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
Journal Cover
Journal of Advanced Transportation
Journal Prestige (SJR): 0.581
Citation Impact (citeScore): 1
Number of Followers: 12  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0197-6729 - ISSN (Online) 2042-3195
Published by Hindawi Homepage  [339 journals]
  • Characteristics Analysis and Equilibrium Optimization of Mixed Traffic
           Flow considering Connected Automated and Human-Driven Vehicles

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      Abstract: Considering the impact of informatization condition, vehicles on the road network are divided into connected automated vehicles (CAVs) and human-driven vehicles (HDVs), which follow the principle of system optimization and stochastic user equilibrium, respectively. Taking the road network reserve capacity maximization model under the condition of road capacity constraint as the upper-level programming and the traffic assignment model under heterogeneous flow environment as the lower level programming, then a bilevel programming model is constructed. Among them, the nonuniform demand growth multiplier is adopted for each OD pair to reflect the inconsistency of traffic demand structure growth, and the calculation of link capacity is related to the market penetration of CAVs. The incremental method, method of successive averages, and simulated annealing algorithm are used to solve the model, and the effects of different market penetration on road network capacity, travel time, and saturation are analyzed through a numerical example. The relevant data under different weights are normalized and the optimal deployment scheme of CAVs and HDVs in different periods is obtained by comprehensive evaluation. Meanwhile, the mixed equilibrium flow state is explored under the premise of given market penetration to verify the feasibility of the model and algorithm.
      PubDate: Fri, 12 Aug 2022 07:50:01 +000
       
  • Off-Ramp Vehicle Mandatory Lane-Changing Duration in Small Spacing Section
           of Tunnel-Interchange Section Based on Survival Analysis

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      Abstract: Due to topography, geology, and other factors, small spacing sections are common between tunnels and interchange exits. There is mandatory lane-changing behavior for vehicles that need to leave the main line and drive inside the road before leaving the tunnel. Affected by the “white hole” of a tunnel, the lane-changing behavior of off-ramp vehicles differs significantly from that of original roadbed sections. To study the mandatory lane-changing duration (MLCD) of off-ramp vehicles in small spacing sections of the tunnel to interchange in mountainous areas, their time and trajectory data were collected based on a driving simulator. According to the characteristics of the data, the survival analysis method was used to analyze the influence on the MLCD of off-ramp vehicles of the spacing section between the tunnel and interchange, vehicle types, tunnel types, ramp types, highway service level, and whether to set exit advance guide signs in the tunnel and the Cox proportional hazards model of the MLCD was established. The results showed that the spacing of the tunnel interchange, the road service level, and whether to set exit advance guide signs in the tunnel had significant effects on the MLCD of vehicles, while the vehicle, the tunnel, and the ramp types did not. When the spacing section of the tunnel interchange was less than 500 m, the off-ramp vehicle had continuous mandatory lane-changing behavior, and when the distance decreased from 400 m to 300 m, the risk rate of lane changing increased by 5.68 times. Survival function curve estimation provided the 75% quantile of MLCD of off-ramp vehicles under different conditions, which could provide a theoretical reference for setting the minimum distance between a tunnel and interchange exit.
      PubDate: Thu, 11 Aug 2022 06:05:02 +000
       
  • Research on Lateral and Longitudinal Coordinated Control of Distributed
           

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      Abstract: Aiming at the problem that it is difficult to ensure the trajectory tracking accuracy and driving stability of the distributed driven driverless formula racing car under high-speed tracking conditions, a lateral and longitudinal coordinated control strategy is proposed. Based on the adaptive model predictive control theory, the lateral motion controller is designed, and the prediction time domain of the controller is changed in real time according to the change of vehicle speed. Based on the sliding mode variable structure control theory, a longitudinal motion controller is designed to accurately track the desired vehicle speed. Considering the coupling between the lateral and longitudinal controls, the lateral controller inputs the longitudinal speed and displacement of the vehicle, using the feedback mechanism to update the prediction model in real time, the longitudinal controller takes the front wheel angle as the input, the driving torque is redistributed through the differential drive control, and the lateral and longitudinal coordinated control is carried out to improve the trajectory tracking accuracy and driving stability. The typical working conditions are selected for co-simulation test verification. The results show that the lateral and longitudinal coordinated control strategy can effectively improve the vehicle trajectory tracking control accuracy and driving stability.
      PubDate: Thu, 11 Aug 2022 05:50:03 +000
       
  • Analysis of Fuel Tank Collision Structure Based on Defense Point Method

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      Abstract: Aiming at the impact process of a fuel tank, which is a transient energy conversion process, the material absorbs energy through deformation to analyze the mechanical properties of the fuel tank during the impact process. The defense node method is adopted to simulate the dynamic response of the fuel tank during impact. The results show that it can accurately evaluate the safety of the container.
      PubDate: Wed, 10 Aug 2022 06:20:01 +000
       
  • Urban Arterial Signal Coordination Using Spatial and Temporal Division
           Methods

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      Abstract: Traffic signal coordination on urban arterials often requires that timing plans be divided either spatially into clusters of signalized intersections or temporally as time-of-day-based plans. This research proposes a method of dividing timing plans by both spatial and temporal factors simultaneously, in order to provide a dynamic coordinated signal control plan suitable for handling variations in intersection demands and fluctuations in traffic flow. The optimal coordination phase difference of adjacent space coordination subarea is obtained through the method of set operation, so that the spatial subareas can be connected. Similarly, timing plans are dynamically grouped into times of day using the concept of risk decision-making by solving the minimum value of the risk function. Divisions can be further adjusted in real time by changing the conditions, thus resulting in dynamic coordinated signal control. The proposed method was tested in a microscopic simulation of a real-world arterial based on empirical volumes and turning movements. The results showed that the proposed model produced greater reductions in delay and queue length when compared to the methods that subdivide by spatial or temporal thresholds alone. Sensitivity analysis revealed that the proposed method was better suited to imbalances in directional volumes when compared to spatial or temporal division methods alone.
      PubDate: Tue, 09 Aug 2022 07:50:02 +000
       
  • Improvement of Multiclass Classification of Pavement Objects Using
           Intensity and Range Images

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      Abstract: Automated recognition of road surface objects is vital for efficient and reliable road condition assessment. Despite recent advances in developing computer vision algorithms, it is still challenging to analyze road images due to the low contrast, background noises, object diversity, and variety of lighting conditions. Motivated by the need for an improved pavement objects classification, we present Dual Attention Convolutional Neural Network (DACNN) to improve the performance of multiclass classification using intensity and range images collected with 3D laser imaging devices. DACNN fuses heterogeneous information in intensity and range images to enhance distinguishing foreground from background, as well as to improve object classification in noisy images under various illumination conditions. DACNN also leverages multiscale input images by capturing contextual information for object classification with different sizes and shapes. DACNN contains an attention mechanism that (i) considers semantic interdependencies in spatial and channel dimensions and (ii) adaptively fuses scale-specific and mode-specific features so that each feature has its own level of contribution to the final decision. As a practical engineering project, dataset are collected from road surfaces using 3D laser imaging. DACNN is compared with four deep classifiers that are widely used in transportation applications. Experiments show that DACNN consistently outperforms the baselines by 22–35% on average in terms of the F-score. A comprehensive discussion is also presented regarding computational costs and how robustly the investigated classifiers perform on each road object.
      PubDate: Tue, 09 Aug 2022 07:20:02 +000
       
  • RFM Model and K-Means Clustering Analysis of Transit Traveller Profiles: A
           Case Study

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      Abstract: Public transportation users increase as the population grows. In Taipei, Taiwan, this tendency is observed by analyzing historical data from the Mass Rapid Transit (MRT) and economy-shared bicycle (known as YouBike) riders. While this trend exists, the Taipei City government promotes green transportation by providing discounts to users who transfer from MRT or bus to YouBike within a particular period. Therefore, this study focuses on analyzing the patterns of users in order to identify possible clusters. Clusters of customers can be considered fundamental and competitive factors for the Ministry of Transportation to encourage the use of green transportation and promote a sustainable environment. Based on big data smart card information, this paper proposes using the RFM and K-means clustering algorithm to analyze and construct mode-switching traveller profiles on MRT and YouBike riders. As a result, three distinct clusters of MRT-YouBike riders have been identified: potential, vulnerable, and loyal. There are also suggestions regarding the most profitable groups, which customers to focus on, and to whom give special offers or promotions to foster loyalty among transit travellers.
      PubDate: Mon, 08 Aug 2022 05:05:01 +000
       
  • Trajectory Clustering in an Intersection by GDTW

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      Abstract: GPS trajectory data in intersections are series data with different lengths. Dynamic time wrapping (DTW) is good to measure the similarity between series with different lengths, however, traditional DTW could not deal with the inclusive relationship well between series. We propose a unified generalized DTW algorithm (GDTW) by extending the boundary constraint and continuity constraint of DTW and using the weighted local distance to normalize the cumulative distance. Based on the density peak clustering algorithm DPCA using asymmetric GDTW to measure the similarity of two trajectories, we propose an improved DPCA algorithm (ADPC) to adopt this asymmetric similarity measurement. In experiments using the proposed method, the number of clusters is reduced.
      PubDate: Mon, 08 Aug 2022 04:20:01 +000
       
  • Charging-Related State Prediction for Electric Vehicles Using the Deep
           Learning Model

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      Abstract: Electric vehicles (EVs) are becoming the potential contender for the conventional gasoline vehicles in view of the environment-friendly and energy-efficient characteristics. The prediction of EV charging-related states (defined in this study as home charge, outside charge, home stop, outside stop, low-battery travel, and high-battery travel) could help to identify the future charging demand (power consumption) of EV individuals. Specifically, it could guide the operation and management of charging facilities and also provide tailored charger availability information based on users’ real-time locations. This study aims to predict charging-related states of individual EVs using a deep learning approach. We first propose a tangible approach to convert EV trajectory data into state sequences and then develop a bidirectional gated recurrent unit model with attention mechanism (Bi-GRU-Attention) to forecast EV states. A sensitivity analysis is conducted to tune and/or calibrate parameters in the model based on plug-in hybrid EV trajectories dataset collected in Shanghai, China. Experiment results show that (i) the proposed method could achieve an average accuracy of 77.15% with a 1-hour prediction length and it outperforms the baseline models for all tested prediction lengths; (ii) it is also revealed that the prediction accuracy varies dramatically with different states and time periods. Among all states, the proposed model has a higher prediction accuracy on “home stop” (89.0%). As for time periods, the EV states around 08:00 am and 04:00 pm are hard to predict, and a comparatively low prediction accuracy (close to 60%) is obtained; and (iii) the stability and robustness analysis implies that the proposed model is stable and insensitive to SOC noise or season.
      PubDate: Mon, 08 Aug 2022 04:20:00 +000
       
  • A Hybrid Framework for Real-Time Dispatching of Airline Unit Load Devices
           under Demand Variations

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      Abstract: This study is devoted to a new research topic in real-time airline operations, the redispatching of unit load devices (ULDs) under demand variations. We develop a new hybrid framework to solve the problem of ULD redispatch following the time-sequence decision-making required by airlines. The hybrid framework is developed by integrating techniques including the probability distribution technique to simulate different types of operational demand, the adjustable number of stages which is needed to meet the requirements of a decision-making process following a time sequence and the time pressure characteristic of real operations, and the scenario tree and probability rule approaches which are aimed and representing all possible demand scenarios for a stage, while the network flow technique is applied to represent the movement and location of ULDs at each airport over time and is used for the development of the associated mathematical model and the simulation. We performed a simulation of 2,000 cases based on different operational days and types of operational demand. The results show that this hybrid framework is able to achieve stability and also a small variability of both ULD operating costs and solution times, which could allow the airline to save on ULD operating costs, under demand variations in real-time operations.
      PubDate: Mon, 08 Aug 2022 04:05:01 +000
       
  • Vision-Based Branch Road Detection for Intersection Navigation in
           Unstructured Environment Using Multi-Task Network

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      Abstract: Autonomous vehicles need a driving method to be less dependent on localization data to navigate intersections in unstructured environments because these data may not be accurate in such environments. Methods of distinguishing branch roads existing at intersections using vision and applying them to intersection navigation have been studied. Model-based detection methods recognize patterns of the branch roads, but are sensitive to sensor noise and difficult to apply to various complex situations. Therefore, this study proposes a method for detecting the branch roads at the intersection using deep learning. The proposed multi-task deep neural network distinguishes the branch road into a shape of rotated bounding boxes and also recognizes the drivable area to consider obstacles inside the box. Through the output of the network, an occupancy grid map consisting of one branch road at an intersection is obtained, which can be used as an input to the existing motion-planning algorithms that do not consider intersections. Experiments in real environments show that the proposed method detected the branch roads more accurately than the model-based detection method, and the vehicle drove safely at the intersection.
      PubDate: Fri, 05 Aug 2022 05:50:01 +000
       
  • Research on Separation and Emission Reduction of Regional Airliner Based
           on Wake Encounter Response Model

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      Abstract: To ensure the safety of aircraft operation, the current regional passenger aircraft maintains a large distance from the preceding aircraft in actual operation, which result in reducing the operation efficiency of airports and airspace, and increasing pollutant emissions. To address these issues, in this paper, two aircraft types are selected in which the CRJ-900 encounters the trailing wake vortices of the A380 in front. An improved strip model is developed to build the CRJ-900 overall response wake encounter value. First, the safety of the CRJ-900 longitudinal and lateral wake encounters in different flight stages is analyzed. Second, we calculate the critical safety separation and its impact on air transport efficiency. Third, we use the LTO model to measure the reduction of aircraft fuel consumption and pollutant emissions. The results demonstrated that the medium-sized aircraft CRJ-900 has the potential to reduce the wake separation when following the super-heavy A380 aircraft. In terms of the critical safety separation calculated by the safety index, the operating efficiency of airports and airspace could be effectively improved, allowing the reduction of pollutant emissions during aircraft take-off and landing. During the takeoff, level flight, and landing phase, the results are summarized as follows: when the CRJ-900 is 13km away from the A380, the maximum lift variation is 11334N, 8157N, and 7366N; the maximum rolling moment variation is 43836N•M, 35274 N•M, and 28487 N•M; the maximum value of the rolling moment coefficient (RMC) is 0.0171, 0.0160, and 0.0130; when the RMC critical value is 0.031, the maximum safe separation for different flight stages is 11960m, which is 1040m shorter than the existing separation; when the RMC critical value is 0.05, the maximum safe separation distance of each stage is 10083m, a reduction of 2917m compared with the existing separation; when the RMC threshold is 0.07, the maximum safe separation of different flight stages is 9021m, a reduction of 3979m compared to the existing separation; when the RMC value is between 0.031-0.07, the fuel consumption can be reduced by 7.9%–12.8%, and the pollutant emission can be reduced by 9.1%–12.8%.
      PubDate: Thu, 04 Aug 2022 13:35:01 +000
       
  • ORCLSim: A System Architecture for Studying Bicyclist and Pedestrian
           Physiological Behavior through Immersive Virtual Environments

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      Abstract: Injuries and fatalities for vulnerable road users, especially bicyclists and pedestrians, are on the rise. To better inform design for vulnerable road users, we need to evaluate how bicyclist and pedestrian behavior and physiological states change in different roadway design and contextual settings. Previous research highlights the advantages of using immersive virtual environments (IVEs) in conducting bicyclist and pedestrian studies. These environments do not put participants at risk of injury, are low cost compared to on-road or naturalistic studies, and allow researchers to fully control variables of interest. In this paper, we propose a framework, Omni-Reality and Cognition Lab Simulator (ORCLSim), to support human sensing techniques within IVEs to evaluate bicyclist and pedestrian physiological and behavioral changes in different contextual settings. To showcase this framework, we present two case studies, where pilot data from five participants’ physiological and behavioral responses in an IVE setting are collected and analyzed, representing real-world roadway segments and traffic conditions. Results from these case studies indicate that physiological data are sensitive to road environment changes and real-time events in the IVE, especially changes in heart rate and gaze behavior. In addition, our preliminary data indicate participants may respond differently to various roadway settings (e.g., signalized vs. unsignalized intersections). By analyzing these changes, future studies can identify how participants’ stress level and cognitive load are impacted by the surrounding environment. The ORCLSim system architecture is a prototype that can be customized for future studies in understanding users’ behavioral and physiological responses in virtual reality settings.
      PubDate: Thu, 04 Aug 2022 07:35:01 +000
       
  • Analysis of the Impact of Ride-Hailing on Urban Road Network Traffic by
           Using Vehicle Trajectory Data

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      Abstract: The growth of ride-hailing services has made people’s daily commutes more convenient but has increased traffic on the road. However, the data needed to verify the impact of ride-hailing services on the urban road traffic network are lacking. This study matches data on the trajectories of different kinds of vehicles in Xuancheng city in the urban road network by using vehicle information data, ride-hailing information data, and license plate data recorded by the traffic bayonet system from December 26, 2018, to January 25, 2019. We used two indices, the detecting intensity and the detecting rate, to analyze the characteristics of travel based on ride-hailing services in Xuancheng. The results show that the ride-hailing vehicles have obvious travel characteristics of morning peak and evening peak, and in central urban areas and through the proposed indices of the travel time occupation rate and the travel space occupation rate to further quantitatively analyze the spatial and temporal characteristics of travel of different kinds of vehicles. Following this, we calculated the average ratios of different kinds of vehicles on congested sections of the road network and used simple regression to analyze the relationship between this and the average speed on these sections to quantitatively analyze the impact of ride-hailing on traffic congestion. The work here can provide effective decision-making support to the government for managing travel based on ride-hailing services.
      PubDate: Wed, 03 Aug 2022 06:20:00 +000
       
  • Development of Integrated Choice and Latent Variable (ICLV) Models Using
           Matrix-Based Analytic Approximation and Automatic Differentiation Methods
           on TensorFlow Platform

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      Abstract: This study further explores the multinomial probit-based integrated choice and latent variable (ICLV) models. The LDLT matrix-based analytic approximation methods, including Mendell and Elston (ME) method, bivariate ME (BME) method, and two-variate bivariate screening (TVBS) method, were adapted to calculate the multivariate cumulative normal distribution (MVNCD) function in the ICLV model because of the better performances in accuracy and computational time. Integrated with the composite marginal likelihood (CML) estimation approach, the ICLV model based on high-dimensional integration can be estimated accurately within a reasonable time. In this study, some three-alternative and four-alternative ICLV models are simulated to examine their abilities to recover model parameters. It is found that the parameter estimates and standard error estimates are acceptable for both models and the computational time is expected to decrease using tensor data structures on the TensorFlow platform. For the four-alternative ICLV models, the TVBS method has the highest level of accuracy. The BME method is also a good alternative to TVBS if computational time is of great concern. The application of the automatic differentiation (AD) technique in the model can free researchers from coding analytical gradients of log-likelihood functions and thereby greatly reduce the workload of researchers.
      PubDate: Tue, 02 Aug 2022 06:20:00 +000
       
  • Effects of Implementing Night Operation Signal Coordination on Arterials

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      Abstract: Traffic signal coordination, which connects a series of signals along an arterial by various coordination methodologies, has been proven as one of the most cost-effective means for alleviating traffic congestion. Various metropolitan planning organizations (MPO) or transportation management centers (TMC) have included signal timing updates in their strategic plans. However, in practice, signal coordination is usually implemented when traffic volume is heavy (i.e., during peak hours). For the rest of the day, the free operation strategy is usually used to reduce the waiting time of uncoordinated phases. However, this free operation strategy may result in the loss of operational efficiency on the major street. Currently, implementing signal coordination during off-peak hours is rare in the U.S. since there is lack of an efficient method that considers traffic operations for both the major and the minor streets. Therefore, this research provides a novel method that balances the control delays between the major street and the minor street. The procedure is to optimize the splits of the major street while also using the reservice strategy in the signal controller for the minor street. Microsimulation modeling was employed to assess the performance of traffic signal coordination during off-peak periods. Results show that, under reasonable splits, the coordination effect on the major street can be achieved and protected with an acceptable delay to minor street traffic. The strategy can be immediately implemented to reduce travel time for major street traffic.
      PubDate: Tue, 02 Aug 2022 06:05:01 +000
       
  • MaaS Bundling and Acceptance in the Pandemic Era: Evidence from Padua,
           Italy

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      Abstract: Given the benefits both individuals and collectivity have achieved over the past few years thanks to Mobility-as-Service (MaaS) systems, various studies were conducted to predict the level of acceptance of MaaS bundles from different territorial scales and in different countries. Results obtained are in some cases contradictory. Literature is lacking in the study of small-to-medium-sized urban contexts and in the effects of the ongoing COVID-19 pandemic. This paper aims to understand (1) what factors influence respondents’ preferences between their usual transportation means and a possible MaaS alternative and (2) what leads a user to prefer one MaaS bundle to another. A logistic regression and a mixed logit model were developed to reach the two aims, respectively. These models were calibrated using questionnaires administered to employees of the Municipality of Padua, a medium-sized city in Italy. Aspects concerning the perception of health safety in relation to the COVID-19 pandemic were included in the analyses. In 37% of the cases, users stated they would be willing to adopt at least one of the proposed MaaS bundles. The results suggest that MaaS solutions can be a useful tool for managing mobility even in medium-sized cities, provided users’ biosecurity concerns are addressed by appropriate countermeasures.
      PubDate: Tue, 02 Aug 2022 03:50:01 +000
       
  • Scheduling Synchronization for Overlapping Segments in Bus Lines: Speed
           Control and Green Extension Strategies

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      Abstract: Overlapping bus lines are ubiquitous in bus networks, particularly in metropolitan areas. The overlapping of bus lines can provide convenience for passengers who wish to transfer. However, it also tends to cause bus bunching at overlapping segment stops. Moreover, overlapping of bus lines introduces additional complexity to the operation of bus systems. This study aimed to dispatch bus vehicles entering overlapping segments dynamically by adopting speed control and green light extension strategies. This ensures that transferring passengers experience less transfer waiting time and reduced bus bunching at overlapping segments. The proposed model considers environmental constraints on vehicle speed and the stochastic factors of passenger arrivals at a stop. Synchronization is maximized by controlling the speed of vehicles along a roadway and determining whether a green light extension strategy is enabled. The effectiveness of the proposed model was verified by applying it to a real overlapping segment in Harbin, China. The results demonstrate that the proposed model can more than double the opportunity for synchronization in overlapping segments while reducing bus bunching at the stops in overlapping segments.
      PubDate: Sat, 30 Jul 2022 08:20:01 +000
       
  • Real-Time Incident-Responsive Signal Control Strategy under Partially
           Connected Vehicle Environment

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      Abstract: The performance of the traffic system can drastically drop when nonrecurrent congestion caused by incidents occurs. Early detection and clearing of traffic incidents will enable the mitigation of the congestion and early restoration of normal traffic conditions. The research in this paper utilized the vehicle information from the recent technological advancement in transportation systems, connected vehicles (CV), and loop-detector information for nonconnected vehicles (NCVs) and developed a novel algorithm to (1) control traffic signals for normal traffic conditions in the absence of incidents, (2) detect traffic incidents using CV/NCV information, and (3) control traffic signals during the occurrence and dissipation of incidents. All the 3 strategies were integrated into one algorithm, which runs as per the real-time traffic conditions, in the presence or absence of incidents. Space-mean speeds of the vehicles on nonincident lanes and throughput maximization criteria were taken as the indicators for the activation of specific signal timings directed at the incident-affected approach. Diverse incident scenarios were tested on a four-legged isolated intersection using the VISSIM simulation tool. Incident detection results showed a higher detection rate and lower mean detection time at higher CV penetration and higher traffic volumes, and at the incident locations nearer to the stop-line. The proposed incident-responsive signal control strategy at 40% and higher CV penetration showed better performance over EPICS adaptive signal control solution, in reducing average travel time delay and the average number of stops per vehicle.
      PubDate: Fri, 22 Jul 2022 07:20:01 +000
       
  • Assessing the Potential of the Strategic Formation of Urban Platoons for
           Shared Automated Vehicle Fleets

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      Abstract: This paper addresses the problem of studying the impacts of the strategic formation of platoons in automated mobility-on-demand (AMoD) systems in future cities. Forming platoons has the potential to improve traffic efficiency, resulting in reduced travel times and energy consumption. However, in the platoon formation phase, coordinating the vehicles at formation locations for forming a platoon may delay travelers. In order to assess these effects, an agent-based model has been developed to simulate an urban AMoD system in which vehicles travel between service points transporting passengers either forming or not forming platoons. A simulation study was performed on the road network of the city of The Hague, Netherlands, to assess the impact on traveling and energy usage by the strategic formation of platoons. Results show that forming platoons could save up to 9.6% of the system-wide energy consumption for the most efficient car model. However, this effect can vary significantly with the vehicle types and strategies used to form platoons. Findings suggest that, on average, forming platoons reduces the travel times for travelers even if they experience delays while waiting for a platoon to be formed. However, delays lead to longer travel times for the travelers with the platoon leaders, similar to what people experience while traveling in highly congested networks when platoon formation does not happen. Moreover, the platoon delay increases as the volume of AMoD requests decreases; in the case of an AMoD system serving only 20% of the commuter trips (by private cars in the case-study city), the average platoon delays experienced by these trips increase by 25%. We conclude that it is beneficial to form platoons to achieve energy and travel efficiency goals when the volume of AMoD requests is high.
      PubDate: Thu, 21 Jul 2022 04:05:01 +000
       
  • A Comprehensive Review on Traffic Control Modeling for Obtaining
           Sustainable Objectives in a Freeway Traffic Environment

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      Abstract: Traffic control strategy plays a significant role in obtaining sustainable objectives because it not only improves traffic mobility but also enhances traffic management systems. It has been developed and applied by the research community in recent years and still offers various challenges and issues that may require the attention of researchers and engineers. Recent technological developments toward connected and automated vehicles are beneficial for improving traffic safety and achieving sustainable goals. There is a need to develop a survey on traffic control techniques, which could provide the recent developments in the traffic control strategy and could be useful in obtaining sustainable goals. This survey presents a comprehensive investigation of traffic control techniques by carefully reviewing existing methods from a new perspective and reviews various traffic control strategies that play an important role in achieving sustainable objectives. First, we present traffic control modeling techniques that provide a robust solution to obtain reasonable traffic and sustainable mobilities. These techniques could be helpful for enhancing the traffic flow in a freeway traffic environment. Then, we discuss traffic control strategies that could be helpful for researchers and practitioners to design a robust freeway traffic controller. Second, we present a comprehensive review of recent state-of-the-art methods on the vehicle design control strategy, which is followed by the traffic control design strategy. They aim to reduce traffic emissions and energy consumption by a vehicle. Finally, we present the open research challenges and outline some recommendations which could be beneficial for obtaining sustainable goals in traffic systems and help researchers understand various technical aspects in the deployment of traffic control systems.
      PubDate: Wed, 20 Jul 2022 06:50:01 +000
       
  • A PH/PH Queuing Model in Randomly Changing Environments for Traffic
           Circulation Systems

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      Abstract: Robust optimal design of circulation systems (e.g., roads for vehicles or corridors for pedestrians) relies on an accurate steady-state traffic flow model that considers the effect of randomly changing environmental factors (e.g., daily periodicity and weather). Most analytical models assume that the customer interarrival time and service time of circulation facilities follow the exponential distribution with fixed rate parameters, which is unrealistic in most cases. In this paper, we develop a stationary PH /PH state-dependent queuing model in a randomly changing environment (RE), which is represented by a Markov chain. The model simultaneously considers the general randomness of arrival and service, the randomly varying rate parameters, and the state-dependent service (the travel time increases with the number of customers). The existing matrix analytic scheme (MAS) algorithm is extended to solve the proposed model because it avoids the explicit calculation of probability distributions. The space complexity of the algorithm is only linear in the number of RE states and is independent of the enormous (four-dimensional) state space of the Markov process. Its time complexity is a linear function of the product of the queue capacity and the number of RE states. Our model is validated versus simulation estimates. The obtained conditional performance measures can accurately capture the queue accumulation and dissipation and reveal the effect of randomly changing environments. Numerical experiments provide some interesting findings. (1) The proposed stationary model coincides with the transient M()/G// fluid queuing model under special conditions. (2) Under high traffic intensities, increasing the randomness in the duration time of the RE state leads to an obvious growth in the conditional queue length. (3) An increase in the facility length leads to an increase or a decrease in the average output rate, depending on whether the congestion dissipates effectively in one cycle. (4) A larger width is required to obtain the maximum average output rate for traffic demand with a greater nonuniformity.
      PubDate: Wed, 20 Jul 2022 06:35:00 +000
       
  • Stability Analysis of the New Traffic Flow Lattice Model considering
           Taillight Effect and Speed Deviation

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      Abstract: A new macroscopic traffic flow lattice model is established which considered the taillight effect and velocity deviation. By combining the concept of critical density, the critical condition of taillight triggering is established. The situation of taillight appearing is fully considered, and the influence of taillight effect is analyzed. Through the stability analysis of the model, the stability conditions of the model are obtained. By nonlinear analysis, the mKdV equation is derived which can describe the evolution mechanism of the density wave. From the phase diagram, we can find that the two factors have a positive impact on the stability of traffic flow. Finally, spatiotemporal evolution of the density wave and cross-section view of the density wave are obtained by numerical simulation to verify the theoretical derivation of this paper. The simulation results show that the stability of traffic flow can be improved by considering taillight effect and speed deviation. In addition, by comparing the time-space evolution maps of different parameter values, it can be found that the stability of traffic flow considering the taillight effect and speed deviation is better than that considering one factor alone. However, the stability of traffic flow will be negatively affected by low speed estimate and high critical density.
      PubDate: Wed, 20 Jul 2022 04:05:02 +000
       
  • Exploring Relationships between Months and Different Crash Types on
           Mountainous Freeways Using a Combined Modeling Approach

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      Abstract: Investigating the relationship between the months and traffic crashes is a foremost task for the safety improvement of mountainous freeways. Taking a mountainous freeway located in China as an example, this paper proposed a combined modeling framework to identify the relationships between months and different crash types. K-means and Apriori were initially used to extract the monthly distribution patterns of different types of crashes. A graphical approach and a risk calculation equation were developed to assess the output of K-means and Apriori. Then, using the assessment results as the input, a logistic regression model was constructed to quantify the effects of each month on crashes. The results indicate that the monthly distribution patterns of different crash types are inconsistent, i.e., for a specific month, the high risk of a certain crash type may be covered up if experts only focus on the total number of crashes. Moreover, when identified as high-risk months by K-means and Apriori, the crash-proneness will significantly increase several times than months identified as high-risk by only one of K-means and Apriori, thereby illustrating the superior performance of the mix-method. The conclusions can assist local relevant organizations in formulating strategies for preventing different types of traffic crashes in different months (e.g., the risk of rear-end crashes in August, the risk of fixed-object hitting crashes in February, and the risk of overturning crashes in October) and provide a methodological reference for relevant studies in other regions.
      PubDate: Tue, 19 Jul 2022 09:20:00 +000
       
  • How Do Individual Walk Lengths and Speeds, Together with Alighting Flow,
           Determine the Platform Egress Times of Train Users'

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      Abstract: Egress times of railway passengers from train alighting up to station exit typically amount to some tens of seconds, but with much variability even at the train level. Here, we first model the egress time as the ratio of the walk length to the preferred walk speed, under free-flow conditions. Then, we model the possible occurrence of congestion among the users alighting from a train as a traffic bottleneck affecting those passing at a “queue focal point” during a “queued time interval.” Analytical formulas are provided for the CDF and PDF of egress times, covering the free-flow case and the congested case. Their computation is straightforward for bivariate Gaussian length-speed walk pair. A maximum-likelihood method is developed, together with a quick estimation procedure. A case study of four contrasted trains serving an urban mass transit station in Paris is reported. One train experienced free-flow alighting conditions, whereas each of the other three had its own bottleneck. The MLE method enabled us to recover all parameters but one, due to an issue of identifiability: the solution was to take the mean walk speed as exogenous.
      PubDate: Tue, 19 Jul 2022 08:50:02 +000
       
  • Reliability and Security Analysis of Artificial Intelligence-Based
           Self-Driving Technologies in Saudi Arabia: A Case Study of Openpilot

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      Abstract: Saudi Arabia has an ambitious vision that embraces artificial intelligence (AI) technologies at a mass scale in new cities such as Neom. Self-driving has recently become one of the most important AI applications due to the advancement of sensors and AI algorithms. Given that safety is vital to the success of self-driving cars, existing infrastructures (e.g., roads and traffic signs) should be compatible with self-driving technologies. However, self-driving technologies have not been thoroughly examined in Saudi Arabia with regard to the country’s infrastructure and traffic. Therefore, this paper highlights the main areas of improvement in available self-driving technologies in Saudi Arabia. This analysis can help governments understand the current limitations of such technologies so that they can regulate them and enhance infrastructures to prepare for the mass adoption of self-driving cars. It can also help car manufacturers and developers improve self-driving algorithms to overcome their existing limitations, which will ultimately improve the safety and experience of driving.
      PubDate: Mon, 18 Jul 2022 13:35:01 +000
       
  • Impact of New Mobility Solutions on Travel Behaviour and Its Incorporation
           into Travel Demand Models

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      Abstract: Advancement in the fields of electrification, automation, and digitalisation and emerging social trends are fuelling the transformation of road transport resulting in the introduction of various innovative mobility solutions. Yet the reaction of people to many of the new solutions is still vastly unknown. This creates an unprecedented quandary for transport planners who are requested to design future transport systems and create the related investment plans without fully validated models to base the assessment upon. As some evidence on citizens’ behaviour concerning new mobility solutions starts to be progressively made available, first attempts to update the existing models begin to emerge. Nevertheless, a lot more is needed as some of the transpiring mobility solutions have not yet reached the market, making the corresponding behaviour changes imponderable. In this context, the main purpose of this paper is to provide a review on how travel behaviour changes linked to the deployment of new mobility solutions have been considered in travel demand models. The new mobility solutions studied include carsharing, dynamic ridesharing, micromobility sharing services, and personal and shared autonomous vehicles. An overview and comparison of relevant studies implementing activity or trip-based demand models and other methodologies are presented. The analysis shows that the results of the different studies heavily depend on the extent to which behavioural changes are considered. The results of the review thus point to the need for holistic demand models that carefully mimic the urban reality with everything it has to offer and account for the importance of individual traits in the decision-making processes. Such models need an in-depth understanding of the microscopic mechanisms leading to the travel behaviour shifts linked to the most innovative mobility solutions. To achieve this level of detail, mobility living labs and their real-life experiments and experience with citizens, which are flourishing in Europe, are suggested to play a crucial role in the years to come.
      PubDate: Mon, 18 Jul 2022 09:50:06 +000
       
  • Evaluating the Impact of Freeway Service Patrol on Incident Clearance
           Times: A Spatial Transferability Test

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      Abstract: Freeway service patrol (FSPs) programs have been considered as an effective tool for traffic incident management in minimizing the adverse effects of traffic incidents. In this study, random parameters hazard-based duration modeling method was used to evaluate the impact of the newly implemented Alabama Service and Assistance Patrol (ASAP) program, using incident clearance time as a performance measure. It was determined that there is a statistically significant difference in the factors that influence incidents clearance times between incidents that occurred inside and outside the ASAP regions. A total of five variables (on-road, nighttime, peak hours, rain, and fire response present) were observed to have random effects along with ten fixed effects variables on incidents occurring inside the ASAP regions. On the other hand, incidents that occurred outside the ASAP regions were found to have three random effects variables (on-road, nighttime, and fire response present) and seven fixed effects variables. The estimation results indicate a significant association of incident clearance times to incident related variables such as involvement of CMVs, fatality, vehicle towing, seat belt indicated as involved, and on-road incidents that occurred both inside and outside the ASAP regions. The results also reveal that incident clearance times are influenced strongly by temporal variables (e.g., nighttime), traffic factors (e.g., AADT), and operational variables (e.g., fire response present) for incidents both inside and outside the ASAP area models. Overall, it was observed that the incident clearance times recorded in the regions where the ASAP program is in effect are significantly different. The findings of this study are expected to be useful for the state traffic incident management (TIM) agencies in developing and executing strategies to minimize incident clearance times. Ultimately, the study provides a data-driven evidence-based assessment of the ASAP program in the state.
      PubDate: Mon, 18 Jul 2022 08:05:01 +000
       
  • Development of a Theoretical Delay Model for Heterogeneous and Less
           Lane-Disciplined Traffic Conditions

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      Abstract: In developing countries with limited or no availability of traffic sensors, theoretical delay models are the most commonly used tool to estimate control delay at intersections. The traffic conditions in such countries are characterised by a large mix of vehicle types and limited or no lane discipline (Heterogeneous, Less Lane-Disciplined (HLLD) traffic conditions), resulting in significantly different traffic dynamics. This research develops a queueing theory-based theoretical delay model that explicitly incorporates HLLD traffic conditions’ characteristic features like lack of lane discipline, violation of the First-In-First-Out rule, and a large mix of vehicle types. A new saturation flow-based Passenger Car Equivalent (PCE) estimation methodology to address heterogeneity and a virtual lane estimation approach to address lack of lane-discipline are proposed. The developed model shows 64% lesser error in average control delay estimation compared to the in-practice delay estimation models under HLLD traffic conditions. The developed model is used for signal optimisation under HLLD traffic conditions and reductions of up to 24% in control delay in comparison to the in-practice signal timing approach are observed. The study also highlights the significance of knowing the variation of delay in addition to average delay and presents a simple approach to capture the variation in delay.
      PubDate: Mon, 18 Jul 2022 05:35:00 +000
       
  • Optimization Drive on a Flat Tire Vehicular System for Autonomous
           E-Vehicles Using Network Distribution Simulations

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      Abstract: The run-on flat tire is an important technology in the area of vehicle safety technology. Nowadays, traveling by a personal vehicle from one place to another has increased due to the increase in the global economy. The main problem that is faced while traveling is tire puncture. The tire may get punctured by any sharp objects on the road such as screws and iron pins that traps the tire surface. A situation like this may be overcome by the usage of the drive on a puncher tire device which will be used to reach the destination without any need for a puncher shop. Using this device will reduce the damage of the tire and tube. This device is portable and can be placed in a vehicle itself. For this reason, a design has been developed by the CATIA 3D experience. The drive on a puncher tire device was designed using the software developed by the Dassault systems named CATIA 3D experience. Aluminum alloy was chosen as the base material to design and simulate this product. Also, the network distribution simulations were used to develop the mathematical equations to check the adequacy of the model. This device is very useful while traveling long distances if any puncher will occur. The sensors were attached to the product to receive the signal from the vehicle, so that the vehicle will run smoothly for a short distance. Drive on a puncher tire will be suitable for both two- and four-wheeler vehicles and also useful for all the areas like villages, towns, panchayats, and cities. If the tire is puncher, we cannot drive the vehicle; hence, a skating device is fixed at a tired bottom, which is used to move the vehicle. The proposal will be beneficial for a huge number of people who own two and four wheelers. This design and simulation will address the problem of the two- and four-wheeler owners traveling long distances.
      PubDate: Fri, 15 Jul 2022 11:05:01 +000
       
 
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