is reported, including a vehicle discovery service function in order to test the capabilities of our work and a comparative analysis with other LDM implementations showing that our proposed iLDM outperformed in several relevant features, furthering its practical utilisation in advanced driver assistance system development.
      Citation: Vehicles
      PubDate: 2022-01-08
      DOI: 10.3390/vehicles4010003
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 60-73: Battery Electric Vehicle Efficiency Test
           for Various Velocities

    • Authors: Anja Konzept, Benedikt Reick, André Kaufmann, Ralf Hermanutz, Ralf Stetter
      First page: 60
      Abstract: Since battery electric vehicle (BEV) sales are increasing, the calculation of necessary electric power supply, and energy consumption data, and vehicle range is important. The Worldwide harmonized Light vehicles Test Procedure (WLTP) currently in use can deliver data to collect comparable energy consumption data for different vehicles on defined chassis dynamometer test cycles. Nevertheless, the energy consumption and so the range of BEVs are also dependent on the individual trajectory of the user. Therefore, five velocity profiles are developed in this work. The maximum speeds are based on typical velocities in German city traffic and extra-urban traffic. The energy required to finish a single velocity profile is assumed to be constant despite varying maximum velocities. With this kind of driving profiles it is possible to create an individual and more precise statement on the energy consumption and the range of a BEV. In this work, the profiles are driven on a chassis dynamometer with an VW e-Up. The vehicle charging efficiency is tested with two different AC charging modes and is also taken into account. The drive efficiencies of the tested vehicle are presented in dependence of the velocity profile driven. Finally the results are compared with a real-driving velocity profile and the energy consumption data obtained by the board computer of the vehicle.
      Citation: Vehicles
      PubDate: 2022-01-17
      DOI: 10.3390/vehicles4010004
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 74-99: Improved Mathematical Approach for Modeling
           Sport Differential Mechanism

    • Authors: Maksym Diachuk, Said M. Easa
      First page: 74
      Abstract: Improved mathematical and simulation modes of the active differential mechanism (DM) with controllable torque redistribution would better contribute to developing intelligent vehicle transmissions. The issue is caused by actualizing the precise steerability control using advanced automated transmissions, allowing torque vectoring for all-wheel-drive vehicles and ensuring an option for correcting the vehicle trajectory. This paper presents an alternative mathematical method for obtaining differential equations for modeling vehicle transmission components and its implementation for simulating the Audi sport DM. First, the steerability issues of sport DM technology are discussed, and the sport DM design is described in detail. Then, a mathematical approach is proposed that includes three types of equation systems: generalized dynamics equations, kinematic constraint equations, and gearing condition equations. The approach also considers the flexibility of the clutch’s frictional pack, friction torque, lockup condition, and piston dynamics. Finally, a Simulink model that reflects the DM operation and calculation procedures is developed. A series of simulations of the sport DM operation with forcible torque distribution is carried out. The results show that the proposed mathematical model is universal, efficient, and accurate.
      Citation: Vehicles
      PubDate: 2022-01-21
      DOI: 10.3390/vehicles4010005
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 100-101: Acknowledgment to Reviewers of Vehicles
           in 2021

    • Authors: Vehicles Editorial Office Vehicles Editorial Office
      First page: 100
      Abstract: Rigorous peer-reviews are the basis of high-quality academic publishing [...]
      Citation: Vehicles
      PubDate: 2022-01-30
      DOI: 10.3390/vehicles4010006
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 102-123: Shared Automated Electric Vehicle
           Prospects for Low Carbon Road Transportation in British Columbia, Canada

    • Authors: Orhan Atabay, Ned Djilali, Curran Crawford
      First page: 102
      Abstract: This study explores the long-term energy use implications of electrification, automation and sharing of road vehicles in British Columbia, Canada. Energy use is first analyzed for the years 1990–2016 for forward forecasting, and hypothetical scenarios ranging from conservative to disruptive, incorporating various effects of road vehicle electrification, sharing and automation, as well as influences of other technology disruptions, such as online shopping and e-learning are presented and used to project the road transportation energy use in B.C. to 2060. Transportation energy use projections are compared to those of the Canadian Energy Regulator (CER). When considering only the effect of vehicle electrification, the scenarios show higher energy savings compared to CER’s scenarios. The combined impact of vehicle electrification and automation leads to decreased energy use to 2060 for all scenarios considered. The energy savings for all scenarios, except for the conservative one, are higher than CER’s projections. When the effects of vehicle electrification, automation and sharing are merged, all scenarios yield energy savings beyond the CER projections. Inclusion of other technology disruptions and the effects of pandemics like COVID-19 reduce transportation demand and provide further energy savings. The BAU scenario given in this study shows energy use decreases compared to 2016 of 26.3%, 49%, 62.24%, 72.1% for the years 2030, 2040, 2050, and 2060 respectively.
      Citation: Vehicles
      PubDate: 2022-02-03
      DOI: 10.3390/vehicles4010007
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 124-136: Investigation of Noise Generated by
           Railway Freight Wagon Bogie Type Y25Ls(s)e-K and Proposals of Noise
           Reduction

    • Authors: Ján Ďungel, Peter Zvolenský, Juraj Grenčík, Ján Krivda
      First page: 124
      Abstract: There have been numerous attempts and investigations carried out with the objective to reduce the noise generated by railway freight wagons because noise is one of ever-present negative environmental pollution phenomena. This resulted in strong legislation requirements on noise reduction in railway transport, in the case of freight wagons, only exterior noise is a problem. However, the extremely hard metal structures of the wagons running on hard rails naturally generate high magnitudes of acoustic energy. One big initiative, especially in Germany, seeks a solution in replacement of the cast iron brake pads with the composite one which should result in so-called “silent trains”. But braking is used only during a minor part of the train run, leaving most of the acoustic phenomena of the train run unaffected. In our research, we focused on freight bogies type Y25Ls(s)e-K that are used, including in Slovakia. We simulated the structural natural frequencies to predict vibrations and consequent sound generated by these vibrations. The idea was to localize the vibrations and propose possibilities of noise attenuation. The more realistic view about sound fields was obtained by practical measurements on a moving bogie. Measurements on the test track at a maintenance workshop were done by using a digital acoustic camera Soundcam. For attenuation of noise radiated by the bogie frame, acoustic silencers made from recycled porous fiber material have been applied to the bogie frame. To determine the acoustic difference, the material was applied only on half of the bogie, and then the measurements were carried out. The results showed a promising improvement in reduced noise radiation, which gives support for further research in this area with more precise simulations and more precise coating of the bogie frame as well as the proposal and measurement of noise-attenuating coatings of other structural parts of the freight wagons.
      Citation: Vehicles
      PubDate: 2022-02-03
      DOI: 10.3390/vehicles4010008
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 137-144: Transfer of Statistical Customer Data
           into Relevant Parameters for the Design of Vehicle Drive Systems

    • Authors: Raphael Mieth, Frank Gauterin, Felix Pauli, Harald Kraus
      First page: 137
      Abstract: Vehicle drive systems are often oversized for common customer operation in order to cover the high demands of rare driving events such as towing a trailer, high acceleration or steep inclines. This high torque and power requirement affects the efficiency map and the highest efficiency is around the area of increased torque and speed. However, in everyday use, drive systems are mostly driven by customers at low speed and load, and therefore are not operating in the most efficient area. Designing a drive system that only covers the area of highest customer operation can increase efficiency by moving the sweet spot of efficiency to the relevant area, and thus reduce energy consumption. Therefore, customer data need to be analyzed in order to identify customer requirements and to localize the area of greatest operation. The method presented in this paper analyzes customer data in order to identify design-relevant parameters for a customer-specific drive system design. The available customer data results from event-based counts and are submitted as a statistical frequency distribution. These statistics are compared with discrete time series recorded during test drives in order to derive representative time series that correspond to customer behavior. By applying the time frame-based load analysis to these relevant time series, the desired design-relevant parameters are pointed out.
      Citation: Vehicles
      PubDate: 2022-02-10
      DOI: 10.3390/vehicles4010009
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 145-166: A Development of a New Image Analysis
           Technique for Detecting the Flame Front Evolution in Spark Ignition Engine
           under Lean Condition

    • Authors: Luca Petrucci, Federico Ricci, Francesco Mariani, Gabriele Discepoli
      First page: 145
      Abstract: The aim of herein work is to develop an automatized algorithm for detecting, as objectively as possible, the flame front evolution of lean/ultra-lean mixtures ignited by low temperature plasma-based ignition systems. The low luminosity characterizing the latter conditions makes both kernel formation and combustion development difficult to detect accurately. Therefore, to estimate the igniter capability to efficiently ignite the mixture, ever more performing tools are required. The present work proposes a new image analysis technique, based on a dual-exposure fusion algorithm and on Convolutional Neural Networks (CNNs), to process low brightness images captured via high-speed camera on an optical engine. The performance of the proposed algorithm (PA) is compared to the one of a base reference (BR) algorithm used by the same research group for the imaging analysis. The comparison shows the capability of PA to quantify the flame radius of consecutive combustion cycles with lower dispersion if compared to BR and to correctly detect some events considered as misfires or anomalies by BR. Moreover, the proposed method shows greater capability to detect, in advance, the kernel formation with respect to BR, thus allowing a more detailed analysis of the performance of the igniters. A metric quantitative analysis is carried out, as well, to confirm the above-mentioned results. Therefore, PA results to be more suitable for analyzing ultra-lean combustions, heavily investigated to meet the increasingly stringent legislation on the internal combustion engines. Finally, the proposed algorithm allows us to automatically estimate the flame front evolution, regardless of the user’s interpretation of the phenomenon.
      Citation: Vehicles
      PubDate: 2022-02-16
      DOI: 10.3390/vehicles4010010
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 167-181: Physics-Based Simulation and Automation
           of a Load-Haul-Dump Operation for an Articulated Dump Truck

    • Authors: Bilal Hejase, Umit Ozguner
      First page: 167
      Abstract: Many trucks are used for a class of activities involving a sequence of basic load-haul-dump operations. The repetitiveness of this operation has been an enabler for autonomous vehicle technology in efforts to increase safety and efficiency. In this paper, we present a framework for the automation of the load-haul-dump operation in a mine setting using an articulated dump truck. A simulation environment for the testing of autonomous driving algorithms is developed and a custom mining environment is generated to adapt to our simulation settings. We also present an operational decomposition of the sequence of tasks and develop a finite state machine for high-level decision making based on this decomposition. A path tracking module that considers both bodies of the articulated truck is also developed. The resulting architecture was implemented to achieve autonomy for a load-haul-dump operation in the simulated environment within a fixed path. Experiments show that the proposed FSM-path tracking system can automate the load-haul-dump operation; and that the simulation environment can support the testing and development of autonomous driving algorithms for configurations such as an articulated truck.
      Citation: Vehicles
      PubDate: 2022-02-22
      DOI: 10.3390/vehicles4010011
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 182-198: A Generic Prediction Approach for Optimal
           Control of Electrified Vehicles Using Artificial Intelligence

    • Authors: Felix Deufel, Martin Gießler, Frank Gauterin
      First page: 182
      Abstract: In order to further increase the efficiency of electrified vehicle drives, various predictive energy management strategies (driving strategies) have been developed. Therefore, a generic prediction approach is worked out in this paper, which enables a robust prediction of all traction torque-relevant variables for such strategies. It is intended to be useful for various types of electrification; however, the focus of this work is to the application in hybrid electric vehicles. In contrast to other approaches, no additional information (e.g., telemetry data) is required and thus a reliable prediction is guaranteed at all times. In particular, approaches from the fields of stochastics and artificial intelligence have proven to be effective for such purposes. Within the scope of this work, both so-called Markov Chains and Neural Networks are applied to predict real driving profiles within a required time horizon. Therefore, at first, a detailed analysis of the driver-specific ride characteristics is performed to ensure that real-world operation is represented appropriately. Next, the two models are implemented and the calibration is further discussed. The subsequent direct comparison of the two approaches is performed based on the described methodology, which includes both quantitative and qualitative analyses. Hereby, the quality of the predictions is evaluated using Root Mean Squared Error (RMSE) calculations as well as analyses in time domain. Based on the presented results, an appropriate approach is finally recommended.
      Citation: Vehicles
      PubDate: 2022-03-01
      DOI: 10.3390/vehicles4010012
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 199-218: Potential Analysis for a New Vehicle
           Class in the Use Case of Ride-Pooling: How New Model Developments Could
           Satisfy Customers and Mobility Makers

    • Authors: Martin Dorynek, Lisa-Theres Derle, Martin Fleischer, Alex Thanos, Paul Weinmann, Michael Schreiber, Sebastian Schumann, Tolga Tunc, Klaus Bengler
      First page: 199
      Abstract: Due to changes in mobility and the emergence of new services, it is becoming necessary to establish new vehicle classes between conventional buses and privately owned vehicles. New mobility scenarios need concrete specifications to develop the most user-centered shuttle buses. As a result, we are looking for the requirements and needs of operators and customers. Initially, we want to determine the status quo, as there is no preliminary work in this regard. During the course of extensive literature research, expert interviews, and follow-up workshops, the respective solution space was highlighted and narrowed down. Services such as ride-pooling require adapted vehicle concepts to ensure optimal implementation of their offer. Due to its optimized processes, the automotive industry depends on producing vehicles in a certain quantity and manner. Faster changes and extensive experiments are not possible with the current production approach. Purpose-built vehicle concepts can make mobility services more attractive to customers while facilitating business operations. For instance, potential improvements can be identified in the seating concept.
      Citation: Vehicles
      PubDate: 2022-03-05
      DOI: 10.3390/vehicles4010013
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 219-233: Head Tracking in Automotive Environments
           for Driver Monitoring Using a Low Resolution Thermal Camera

    • Authors: Christoph Weiss, Alexander Kirmas, Sören Lemcke, Stefan Böshagen, Marian Walter, Lutz Eckstein, Steffen Leonhardt
      First page: 219
      Abstract: The steady enhancement of driver assistance systems and the automation of driving functions are in need of advanced driver monitoring functionalities. To evaluate the driver state, several parameters must be acquired. A basic parameter is the position of the driver, which can be useful for comfort automation or medical applications. Acquiring the position through cameras can be used to provide multiple information at once. When using infrared cameras, not only the position information but also the thermal information is available. Head tracking in the infrared domain is still a challenging task. The low resolution of affordable sensors makes it especially difficult to achieve high robustness due the lack of detailed images. In this paper, we present a novel approach for robust head tracking based on template matching and optical flow. The method has been tested on various sets of subjects containing different head shapes. The evaluation does not only include the original sensor size, but also downscaled images to simulate low resolution sensors. A comparison with the ground truth is performed for X- and Y-coordinate separately for each downscaled resolution.
      Citation: Vehicles
      PubDate: 2022-03-08
      DOI: 10.3390/vehicles4010014
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 234-242: Wireless Power Transfer System in Dynamic
           Conditions: A Field-Circuit Analysis

    • Authors: Manuele Bertoluzzo, Paolo Di Barba, Michele Forzan, Maria Evelina Mognaschi, Elisabetta Sieni
      First page: 234
      Abstract: In the paper, a Finite Element (FE) Analysis for investigating the electric properties of a Wireless Power Transfer System (WPTS) devoted to charging the batteries of electric vehicles is performed. In particular, the dynamic-WPTS, which is challenging because of the position-varying properties of the system, is considered. The field analysis is computationally heavy because of thin conductive layers modelling the car chassis: an effective analytical approximation for the field calculation in thin layers is applied to both the car frame bottom and the shielding aluminum layer. This approach allows for an accurate solution and, meanwhile, for a reduction in the computational costs, making the repeated simulations feasible.
      Citation: Vehicles
      PubDate: 2022-03-09
      DOI: 10.3390/vehicles4010015
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 243-258: Autonomous Human-Vehicle Leader-Follower
           Control Using Deep-Learning-Driven Gesture Recognition

    • Authors: Joseph Schulte, Mark Kocherovsky, Nicholas Paul, Mitchell Pleune, Chan-Jin Chung
      First page: 243
      Abstract: Leader-follower autonomy (LFA) systems have so far only focused on vehicles following other vehicles. Though there have been several decades of research into this topic, there has not yet been any work on human-vehicle leader-follower systems in the known literature. We present a system in which an autonomous vehicle—our ACTor 1 platform—can follow a human leader who controls the vehicle through hand-and-body gestures. We successfully developed a modular pipeline that uses artificial intelligence/deep learning to recognize hand-and-body gestures from a user in view of the vehicle’s camera and translate those gestures into physical action by the vehicle. We demonstrate our work using our ACTor 1 platform, a modified Polaris Gem 2. Results show that our modular pipeline design reliably recognizes human body language and translates the body language into LFA commands in real time. This work has numerous applications such as material transport in industrial contexts.
      Citation: Vehicles
      PubDate: 2022-03-09
      DOI: 10.3390/vehicles4010016
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 259-296: A Hybrid Physics-Based and Stochastic
           Neural Network Model Structure for Diesel Engine Combustion Events

    • Authors: King Ankobea-Ansah, Carrie Michele Hall
      First page: 259
      Abstract: Estimation of combustion phasing and power production is essential to ensuring proper combustion and load control. However, archetypal control-oriented physics-based combustion models can become computationally expensive if highly accurate predictive capabilities are achieved. Artificial neural network (ANN) models, on the other hand, may provide superior predictive and computational capabilities. However, using classical ANNs for model-based prediction and control can be challenging, since their heuristic and deterministic black-box nature may make them intractable or create instabilities. In this paper, a hybridized modeling framework that leverages the advantages of both physics-based and stochastic neural network modeling approaches is utilized to capture CA50 (the timing when 50% of the fuel energy has been released) along with indicated mean effective pressure (IMEP). The performance of the hybridized framework is compared to a classical ANN and a physics-based-only framework in a stochastic environment. To ensure high robustness and low computational burden in the hybrid framework, the CA50 input parameters along with IMEP are captured with a Bayesian regularized ANN (BRANN) and then integrated into an overall physics-based 0D Wiebe model. The outputs of the hybridized CA50 and IMEP models are then successively fine-tuned with BRANN transfer learning models (TLMs). The study shows that in the presence of a Gaussian-distributed model uncertainty, the proposed hybridized model framework can achieve an RMSE of 1.3 × 10−5 CAD and 4.37 kPa with a 45.4 and 3.6 s total model runtime for CA50 and IMEP, respectively, for over 200 steady-state engine operating conditions. As such, this model framework may be a useful tool for real-time combustion control where in-cylinder feedback is limited.
      Citation: Vehicles
      PubDate: 2022-03-12
      DOI: 10.3390/vehicles4010017
      Issue No: Vol. 4, No. 1 (2022)
       
  • Vehicles, Vol. 4, Pages 297-313: Estimation of Parallel Hybrid
           Scooter’s Energy Consumption through Real Urban Drive Cycle Using
           IMU

    • Authors: Supriya Kalyankar-Narwade, Ramesh Kumar Chidambaram, Sanjay Patil
      First page: 297
      Abstract: Drive cycle a is primary information useful for analyzing, designing, and optimizing automotive controllers for vehicle homologation. Conventional and electric vehicles are tested and certified based on the specified standard driving cycles as per vehicle category for emission compliance and energy consumption, respectively. In countries such as India, this drive cycle fails to conceal the real-time drive cycles on urban roads with heavy traffic. This real-time drive cycle details the driving skill, congestion, road characteristics, acceleration and deceleration durations, etc. In this context, the real-time drive cycle is captured with the help of an Inertial Measurement Unit. Analysis of IMU measured data with a suitable sampling rate is carried out and energy characterizations are presented in this article. For better accuracy, the IMU data logger is set for an 8 Hz sampling rate which logs the vehicle dynamics data of a scooter. For urban traffic data collection, Pune city is selected and actual energy spent is estimated with the engine, electric, and hybrid modes. State of Charge based switching is carried out with the help of a hybrid controller and observations are tabulated. State of Charge thresholds are monitored and energy-efficient switching is decided. It is estimated from the results that hybrid conversion of a scooter is more efficient due to charge/regeneration into a Lithium-ion battery when the engine powers the wheel and while braking. The range is extended with the above configuration, and further can be increased based on higher battery capacity. Energy management is better handled with a hybrid electric controller for urban roads. Range anxiety issues of EV are lowered in HEV configuration and it is also estimated that parallel Hybrid scooters are more energy-efficient and release lower carbon emissions than conventional vehicles.
      Citation: Vehicles
      PubDate: 2022-03-15
      DOI: 10.3390/vehicles4010018
      Issue No: Vol. 4, No. 1 (2022)
       
 
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