Subjects -> TRANSPORTATION (Total: 216 journals)
    - AIR TRANSPORT (9 journals)
    - AUTOMOBILES (26 journals)
    - RAILROADS (10 journals)
    - ROADS AND TRAFFIC (9 journals)
    - SHIPS AND SHIPPING (39 journals)
    - TRANSPORTATION (123 journals)

TRANSPORTATION (123 journals)                     

Showing 1 - 53 of 53 Journals sorted alphabetically
Accident Analysis & Prevention     Hybrid Journal   (Followers: 123)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 9)
Applied Mobilities     Hybrid Journal   (Followers: 3)
Archives of Transport     Open Access   (Followers: 18)
Asian Transport Studies     Open Access   (Followers: 1)
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Case Studies on Transport Policy     Hybrid Journal   (Followers: 16)
Cities in the 21st Century     Open Access   (Followers: 17)
Danish Journal of Transportation Research / Dansk Tidsskrift for Transportforskning     Open Access   (Followers: 3)
Decision Making : Applications in Management and Engineering     Open Access   (Followers: 2)
Economics of Transportation     Partially Free   (Followers: 14)
Emission Control Science and Technology     Hybrid Journal   (Followers: 2)
eTransportation     Open Access   (Followers: 2)
EURO Journal of Transportation and Logistics     Hybrid Journal   (Followers: 15)
European Transport Research Review     Open Access   (Followers: 24)
Geosystem Engineering     Hybrid Journal   (Followers: 2)
IATSS Research     Open Access  
IEEE Open Journal of Intelligent Transportation Systems     Open Access   (Followers: 7)
IEEE Vehicular Technology Magazine     Full-text available via subscription   (Followers: 7)
IET Electrical Systems in Transportation     Open Access   (Followers: 11)
IET Intelligent Transport Systems     Open Access   (Followers: 12)
IET Smart Cities     Open Access  
IFAC-PapersOnLine     Open Access   (Followers: 1)
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 11)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 12)
International Journal of e-Navigation and Maritime Economy     Open Access   (Followers: 6)
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 11)
International Journal of Electronic Transport     Hybrid Journal   (Followers: 9)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 7)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 16)
International Journal of Mobile Communications     Hybrid Journal   (Followers: 9)
International Journal of Ocean Systems Management     Hybrid Journal   (Followers: 3)
International Journal of Physical Distribution & Logistics Management     Hybrid Journal   (Followers: 14)
International Journal of Services Technology and Management     Hybrid Journal   (Followers: 1)
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 19)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 19)
International Journal of Transportation Engineering     Open Access   (Followers: 2)
International Journal of Transportation Science and Technology     Open Access   (Followers: 12)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 3)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 16)
Journal of Big Data Analytics in Transportation     Hybrid Journal   (Followers: 2)
Journal of Intelligent and Connected Vehicles     Open Access   (Followers: 2)
Journal of KONES     Open Access  
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 6)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 9)
Journal of Navigation     Hybrid Journal   (Followers: 286)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 12)
Journal of Sustainable Mobility     Full-text available via subscription   (Followers: 3)
Journal of Traffic and Transportation Engineering (English Edition)     Open Access   (Followers: 5)
Journal of Transport & Health     Hybrid Journal   (Followers: 12)
Journal of Transport and Land Use     Open Access   (Followers: 27)
Journal of Transport and Supply Chain Management     Open Access   (Followers: 16)
Journal of Transport Geography     Hybrid Journal   (Followers: 28)
Journal of Transport History     Hybrid Journal   (Followers: 13)
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 10)
Journal of Transportation Security     Hybrid Journal   (Followers: 2)
Journal of Transportation Systems Engineering and Information Technology     Full-text available via subscription   (Followers: 12)
Journal of Transportation Technologies     Open Access   (Followers: 15)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 8)
Journal on Vehicle Routing Algorithms     Hybrid Journal  
Les Dossiers du Grihl     Open Access   (Followers: 1)
LOGI ? Scientific Journal on Transport and Logistics     Open Access   (Followers: 1)
Logistics     Open Access   (Followers: 3)
Logistics & Sustainable Transport     Open Access   (Followers: 6)
Logistique & Management     Hybrid Journal  
Mobility in History     Full-text available via subscription   (Followers: 5)
Modern Transportation     Open Access   (Followers: 12)
Nonlinear Dynamics     Hybrid Journal   (Followers: 20)
Open Journal of Safety Science and Technology     Open Access   (Followers: 18)
Open Transportation Journal     Open Access   (Followers: 1)
Packaging, Transport, Storage & Security of Radioactive Material     Hybrid Journal   (Followers: 4)
Periodica Polytechnica Transportation Engineering     Open Access  
Pervasive and Mobile Computing     Hybrid Journal   (Followers: 8)
Proceedings of the Institution of Mechanical Engineers Part F: Journal of Rail and Rapid Transit     Hybrid Journal   (Followers: 15)
Promet : Traffic &Transportation     Open Access  
Public Transport     Hybrid Journal   (Followers: 21)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Research in Transportation Business and Management     Partially Free   (Followers: 8)
Revista Transporte y Territorio     Open Access   (Followers: 1)
Revue Marocaine de Management, Logistique et Transport     Open Access  
Romanian Journal of Transport Infrastructure     Open Access   (Followers: 1)
SourceOCDE Transports     Full-text available via subscription   (Followers: 2)
Sport, Education and Society     Hybrid Journal   (Followers: 13)
Sport, Ethics and Philosophy     Hybrid Journal   (Followers: 3)
Streetnotes     Open Access   (Followers: 1)
Synthesis Lectures on Mobile and Pervasive Computing     Full-text available via subscription   (Followers: 1)
Tire Science and Technology     Full-text available via subscription   (Followers: 3)
Transactions on Transport Sciences     Open Access   (Followers: 7)
Transport     Open Access   (Followers: 17)
Transport and Telecommunication     Open Access   (Followers: 5)
Transport in Porous Media     Hybrid Journal   (Followers: 2)
Transport Problems     Open Access   (Followers: 5)
Transport Reviews: A Transnational Transdisciplinary Journal     Hybrid Journal   (Followers: 10)
Transport technic and technology     Open Access   (Followers: 1)
Transportation     Hybrid Journal   (Followers: 35)
Transportation Engineering     Open Access   (Followers: 1)
Transportation Geotechnics     Full-text available via subscription   (Followers: 1)
Transportation in Developing Economies     Hybrid Journal  
Transportation Infrastructure Geotechnology     Hybrid Journal   (Followers: 8)
Transportation Journal     Full-text available via subscription   (Followers: 17)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 6)
Transportation Research Interdisciplinary Perspectives     Open Access   (Followers: 3)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 41)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 39)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 31)
Transportation Research Procedia     Open Access   (Followers: 7)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 36)
Transportation Safety and Environment     Open Access   (Followers: 2)
Transportation Science     Full-text available via subscription   (Followers: 26)
Transportation Systems and Technology     Open Access  
TRANSPORTES     Open Access   (Followers: 6)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 9)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 1)
Transportrecht     Hybrid Journal   (Followers: 1)
Travel Behaviour and Society     Full-text available via subscription   (Followers: 12)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 4)
Urban Development Issues     Open Access   (Followers: 3)
Urban, Planning and Transport Research     Open Access   (Followers: 33)
Vehicles     Open Access  
Vehicular Communications     Full-text available via subscription   (Followers: 4)
World Electric Vehicle Journal     Open Access   (Followers: 1)
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 6)
Транспортні системи та технології перевезень     Open Access  

           

Similar Journals
Journal Cover
International Journal of Intelligent Transportation Systems Research
Journal Prestige (SJR): 0.301
Citation Impact (citeScore): 1
Number of Followers: 16  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1868-8659 - ISSN (Online) 1868-8659
Published by Springer-Verlag Homepage  [2658 journals]
  • Exploring the Performance of Streaming-Data-Driven Traffic State
           Estimation Method Using Complete Trajectory Data

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      Abstract: This study aims to evaluate the performance of an extended floating car data (xFCD)-based traffic state estimation method proposed by Seo et al. (2015), which does not rely on any strong assumptions such as Fundamental Diagram, using high-resolution complete trajectory data, viz. Zen Traffic Data (ZTD). Traffic state estimated by this method, considering randomly sampled trajectories of ZTD as those of probe vehicles with known penetration rates, are compared with ones obtained by complete ZTD by applying Edie’s generalized definitions. The variation in estimation errors and covering percentages are analyzed for varying settings: spatiotemporal resolution and probe penetration rates.
      PubDate: 2021-07-16
       
  • DB-Corouting: Density Based Coordinated Vehicle Rerouting in Smart
           Environment

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      Abstract: Congestion control is a widely accepted domain in Intelligent Transportation System. Two approaches are commonly used to address the issue: either by controlling the traffic signals or by re-routing the vehicles in a congested state. However, the objective is to minimize the average travel time of the vehicles in a given road scenario. Choosing shortest path could be a solution. But the vehicles, following the shortest path, may face congestion if the decision is done in an un-coordinated manner. This could be due to non-inclusion of crucial decision parameter(s) and lack of cooperative decision on the decisive parameters of the concerned traffic scenario. There are efforts to include the density of the road segments within decision variables. The novelty of the proposed solution is to address the adaptive nature of the density parameter and considers effectively in the solution proposal. The solution considers the effect of density in a nearby road segment is more than the rare one. The introduction of the adaptive nature of this decision variable models the real road network more accurately and subsequent solution is more effective. Exhaustive experimentation has been done, considering various use cases. The proposed Density Based Coordinated Vehicle Rerouting, coined as “DB-Corouting” algorithm is simulated through “SUMO” and “Open Street Map” and the necessary finding ensures the effectiveness of the proposed solution in terms of selected metrics such as average traveling time, average waiting time, Traffic satisfaction Index etc.. The proposed solution outperforms the comparable solutions in terms of the selected metrics and always offers an efficient solution irrespective of traffic distribution.
      PubDate: 2021-07-10
       
  • Evaluating Action Durations for Adaptive Traffic Signal Control Based On
           Deep Q-Learning

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      Abstract: Adaptive traffic signal control is the control technique that adjusts the signal times according to traffic conditions and manages the traffic flow. Reinforcement learning is one of the best algorithms used for adaptive traffic signal controllers. Despite many successful studies about Reinforcement Learning based traffic control, there remains uncertainty about what the best actions to actualize adaptive traffic signal control. This paper seeks to understand the performance differences in different action durations for adaptive traffic management. Deep Q-Learning has been applied to a traffic environment for adaptive learning. This study evaluates five different action durations. Also, this study proposes a novel approach to the Deep Q-Learning based adaptive traffic control system for determine the best action. Our approach does not just aim to minimize delay time by waiting time during the red-light signal also aims to decrease delay time caused by vehicles slowing down when approaching the intersection and caused by the required time to accelerate after the green light signal. Thus the proposed strategy uses not just information of intersection also uses the data of adjacent intersection as an input. The performances of these methods are evaluated in real-time through the Simulation of Urban Mobility traffic simulator. The output of this paper indicate that the short action times increase the traffic control system performances despite more yellow signal duration. The results clearly shows that proposed method decreases the delay time.
      PubDate: 2021-06-29
       
  • A Smart Coordination System Integrates MCS to Minimize EV Trip Duration
           and Manage the EV Charging, Mainly at Peak Times

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      Abstract: The fixed public charging stations (FCS) network is challenged by widespread of electric vehicle (EV) uses. Therefore, there is exploitation of the many parks spread over the territory of a smart city by means of mobile charging stations (MCS). That can be set up or moved anywhere as needed. This allows for the rapid expansion of the charging infrastructure. In this work, we propose an architecture system consisting of a set of algorithms to manage electric vehicle charging plans in terms of minimizing journey time, including waiting and charging time at charging stations (CS). Thus, During the CS selection decision, the system takes into consideration the amount of sufficient energy for the EV to reach the specified CS, the remaining amount of energy in stock if the selected CS is the MCS type, the CS Real-time status, and the first-come-first-served policy based on providing charge seats in CS. Moreover, the dynamically system regulates each FCS at its peak time of its MCS operation, ensuring a semi-permanent equilibrium in electrical grid usage and reducing congestion by changing the flow of vehicles that are directed towards FCSs for charging. The evaluation results demonstrate, in the context of the Helsinki City scenario, the effectiveness of the proposed system and algorithms, in terms of achieving the above-mentioned objectives.
      PubDate: 2021-06-09
      DOI: 10.1007/s13177-021-00258-1
       
  • A Short-term Traffic Speed Prediction Model Based on LSTM Networks

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      Abstract: To successfully deploy an intelligent transportation system, it is essential to construct an effective method of traffic speed prediction. Recently, due to the advancements in sensor technology, traffic data have experienced explosive growth. It is therefore a challenge to construct an efficient model with highly accurate predictions. To improve the accuracy and the efficiency of short-term traffic predictions, we propose a prediction model based on deep learning approaches. We use a long short-term memory (LSTM) network to analyze sequential sensor data to predict the car speed of the next time interval on the freeway. Unlike the traditional model that only considers the changes in traffic speed which is used to derive the temporal and spatial features from the prediction road section, we mainly consider the features of the number of the most representative car types and the traffic speed variation of the front road segment that is ahead of the prediction road segment in addition to the number of cars, the road occupancy, and the traffic speed latency to successfully learn and capture the hidden patterns from the sensor data so as to improve the prediction accuracy. To the best of our knowledge, very few investigations have been conducted to consider the correlation between car speed and car type for a prediction model. Moreover, our extensive experiments demonstrate that the proposed method for traffic speed prediction has achieved high accuracy.
      PubDate: 2021-06-09
      DOI: 10.1007/s13177-021-00260-7
       
  • An Improved Method of Nonmotorized Traffic Tracking and Classification to
           Acquire Traffic Parameters at Intersections

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      Abstract: High computational cost and low tracking stability make it still a challenging task to acquire nonmotorized traffic parameters at intersections via vision-based method. In order to address the above issues, our study improves a cooperative tracking and classification method, and proposes a vision-based data collection system to monitor nonmotorized traffic at intersections. The system utilizes the combination of two tracking algorithms, Kernelized Correlation Filter and Kalman filter, to ensure the continuous tracking. Based on multivariate feature, K-means clustering and Support Vector Machine are implemented to classify nonmotorized traffic according to the motion and appearance feature respectively. As a result, the proposed system can acquire trajectories of pedestrians and cyclists and extract traffic parameters, including flow and velocity. Our method performs well in both efficiency and accuracy by fusing simple but effective algorithms and is robust in the complex scenario especially at large-scale intersections with limited training samples. The experimental results show that it can extract more trajectories with low computational lost. Moreover, the error of flow and velocity result is controlled within acceptable limits, which directly proves it feasible to collect field data in project applications.
      PubDate: 2021-06-01
      DOI: 10.1007/s13177-020-00247-w
       
  • Influence of Moving Light Guide System on Traffic Flow in Presence of
           Autonomous Vehicles

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      Abstract: As a measure against traffic congestion in uphill and sagging sections of roads, a moving light guide system using LED light emitters installed near the road shoulder has been introduced. In addition, despite the increasing development of autonomous vehicles, no studies have been conducted on the effects of this system under a mixture of both manually driven and autonomous vehicles. The purpose of this study was to conduct a driving simulator experiment to understand the influence of the moving light guide system on the traffic flow when the autonomous driving vehicles are mixed with manual vehicles. Our observations suggest that the moving light guide system may be effective for manual vehicles, even in the presence of autonomous vehicles.
      PubDate: 2021-06-01
      DOI: 10.1007/s13177-021-00252-7
       
  • Traffic Optimization Methods of Urban Multi-leg Intersections

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      Abstract: The research on the organization of intersections has always been the key and difficult point of road optimization, especially for multi-leg intersections. Since the traffic flow direction and the number of conflict points of multi-leg intersection are more than that of ordinary intersection, the difficulty of organization and optimization increases accordingly. At present, the research on multi-leg intersections is not much or deep enough at home and abroad. In general, it is transformed into a roundabout when the traffic volume is small, and the signal lamp is set with the increase of traffic volume. However, the signalized roundabout is not applicable when the traffic flow at the signal roundabout increases to a certain extent. Therefore, this paper introduces Huangsha six import signal free roundabout in Dianjiang County of Chongqing as the research case, takes the traffic delay and queue length as the evaluation index, and two new optimization methods are proposed on the basis of the original methods, namely improved the signalized roundabout and the signalized intersection. To assess the feasibility of these methods, VISSIM is used for simulation comparison. The simulation results show that compared with the current traffic situation, the average delay time of vehicles in the signalized intersection optimization method is reduced by 9.3 s, the average queue length decreased by 3.7 m, and its indicators are better than the signalized roundabout. Therefore, the method of signalized intersection not only provides a good mirror for the reconstruction of multi-leg intersections, but also offers relevant theoretical and practical exploration.
      PubDate: 2021-06-01
      DOI: 10.1007/s13177-020-00245-y
       
  • High-Resolution Image Data Collection Scheme for Road Sensing Using
           Wide-Angle Cameras on General-Use Vehicle Criteria to Include/Exclude
           Collected Images for Super Resolution

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      Abstract: Fisheye cameras or wide-angle cameras used on automobiles will have various future applications as “distributed sensors in daily transport” -- objects on roadside are frequently observed multiple times by multiple vehicles. Although the object regions are often captured with relatively low image quality (low resolution and large blur) resulting from the character of the lens, it is possible to enhance their quality by post-processing using super resolution (SR) technology. Here, it is required to decide which images to use as inputs for SR: a greater number of lower-quality images or fewer higher-quality images. We evaluated and discussed the input image quality necessary to obtain most effective SR results, especially focusing on degree of image blur. As a conclusion, we found a criterion that was related to the blur level of the initial input image of SR. Then, we considered its potential use as a requisite in observing road environments.
      PubDate: 2021-06-01
      DOI: 10.1007/s13177-020-00243-0
       
  • Segment-Based Count Regression Geospatial Modeling of the Effect of
           Roadside Land Uses on Pedestrian Crash Frequency in Rural Roads

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      Abstract: Pedestrians are one of the most vulnerable road users that are prone to injury and death. Various factors have been incorporated into transportation systems in order to improve pedestrian safety in recent studies. The main objective of this study is to develop a segment-based micro-level geospatial-based approach to find the interaction between the frequency of pedestrian crashes and roadside land uses in rural roads. The proposed approach uses geospatial functions for extracting contributing factors and two different lengths of road segments as analysis units to reduce the randomness of the crash locations. These spatial factors are used to estimate the number of pedestrian crashes in each segment using four count-based regression models, including Poisson, negative binomial (NB) regression models, and their zero-inflated extensions. The latest four-year reporting crashes and land use data for a four-lane divided rural multilane in Guilan province, Iran, were tested to illustrate the models' accuracy and performance in the proposed approach. Modeling results highlighted the superiority of the Poisson regression model and its zero-inflated extension for two different strategies of segment length. Moreover, the results showed that residential, commercial, governmental, institutional, utility, and religious land uses have various decisive impacts on the increase of pedestrian crash frequency. This information could be used in long-term transportation systems planning, which would lead to an improvement in pedestrian safety levels.
      PubDate: 2021-06-01
      DOI: 10.1007/s13177-020-00250-1
       
  • Influence of Weather Features in Determining Sudden Braking

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      Abstract: Understanding conditions and situations causing abnormal driving behaviors like sudden braking or sudden acceleration is important for preventing traffic accidents. Previous studies have used probe vehicle data to detect risky situations where sudden braking frequently occurred. However, they have mainly focused on location and vehicle-related factors. In this paper, we build models which discriminate sudden braking using a machine learning method. The models use weather-related information as well as probe data. To investigate how weather-related factors help to determine sudden braking, we conducted extensive experiments using probe data obtained from dashboard cameras and two types of weather-related information obtained from meteorological observatories (MO) and AMeDAS. Experimental results illustrate that using weather-related information improves performance in determining sudden braking and that the temporally and spatially denser characteristics of weather-related factors from AMeDAS help to compensate for insufficiencies in the model with MO data.
      PubDate: 2021-06-01
      DOI: 10.1007/s13177-021-00253-6
       
  • A Collaborative 1-to-n On-Demand Ride Sharing Scheme Using Locations of
           Interest for Recommending Shortest Routes and Pick-up Points

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      Abstract: Ride-sharing offers a cheaper means of transportation to riders whose routes are similar to the driver’s route within an acceptable time. It is a new paradigm in the urban road transportation system to reduce traffic and enhances the economy of car owners. Unlike 1-to-n ride-sharing that allows n-rider to share rides with a driver, 1-to-1 ride-sharing does not maximize the advantages of ride-sharing. However, the major challenge of 1-to-n ride-sharing is how to match a minimum number of riders with a driver without compromising their privacy, and solves how to synchronize car owners’ destinations with their riders’ destinations without incurring a delay. Meanwhile, most of the existing ride-sharing schemes are developed for 1-to-1 ride-sharing services, where a rider shares a ride with a driver. In this paper, an effective collaborative ride-sharing scheme is proposed for 1-to-n ride sharing. Our scheme is capable of recommending optimal routes and pick-up points for riders and drivers using their previously visited location’s record. It is also capable of providing a single but centralized ride-sharing public management system for every car owner. Thus, eliminates the inefficient disjointed private carpooling form of 1-to-1 ride sharing. It consists of a trust model that is used for computing trust value for riders and drivers, and a similarity model to compute the similarity between locations and riders or drivers. More so, it allows more than a driver to provide collaborative ride-sharing for a rider in case the rider’s destination is farther than the driver’s destination. The scheme is analyzed, the experimental and analysis results show that our scheme is not only secure but also with low computational latency.
      PubDate: 2021-06-01
      DOI: 10.1007/s13177-020-00234-1
       
  • Fitting Knock-on Delay Duration Distributions using High-Speed Train
           Operation Records

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      Abstract: Delay distribution models are helpful in real-time train dispatching. These models can aid dispatchers to estimate the probability of delay duration and better manage train delays in practice. In this paper, based on the actual train operation records at Xiamen-Shenzhen high-speed railway (HSR) from April 2015 to October 2016, the number of knock-on delay (KD) trains and the number of arrival trains were counted. The statistical result demonstrated the train frequency affected the KD train frequency to some extent. The statistical method was used to establish the knock-on delay duration distribution (KDDD) model. The five common distribution models fitted KDDDs at peak hours and off-peak hours at four stations. The maximum likelihood estimate obtained the parameters of the five theoretical distributions. The log-normal distribution fitted the KDDDs best at both periods and four stations according to the Kolmogorov–Smirnov (K-S) test result. The probability of knock-on delay duration was calculated, and the result indicated the probability of knock-on delay duration in (1,5) min were the maximum, and those at peak hours were more than those at off-peak hours at Huizhou South and Houmen.
      PubDate: 2021-06-01
      DOI: 10.1007/s13177-020-00246-x
       
  • Blind Spot Detection System in Vehicles Using Fusion of Radar Detections
           and Camera Verification

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      Abstract: Sensors are the quintessential part of Blind Spot Detection (BSD) systems, which have a profound effect on the performance of the system. Every sensor has its unique deficiencies that can deteriorate the performance of the system under grievous circumstances. Hence, making vital tasks in BSD such as object detection arduous. Indeed, previous studies have demonstrated that data fusion techniques can diminish the adverse effects of sensors and improve detection accuracy in the BSD system. One of the main advantages of data fusion is to improve detection accuracy and reduce the processing time by multiple sensors cooperation. We propose a BSD model that objects are detected in consecutive time intervals in the BSD system. Then, association techniques are employed for multi-sensor fusion since all sensors data are not ordinarily ready for fusion simultaneously. It should be noted that the orthodox approach in data association techniques in BSD often includes a global nearest neighbor, joint probabilistic data association, and multiple hypothesis tests. We simulate and compare these techniques by tracking multiple targets and multi-sensor fusion using virtual data in MATLAB. Furthermore, we illustrate that our multi-sensor fusion detection accuracy in the BSD system is augmented compared to a single sensor BSD system.
      PubDate: 2021-06-01
      DOI: 10.1007/s13177-021-00254-5
       
  • Unsignalized Intersection Level of Service: A Bicyclist’s
           Perspective

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      Abstract: As the traffic conditions at unsignalized intersections are complex and chaotic, the perceived satisfaction levels of bicyclists are controlled by several factors. Although complex, the Bicycle Level of Service (BLOS) studies at this facility are highly important so as to improve its performance from the perspective of bicycling. This study is an initial attempt to identify and model the factors influencing BLOS at unsignalized intersections under mixed traffic conditions. For analysis purposes, extensive data sets on the geometric details and operational characteristics are collected from 70 unsignalized intersection approaches located in various parts of five Indian cities. Subsequently, eight variables (effective approach width, peak hour volume, conflicting traffic volume, and average bicycle delay, etc.) having significant influences on the perceived satisfaction levels of through bicyclists are identified. Of all these variables, the average bicycle delay is observed to have the highest influence on user-perceived BLOS. This suggests that the minimization of bicycle delay is the utmost important strategy to enhance perceived satisfaction levels of bicyclists. Further, a step-wise regression-based BLOS model has been developed for the service quality assessment at unsignalized intersection approaches. This model has shown a very good prediction ability in the present context with a coefficient of determination (R2) value of 0.83 with averaged observations. A service scale is also defined to convert the outcomes of this model to letter-graded service classes A–F (excellent–worst). The field application of these tools has shown that above 89% of the investigated sites are offering BLOS ‘C’ or inferior. This is a serious concern for the inhabitants in the long run. Hence, the modeled attributes should be prioritized (in their identified order of importance) in the transportation planning process to avail the better service classes effectively.
      PubDate: 2021-06-01
      DOI: 10.1007/s13177-020-00244-z
       
  • Evaluation of the Driver Visibility Affecting the Occurrence of Crossing
           Accidents

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      Abstract: This research aims to clarify the influence of driver visibility on crossing accidents. We investigated 1101 accidents occurring at 621 intersections in the Hakata-ku Ward, Fukuoka City, from 2015 to 2017. We calculated the yearly accident rate at each intersection based on the accident data and evaluated driver visibility with surveyed intersection information. It was found that the accident rate was high when visibility was poor regardless of the number of lanes on the secondary road at locations where many accidents occurred, and the accident rate was high when the number of lanes on the secondary road was low throughout Hakata Ward.
      PubDate: 2021-06-01
      DOI: 10.1007/s13177-020-00249-8
       
  • A Literature Review on Interactions Between Stakeholders Through
           Accessibility Indicators Under Mobility as a Service Context

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      Abstract: This study aims to explore accessibility indicators influencing the interactions between users, transport service providers (TSPs), and a platform operator, generating a conceptual framework for modeling these interactions under Mobility as a Service context. A systematic literature review was conducted to identify all studies focusing on indicators and modeling the interactions. There are limitations in integrating psychological indicators and dynamic pricing into the existing models. Moreover, there are gaps in considering monthly service packages, the efficiency of transport systems, and the perspectives of the TSPs for modeling the demand–supply interactions. The study ends with conclusions, discussions, and directions for further studies.
      PubDate: 2021-05-10
      DOI: 10.1007/s13177-021-00257-2
       
  • Prediction of Bus Travel Time over Intervals between Pairs of Adjacent Bus
           Stops Using City Bus Probe Data

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      Abstract: Prediction of bus travel time is a crucial tool for passengers. We present methods to predict bus travel time over intervals between pairs of adjacent bus stops using city bus probe data. We apply Gradient Boosting Decision Trees to several kinds of features extracted from the probe data. Experimental results illustrate that adding a combination of features improves the accuracy of travel time prediction over the target interval. In particular, the method using a combination of the travel time over the interval previous to the target one and the number of stops the bus makes before reaching the target interval has better performance than the other methods which use all the other combinations of four features used in this study.
      PubDate: 2021-04-30
      DOI: 10.1007/s13177-021-00251-8
       
  • Analysis and Improvement of Geometric Parallel Parking Methods with
           Respect to the Minimum Final Lateral Distance to the Parking Spot

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      Abstract: Nowadays, the autonomous parking and park assist systems are getting more attention since they provide comfort and relief to the drivers and prevent parking-lot accidents. In this paper, we overview several main geometric path planning methods for autonomous parking of non-holonomic vehicles and we analyze their performances with respect to the final lateral distance to the parking spot. To the best of our knowledge, this kind analysis has never been done before for autonomous parallel parking algorithms. Moreover, we provide a new geometric method to reduce the final lateral distance between the vehicle and the parking spot. While the reference methods are insufficient for the final lateral distance, the proposed method introduces a realizable solution for long vehicles and enhances the performance for short vehicles. Simulations which are performed with various types of vehicles provide up to 48% better performance and show the efficiency of the new approach clearly.
      PubDate: 2021-04-24
      DOI: 10.1007/s13177-021-00256-3
       
  • Smart Roads Geometric Design Criteria and Capacity Estimation Based on AV
           and CAV Emerging Technologies. A Case Study in the Trans-European
           Transport Network

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      Abstract: Smart roads, AV and CAV are emerging technologies that represent the new paradigm of mobility. To support the public and private road operators better prepare themselves to implement these technologies in their respective existing or planned infrastructures, there is an urgent need to develop an integrated analysis framework to evaluate the impact of these novel systems on road capacity and safety in function of different market penetration levels of AVs and CAVs. The research focuses on novel smart road geometric design and review criteria based on the performance of AVs and CAVs. The case study of one of the first planned smart roads in Italy has been analysed.
      PubDate: 2021-04-19
      DOI: 10.1007/s13177-021-00255-4
       
 
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