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: 122)
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: 16)
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   (Followers: 1)
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: 12)
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: 281)
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: 26)
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: 17)
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: 20)
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: 34)
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: 37)
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  
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 6)
Транспортні системи та технології перевезень     Open Access  

           

Similar Journals
Journal Cover
Journal of Advanced Transportation
Journal Prestige (SJR): 0.581
Citation Impact (citeScore): 1
Number of Followers: 16  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 0197-6729 - ISSN (Online) 2042-3195
Published by Hindawi Homepage  [343 journals]
  • Two-Echelon Location-Routing Problem with Time Windows and Transportation
           Resource Sharing
    • Abstract: In this work, a two-echelon location-routing problem with time windows and transportation resource sharing (2E-LRPTWTRS) is solved by selecting facility locations and optimizing two-echelon vehicle routes. The optimal solutions improve the efficiency of a logistics network based on the geographical distribution and service time windows of logistics facilities and customers. Furthermore, resource utilization is maximized by enabling resource sharing strategies within and among different logistics facilities simultaneously. The 2E-LRPTWTRS is formulated as a biobjective optimization model, and obtaining the smallest number of required delivery vehicles and the minimum total operating cost are the two objective functions. A two-stage hybrid algorithm composed of k-means clustering and extended multiobjective particle swarm optimization algorithm is proposed for 2E-LRPTWTRS optimization. A self-adaptive mechanism of flight parameters is introduced and adopted during the iterative process to balance the evolution of particles and improve the efficiency of the two-stage hybrid algorithm. Moreover, 20 small-scale instances are used for an algorithm comparison with multiobjective genetic algorithm and nondominated sorting genetic algorithm-II, and the solutions demonstrate the superiority of the proposed algorithm in optimizing logistics networks. The proposed optimization model and hybrid algorithm are tested by employing a real-world case of 2E-LRPTWTRS in Chongqing, China, and the optimization results verify the positive role of the developed model and algorithm in improving logistics efficiency, reducing operating cost, and saving transportation resources in the operations of two-echelon logistics networks.
      PubDate: Mon, 10 May 2021 09:05:01 +000
       
  • Layout Methods for Integrated Energy Supply Service Stations from the
           Perspective of Combination Optimization
    • Abstract: Integrated energy supply service stations (IES) are a new type of transportation energy infrastructure offering the advantages of comprehensive functions and intensive land use while providing more convenient and efficient energy supply services. Through the analysis of service station characteristics, this study regards the IES as a spatially superimposed combination of various energy supply services, proposes a layout method from the perspective of combination optimization, and establishes a station optimization model for energy supply stations. This method aims to further coordinate and optimize the combination of various energy supply stations to achieve global optimization of the energy supply service system. Finally, this study uses a hypothetical situation for example analysis to verify the validity and rationality of the method. The layout plan proposed in this study has important theoretical and practical significance for how to achieve the optimal layout of an IES.
      PubDate: Fri, 07 May 2021 08:05:00 +000
       
  • Examining the Bus Ridership Demand: Application of Spatio-Temporal Panel
           Models
    • Abstract: An important tool to evaluate the influence of these public transit investments on transit ridership is the application of statistical models. Drawing on stop-level boarding and alighting data for the Greater Orlando region, the current study estimates spatial panel models that accommodate for the impact of spatial and temporal observed and unobserved factors on transit ridership. Specifically, two spatial models, Spatial Error Model and Spatial Lag Model, are estimated for boarding and alighting separately by employing several exogenous variables including stop-level attributes, transportation and transit infrastructure variables, built environment and land use attributes, and sociodemographic and socioeconomic variables in the vicinity of the stop along with spatial and spatiotemporal lagged variables. The model estimation results are further augmented by a validation exercise. These models are expected to provide feedback to agencies on the benefits of public transit investments while also providing lessons to improve the investment process.
      PubDate: Fri, 07 May 2021 06:20:01 +000
       
  • Comparing Dynamic User Equilibrium and Noniterative Stochastic Route
           Choice in a Simulation-Based Dynamic Traffic Assignment Model: Practical
           Considerations for Large-Scale Networks
    • Abstract: Simulation-based dynamic traffic assignment (DTA) models play a vital role in transportation planning and operations. While the widely studied equilibrium-seeking DTA including dynamic user equilibrium (DUE) often provides robust and consistent outcomes, their expensive computational cost for large-scale network applications has been a burden in practice. The noniterative stochastic route choice (SRC) model, as a nonequilibrium seeking DTA model, provides an alternative for specific transportation operations applications that may not require equilibrium results after all (e.g., evacuation and major network disruptions) and thus tend to be computationally less expensive, yet may suffer from inconsistent outcomes. While DUE is a widely accepted approach for many strategic planning applications, SRC has been increasingly used in practice for traffic operations purposes. This paper aims to provide a comparative and quantitative analysis of the two modeling approaches. Specifically, a comparison has been made at two levels: link-level flows and network-level congestion patterns. Results suggest that adaptive driving improves the quality of the SRC solution, but its difference from DUE still remains significant at the link level. Results have practical implications for the application of large-scale simulation-based DTA models for planning and operations purposes.
      PubDate: Wed, 05 May 2021 06:50:00 +000
       
  • A Multifeatures Spatial-Temporal-Based Neural Network Model for Truck Flow
           Prediction
    • Abstract: The majority of studies on road traffic flow prediction have focused on the flow of passenger cars or the flow of traffic as a whole, which ignore the significant impact of trucks with different sizes and operational characteristics on traffic flow efficiency. Therefore, in this paper, we focus on truck traffic flow and propose a Multifeatures Spatial-Temporal-Based Neural Network model (M-BiCNNGRU) to improve its prediction. The proposed model not only comprises conventional temporal characteristics and spatial relationships but also includes a range of multifeatures. These multifeatures include policy limit, optimal time delay, road resistance, and traffic congestion state. The impacts of upstream and downstream road sections are considered on the spatial relationship by using a Convolutional Neural Network (CNN). A Bidirectional Gated Recurrent Unit (Bi-GRU) is employed to account for the temporal characteristics. To evaluate the proposed model, traffic flow data were collected from a major expressway in Beijing and the results were compared with those derived from existing models. The results show that the prediction accuracy of the BiCNNGRU model, with spatial-temporal characteristics, and the M-BiGRU model, with multifeatures and temporal, is, respectively, 4.13% and 2.15% greater than that of the Bi-GRU model, with temporal characteristics. The prediction accuracy of the proposed M-BiCNNGRU model is 92.86%, which is 7.12% greater than that of the Bi-GRU model and 13.83% greater than that of the Support Vector Regression (SVR) model. In general, therefore, the proposed M-BiCNNGRU model, which combines multifeatures, temporal characteristics, and spatial relationships, can significantly improve accuracy in predicting truck traffic flow.
      PubDate: Tue, 04 May 2021 06:20:00 +000
       
  • Deep Learning-Enabled Variational Optimization Method for Image Dehazing
           in Maritime Intelligent Transportation Systems
    • Abstract: Image dehazing has become a fundamental problem of common concern in computer vision-driven maritime intelligent transportation systems (ITS). The purpose of image dehazing is to reconstruct the latent haze-free image from its observed hazy version. It is well known that the accurate estimation of transmission map plays a vital role in image dehazing. In this work, the coarse transmission map is firstly estimated using a robust fusion-based strategy. A unified optimization framework is then proposed to estimate the refined transmission map and latent sharp image simultaneously. The resulting constrained minimization model is solved using a two-step optimization algorithm. To further enhance dehazing performance, the solutions of subproblems obtained in this optimization algorithm are equivalent to deep learning-based image denoising. Due to the powerful representation ability, the proposed method can accurately and robustly estimate the transmission map and latent sharp image. Numerous experiments on both synthetic and realistic datasets have been performed to compare our method with several state-of-the-art dehazing methods. Dehazing results have demonstrated the proposed method’s superior imaging performance in terms of both quantitative and qualitative evaluations. The enhanced imaging quality is beneficial for practical applications in maritime ITS, for example, vessel detection, recognition, and tracking.
      PubDate: Mon, 03 May 2021 05:50:02 +000
       
  • Interactive Influence Analysis of Tunnel Lateral Clearance on Driving
           Behavior Using Expressway Field Data
    • Abstract: Changes in lateral clearance are prone to drastic changes in the driving environment at the entrance and exit of the tunnel, which can cause a driver to become psychologically stressed and deviate from the center of a lane, thus creating a greater security risk. However, most of the existing regulations and studies only focus on the horizontal and vertical alignment of the tunnel entrances and exits, and there are few studies on the influence of lateral clearance on driving behavior. This study hired 15 random subjects to conduct real vehicle tests in eight tunnels on expressways with 3 design speeds by using a CAN-OBD analyzer and steering wheel angle meter. First, in five lateral clearance variation schemes, different speed characteristic indicators and steering wheel angles were selected as the indicators of driving behavior. Second, the interactive influence of the design speed, lateral clearance, operating speed, steering wheel angle, and other indicators were analyzed. Finally, paired t-test analysis and Wilcoxon and Friedman nonparametric tests were used to compare the differences in various indicators among different lateral clearance schemes. The results showed that when the left lateral clearance is 1.5 meters, the operating speed is increased by 3.9%, while the standard deviation of speed is small, and the driving performance is higher. When the right lateral clearance is 1.75 and 2.00 meters, the operating speed is not much different. However, the latter’s speed standard deviation is smaller. By contrast, when the right lateral clearance is up to 2.25 m, the operating speed increases by 3.7%. However, the speed standard deviation also increases. Different lateral clearances have little effect on the steering wheel angle. The operating speed on the right side is higher and more stable when the design speed is 100 km/h. This study provides scientific suggestions for the setting of the lateral clearance of the tunnels.
      PubDate: Mon, 03 May 2021 05:50:01 +000
       
  • Quantification of Rear-End Crash Risk and Analysis of Its Influencing
           Factors Based on a New Surrogate Safety Measure
    • Abstract: Traditional surrogate measures of safety (SMoS) cannot fully consider the crash mechanism or fail to reflect the crash probability and crash severity at the same time. In addition, driving risks are constantly changing with driver’s personal driving characteristics and environmental factors. Considering the heterogeneity of drivers, to study the impact of behavioral characteristics and environmental characteristics on the rear-end crash risk is essential to ensure driving safety. In this study, 16,905 car-following events were identified and extracted from Shanghai Naturalistic Driving Study (SH-NDS). A new SMoS, named rear-end crash risk index (RCRI), was then proposed to quantify rear-end crash risk. Based on this measure, a risk comparative analysis was conducted to investigate the impact of factors from different facets in terms of weather, temporal variables, and traffic conditions. Then, a mixed-effects linear regression model was applied to clarify the relationship between rear-end crash risk and its influencing factors. Results show that RCRI can reflect the dynamic changes of rear-end crash risk and can be applied to any car-following scenarios. The comparative analysis indicates that high traffic density, workdays, and morning peaks lead to higher risks. Moreover, results from the mixed-effects linear regression model suggest that driving characteristics, traffic density, day-of-week (workday vs. holiday), and time-of-day (peak hours vs. off-peak hours) had significant effects on driving risks. This study provides a new surrogate safety measure that can better identify rear-end crash risks in a more reliable way and can be applied to real-time crash risk prediction in driver assistance systems. In addition, the results of this study can be used to provide a theoretical basis for the formulation of traffic management strategies to improve driving safety.
      PubDate: Fri, 30 Apr 2021 06:35:01 +000
       
  • An Affinity Propagation-Based Clustering Method for the Temporal Dynamics
           Management of High-Speed Railway Passenger Demand
    • Abstract: The number of passengers in a high-speed railway line normally varies significantly by the time periods, such as the peak and nonpeak hours. A reasonable classification of railway operation time intervals is essential for an adaptive adjustment of the train schedule. However, the passenger flow intervals are usually classified manually based on experience, which is subjective and inaccurate. Based on the time samples of actual passenger demand data for 365 days, this paper proposes an affinity propagation (AP) algorithm to automatically classify the passenger flow intervals. Specifically, the AP algorithm first merges time samples into different categories together with the passenger transmit volume of the stations, which are used as descriptive variables. Furthermore, clustering validity indexes, such as Calinski–Harabasz, Hartigan, and In-Group Proportion, are employed to examine the clustering results, and reasonable passenger flow intervals are finally obtained. A case study of the Zhengzhou-Xi’an high-speed railway indicates that our proposed AP algorithm has the best performance. Moreover, based on the passenger flow interval classification results obtained using the AP algorithm, the train operation plan fits the passenger demand better. As a result, the indexes of passenger demand satisfaction rate, average train occupancy rate, and passenger flow rate are improved by 7.6%, 16.7%, and 14.1%, respectively, in 2014. In 2015, the above three indicators are improved by 5.7%, 18.4%, and 14.4%, respectively.
      PubDate: Wed, 28 Apr 2021 10:05:01 +000
       
  • Enhancing Railway Maintenance Safety Using Open-Source Computer Vision
    • Abstract: As high-speed railways continue to be constructed, more maintenance work is needed to ensure smooth operation. However, this leads to frequent accidents involving maintenance workers at the tracks. Although the number of such accidents is decreasing, there is an increase in the number of casualties. When a maintenance worker is hit by a train, it invariably results in a fatality; this is a serious social issue. To address this problem, this study utilized the tunnel monitoring system installed on trains to prevent railway accidents. This was achieved by using a system that uses image data from the tunnel monitoring system to recognize railway signs and railway tracks and detect maintenance workers on the tracks. Images of railway signs, tracks, and maintenance workers on the tracks were recorded through image data. The Computer Vision OpenCV library was utilized to extract the image data. A recognition and detection algorithm for railway signs, tracks, and maintenance workers was constructed to improve the accuracy of the developed prevention system.
      PubDate: Wed, 28 Apr 2021 06:05:01 +000
       
  • Driver Lane-Changing Behavior Prediction Based on Deep Learning
    • Abstract: A correct lane-changing plays a crucial role in traffic safety. Predicting the lane-changing behavior of a driver can improve the driving safety significantly. In this paper, a hybrid neural network prediction model based on recurrent neural network (RNN) and fully connected neural network (FC) is proposed to predict lane-changing behavior accurately and improve the prospective time of prediction. The dynamic time window is proposed to extract the lane-changing features which include driver physiological data, vehicle kinematics data, and driver kinematics data. The effectiveness of the proposed model is validated through the experiments in real traffic scenarios. Besides, the proposed model is compared with five prediction models, and the results show that the proposed prediction model can effectively predict the lane-changing behavior more accurate and earlier than the other models. The proposed model achieves the prediction accuracy of 93.5% and improves the prospective time of prediction by about 2.1 s on average.
      PubDate: Wed, 28 Apr 2021 05:20:01 +000
       
  • A Monitoring Approach Based on Fuzzy Stochastic P-Timed Petri Nets of a
           Railway Transport Network
    • Abstract: This paper proposes a monitoring approach based on stochastic fuzzy Petri nets (SFPNs) for railway transport networks. In railway transport, the time factor is a critical parameter as it includes constraints to avoid overlaps, delays, and collisions between trains. The temporal uncertainties and constraints that may arise on the railway network may degrade the planned schedules and consequently affect the availability of the transportation system. This leads to many problems in the decision and optimization of the railway transport systems. In this context, we propose a new fuzzy stochastic Petri nets for monitoring (SFPNM). The main goal of the proposed supervision approach is to allow an early detection of traffic disturbance to avoid catastrophic scenarios and preserve stability and security of the studied railway networks. Finally, to demonstrate the effectiveness and accuracy of the approach, an application to the case study of the Tunisian railway network is outlined.
      PubDate: Tue, 27 Apr 2021 09:20:01 +000
       
  • I See Your Gesture: A VR-Based Study of Bidirectional Communication
           between Pedestrians and Automated Vehicles
    • Abstract: Automated vehicles (AVs) are able to detect pedestrians reliably but still have difficulty in predicting pedestrians’ intentions from their implicit body language. This study examined the effects of using explicit hand gestures and receptive external human-machine interfaces (eHMIs) in the interaction between pedestrians and AVs. Twenty-six participants interacted with AVs in a virtual environment while wearing a head-mounted display. The participants’ movements in the virtual environment were visualized using a motion-tracking suit. The first independent variable was the participants’ opportunity to use a hand gesture to increase the probability that the AV would stop for them. The second independent variable was the AV’s response “I SEE YOU,” displayed on an eHMI when the vehicle yielded. Accordingly, one-way communication (gesture or eHMI) and two-way communication (gesture and eHMI combined) were investigated. The results showed that the participants decided to use hand gestures in 70% of the trials. Furthermore, the eHMI improved the predictability of the AV’s behavior compared to no eHMI, as inferred from self-reports and hand-use behavior. A postexperiment questionnaire indicated that two-way communication was the most preferred condition and that the eHMI alone was more preferred than the gesture alone. The results further indicate limitations of hand gestures regarding false-positive detection and confusion if the AV decides not to yield. It is concluded that bidirectional human-robot communication has considerable potential.
      PubDate: Tue, 27 Apr 2021 08:50:01 +000
       
  • Demonstration of Participation Networks in Urban Transport Policy of
           Public and Private Sectors through Social Media: The Case of Bike-Sharing
           Pricing Strategy in China
    • Abstract: Social media has become a valuable platform that enables public and private stakeholders to participate and interact in various transport policies. Using a network-based perspective and a case study of bike-sharing pricing strategies in China, this paper aims to quantitatively characterize the pattern and structure of multi-stakeholders engagement networks. Furthermore, this paper also empirically examines the confirmation bias that might exist among participants. Dataset on retweets from the Chinese Twitter-Sina Weibo is collected. Results reveal two types of important actors with unequal roles in terms of information diffusion: the “network root” and the “network bridge.” The former is mainly comprised of organizations and influential individuals who dominate message sharing, whereas the latter is comprised of the general public with various occupational backgrounds who control the efficiency and the scope of information spreading. The result also reveals a hierarchical structure in both networks and a community gathering like-minded individuals. The empirical result also demonstrates the existence of echo chambers in the transport participation network of governments and enterprises. Most echo chambers operate such that organizations or influential individuals amplify the views of the general public with more critical viewpoints. These findings of this study can assist transport stakeholders in crafting more sustainable strategies based on the understanding of uneven patterns in online public participation. Furthermore, this study sheds insights on how social media could be used to facilitate the collection of diverse people’s opinions and the evaluation of multi-stakeholder engagement for major transport issues.
      PubDate: Tue, 27 Apr 2021 08:35:00 +000
       
  • Risk Distribution Characteristics and Optimization of Short Weaving Area
           for Complex Municipal Interchanges
    • Abstract: This paper is focused on analyzing the risk distribution characteristics in short weaving areas of urban interchanges. The study was carried out on merge-diverge weaving areas with different lengths of 350 m, 450 m, and 550 m. To evaluate and identify the risk, the average speed, speed standard deviation, acceleration range, and average absolute value of acceleration were selected as indicators. Vissim simulation was applied to collect the identification indicator value of 21 typical lane sections. The results show that the risk is concentrated at the 3/4 section and exit section of the outer lane. The vehicle-operating status of the inner and middle lanes is almost unaffected. The operating speed of the outer lane is approximately 4/5 of the same position in the inner lane at 3/4 of the length of the weaving segment, while the speed standard deviation is approximately 2 times greater, and the acceleration range is approximately 2–3 times greater. Moreover, the acceleration of the average absolute value is also approximately 2–3 times greater. To balance the risk distribution, an optimization method is proposed based on the result analysis. Compared with the original design, the results show that a reasonable method of traffic organization for the complex weaving area can effectively improve the risk distribution in the weaving area and reduce the high peak of risk concentration. These results provide a basis for the optimization method and traffic organization of short weaving areas of municipal interchanges.
      PubDate: Tue, 27 Apr 2021 06:35:01 +000
       
  • A Two-Level Model for Traffic Signal Timing and Trajectories Planning of
           Multiple CAVs in a Random Environment
    • Abstract: Connected and automated vehicles (CAVs) trajectories not only provide more real-time information by vehicles to infrastructure but also can be controlled and optimized, to further save travel time and gasoline consumption. This paper proposes a two-level model for traffic signal timing and trajectories planning of multiple connected automated vehicles considering the random arrival of vehicles. The proposed method contains two levels, i.e., CAVs’ arrival time and traffic signals optimization, and multiple CAVs trajectories planning. The former optimizes CAVs’ arrival time and traffic signals in a random environment, to minimize the average vehicle’s delay. The latter designs multiple CAVs trajectories considering average gasoline consumption. The dynamic programming (DP) and the General Pseudospectral Optimal Control Software (GPOPS) are applied to solve the two-level optimization problem. Numerical simulation is conducted to compare the proposed method with a fixed-time traffic signal. Results show that the proposed method reduces both average vehicle’s delay and gasoline consumption under different traffic demand significantly. The average reduction of vehicle’s delay and gasoline consumption are 26.91% and 10.38%, respectively, for a two-phase signalized intersection. In addition, sensitivity analysis indicates that the minimum green time and free-flow speed have a noticeable effect on the average vehicle’s delay and gasoline consumption.
      PubDate: Tue, 27 Apr 2021 06:05:00 +000
       
  • Real-Time Return Demand Prediction Based on Multisource Data of One-Way
           Carsharing Systems
    • Abstract: One-way carsharing system has been widely adopted in the carsharing field due to its flexible services. However, as one of the main limitations of the one-way carsharing system, the imbalance between supply and demand needs to be solved. Predicting pick-up demand has been studied to achieve the goal, but using returned vehicles to reduce unnecessary relocation is also one of the important methods. Nowadays, trajectory data and other data are available for real-time prediction for return demand. Based on the return demand prediction, the relocation response can be more reasonable. Thus, the balance of demand and supply can be largely improved. The multisource data include trajectory data, user application log data, order data, station data, and user characteristic data. Based on these data, a return demand prediction model was used to predict whether the user will return the vehicle in 15 min in real time, and a destination station prediction model was applied to forecast which station the user will park at. Finally, a case study using ten stations’ one-week field data was conducted to test the benefit of the dynamic return demand prediction. The results showed that the return demand prediction improves the efficiency of the relocations by mitigating the condition that the station parking space is full or empty. The potential application of this study would effectively reduce unnecessary relocation and further formulate an active operation optimization strategy to reduce the system’s operational cost and improve the service quality of the system.
      PubDate: Mon, 26 Apr 2021 11:35:01 +000
       
  • Modeling Acceleration and Deceleration Rates for Two-Lane Rural Highways
           Using Global Positioning System Data
    • Abstract: Several past studies developed acceleration/deceleration rate models as a function of a single explanatory variable. Most of them were spot speed studies with speeds measured at specific locations on curves (usually midpoint of the curve) and tangents to determine acceleration and deceleration rates. Fewer studies adopted an estimated value of 0.85 m/s2 for both deceleration and acceleration rates while approaching and departing curves, respectively. In this study, instrumented vehicles with a high-end GPS (global positioning system) device were used to collect the continuous speed profile data for two-lane rural highways. The speed profiles were used to locate the speeds at the beginning and end of deceleration/acceleration on the successive road geometric elements to calculate the deceleration/acceleration rate. The influence of different geometric design variables on the acceleration/deceleration rate was analysed to develop regression models. This study also inspeced the assumption of constant operating speed on the horizontal curve. The study results indicated that mean operating speeds measured at the point of curvature (PC) or point of tangency (PT), the midpoint of curve (MC), and the end of deceleration in curve were statistically different. Acceleration/deceleration rates as a function of different geometric variables improved the accuracy of models. This was evident from model validation and comparison with existing models in the literature. The results of this study highlight the significance of using continuous speed profile data to locate the beginning and end of deceleration/acceleration and considering different geometric variables to calibrate acceleration/deceleration rate models.
      PubDate: Mon, 26 Apr 2021 06:35:00 +000
       
  • Governance in the Internet of Vehicles (IoV) Context: Examination of
           Information Privacy, Transport Anxiety, Intention, and Usage
    • Abstract: This study examines the validity and acceptability of concern for information privacy with the Internet of vehicle context. For this purpose, the exploratory and confirmatory analysis processes were performed for testing the validity of concern for the Internet of vehicle information privacy. A total number of 357 responses were received online which were complete in all respects from college and university students studying information system course at undergraduate and graduate level. The estimated results obtained from exploratory and confirmatory factor analysis revealed that 3-dimension construct containing collection, error, and information accuracy measuring governance for Internet of vehicle information privacy (CFIOVIP) was validated through second order construction with strong goodness-of-fit estimates. The relevant factors were reliable and valid as per their internal and external validity estimates of Cronbach Alpha, average variance extracted, composite reliability, discriminant validity, and factor loading values including their fitness indices for 16 items for 3-dimension construct of CFIOVIP. The findings of the study indicate that Internet of vehicle users view secondary usage of information and unauthorised access of information as the same dimension with the title of information access for measuring CFIOVIP along with two other constructs like collection and error in information for the Internet of vehicle context. The study recommends a 2nd order CFIOVIP construct based on three dimensions, namely, collection, error, and information access, for testing the present governance of the Internet of vehicles.
      PubDate: Sat, 24 Apr 2021 05:20:01 +000
       
  • Modeling and Simulation of Cascading Failures in Transportation Systems
           during Hurricane Evacuations
    • Abstract: Effective and timely evacuation is critical in alleviating the impact of hurricanes. As such, evacuation models are often sought to support the preparedness of evacuations. One important task in the modeling process is to evaluate exogenous factors that cause transportation system capacity loss during evacuation. Typical factors include direct damage to the roadway network due to storm surge and cascading impacts because of other facilities failures. For example, power outage can lead to signal failure and subway suspension. This paper aims to develop a macroscopic simulation-based approach to study the capacity loss of the roadway network in evacuation due to signal loss as a consequence of power outage. In particular, to simulate the case in which traffic signals lose power, a capacity-reduction model from signalized intersections to unsignalized (all-way stop control) intersections was developed and calibrated using microscopic model created in SUMO and Synchro. We used the downtown Manhattan as a case study area and created a hypothetical power-grid network in terms of neighborhoods. Six scenarios were built to simulate power loss of different neighborhoods. The simulation results give insights on how cascading failures of power network affect roadway network and evacuation process.
      PubDate: Fri, 23 Apr 2021 05:20:00 +000
       
  • Safety Effects of Horizontal Curve Design and Lane and Shoulder Width on
           Single Motorcycle Accidents in Norway
    • Abstract: Factors related to the road infrastructure contribute to the occurrence of motorcycle accidents. This study investigates how design parameters of the existing rural two-lane road network in Norway influence the occurrence of single motorcycle accidents. The design elements considered in this study are horizontal curvature (curve type, degree of curvature, and adjacent curve requirements) and lane and shoulder widths. A matched case-control study design was applied to investigate the safety effects of these elements. Cases were defined as segments experiencing at least one single motorcycle accident during the study period from 2013 to 2017, while controls were defined as segments not experiencing an accident in the same period. In order to identify the segments, a GIS analysis was performed on data collected from the National Road Database (NVDB). In case-control studies, matching allows us to control for confounding variables. AADT and speed limit were used as matching variables in this study. A matching ratio of 4 : 1 (i.e., four controls per case) was used, resulting in 752 controls being matched to 188 cases. The results indicate horizontal alignment to have a more significant effect on single motorcycle accidents compared to lane and shoulder widths. Segments with several adjacent reverse curves, with high curvature (R 
      PubDate: Thu, 22 Apr 2021 10:50:02 +000
       
  • Auxiliary Stopping Area Layout Method for High-Speed Maglev Operated
           Bidirectionally on Single Track
    • Abstract: Auxiliary stopping area (ASA) is the necessary emergency facility for train safety of the normal high-speed maglev. The study addresses the ASA layout problem of the high-speed maglev operated bidirectionally on single track. First, an optimization model of the ASA layout for unidirectional double-track lines considering train safety, operation efficiency, and construction cost is established, and two basic methods of the ASA layout are investigated based on the distance demand characteristic of ASAs. Then, the ASA layout problem of bidirectional single-track lines is analyzed, and an ASA two-way coordination layout algorithm (ASA-TWCLA) is proposed. Finally, a numerical experiment is carried out. The results suggest that under the premise of train safety and operation efficiency, compared with using the basic methods separately on the two directions, adopting the ASA-TWCLA algorithm can obtain a more economical ASA layout scheme for the same scenario.
      PubDate: Thu, 22 Apr 2021 10:50:01 +000
       
  • An Integrated Multicriteria Decision-Making Approach to Evaluate Traveler
           Modes’ Priority: An Application to Peshawar, Pakistan
    • Abstract: The transport planning is essential to meeting passengers’ needs for fast, safe, and reliable transport. The research goals of this study are to determine the most suitable mode of transport between predetermined alternatives according the criteria related to the transport planning. The research method combines GIS analysis, SWOT analysis, BEM method, and PROMETHEE II method in an integrated approach for decision-making. The methodology is applied to the city of Peshawar city. It includes six steps. First, a passenger questionnaire is used to establish passenger preferences when making a trip in the city. Secondly, alternative modes of urban transportation are defined. In the case of Peshawar, the following alternatives are considered: a new BRT service, BRT with five additional stops, old bus service, wagon, carpooling, and Careem/Uber. Thirdly, there is GIS analysis to investigate the stops of the BRT alternative transportation. GIS and satellite analysis have been completed for each stop. Fourthly, criteria for the assessment of urban transport modes are determined based on SWOT analysis. A total of twenty four subcriteria are proposed. Fifthly, the best-worst method (BWM) which is based on linear programming method is applied to determine the weightings that should be given to the main criteria and subcriteria. Sixthly, alternative modes of transportation are ranked by applying preference ranking organization method for enrichment evaluations’ (PROMETHEE II) method. The results show that the main important criteria greater than 5% are small movement interval: S4 (6%), security: S7 (13%), reliability: S8 (8%), accessibility:O1 (15%), possibility of special services: O2 (5%), possibility of including insurance in the travel tariff: O3 (8%), possibility of the modernization of the infrastructure: O4 (7%), and environmental pollution: T3 (5%). The implications of this study propose a BRT service with five additional stops is the best urban transport plan for Peshawar. The originality of this research consists in integration of a strategic planning technique SWOT analysis, GIS analysis, and multicriteria analysis in complete methodology to evaluate traveler’s modes priority. The methodology used in this research can be applied to evaluate different transport alternatives for transport networks worldwide.
      PubDate: Thu, 22 Apr 2021 05:50:00 +000
       
  • The Impact of the COVID-19 Movement Restrictions on the Road Traffic in
           the Czech Republic during the State of Emergency
    • Abstract: The COVID-19 pandemic crisis has impacted numerous areas of people’s work and free-time activities. This article aims to present the main impacts of the COVID-19 movement restrictions on the road traffic in the Czech Republic, measured during the first epidemic wave, i.e., from 12 March to 17 May 2020. The state of emergency was imposed by the Czech government as a de jure measure for coping with the perceived crisis, although the measure eventually resulted only in a quite liberal de facto form of stay-at-home instruction. Unique country-scale traffic data of the first six months of 2020 from 37,002 km of roads, constituting 66% of all roads in the Czech Republic, were collected and analyzed. For the prediction of the prepandemic traffic conditions and their comparison with the measured values in the period of the state of emergency, a long-term traffic speed prediction ensemble model consisting of case-based reasoning, linear regression, and fallback submodels was used. The authors found out that the COVID-19 movement restrictions had a significant impact on the country-wide traffic. Traffic density was reduced considerably in the first three weeks, and the weekly average traffic speed in all road types increased by up to 21%, expectedly due to less crowded roads. The exception was motorways, where a different trend in traffic was found. In sum, during the first three weeks of the state of emergency, people followed government regulations and restrictions and changed their travel behavior accordingly. However, following this period, the traffic gradually returned to the prepandemic state. This occurred three weeks before the state of emergency was terminated. From a behavioral perspective, this article briefly discusses the possible causes of such discrepancies between de jure and de facto pandemic measures, i.e., the governmental communication strategy related to loosening of movement restrictions, media reality, and certain culture-related traits.
      PubDate: Wed, 21 Apr 2021 16:35:00 +000
       
  • Research on Urban Traffic Active Control in Cooperative Vehicle
           Infrastructure
    • Abstract: Urban intersection control mainly undertakes two tasks: traffic safety and traffic efficiency. Traditional intersection control models and methods have been insufficient in improving traffic efficiency, which is composed of the increase in traffic demand and the complexity of demand at present. In this paper, we propose a novel model and method called ATCM, which is based on the advanced technology of cooperative vehicle infrastructure. In this paper, a novel active traffic control model (ATCM) is proposed, which is based on the advanced technology of cooperative vehicle infrastructure. ATCM increases the intersection control model variables from the traditional two dimensions to five dimensions. It reshapes intersection control from the perspective of road designers and managers, so it can achieve more flexible and efficient traffic control. To this end, a multivariable active traffic control model is constructed, which includes road speed, lane control, sequence, phase, and green light time; a D-double layer optimization method is designed for this model. The first part of this optimization method combines speed control and dynamic phase sequence control. The second part is realized by the combination of lane control and dynamic phase sequence control. By conducting comprehensive experiments, the results demonstrate that the proposed approach is more flexible and efficient than traditional methods.
      PubDate: Wed, 21 Apr 2021 07:50:00 +000
       
  • An Indoor Vehicle-in-the-Loop Simulation Platform Testing Method for
           Autonomous Emergency Braking
    • Abstract: Autonomous vehicle (AV) is expected to be the ultimate solution for traffic safety, while autonomous emergency braking (AEB), as a crucial and fundamental active safety function of AV, has excellent potential for reducing fatalities and improving road safety. Although AV has the ability to cope with harsh conditions, it is supposed to be tested fully, systematically, and rigorously before it is officially commercialized. This study developed a novel indoor AV-in-the-loop (AVIL) simulation platform based on Client-Server (C/S) architecture for real full-scale AV testing. The proposed AVIL simulation platform consists of three parts: physical hardware components, software components, and various electrical interfaces that ensure the bidirectional virtual reality (VR) interaction. To validate the functionality and performance of the platform, this paper then adopted the Udwadia–Kalaba (U-K) approach to build the AEB system based on a typical driving situation due to the explicitness and simplicity of the U-K approach. Further, a group of real road-based experiments and AVIL-based experiments were conducted. The experimental results showed that the testing data obtained from the proposed AVIL platform have a high similarity to those of the real road tests, which means that the proposed AVIL platform is capable of simulating the AV running condition when it performs linear emergency braking on the road, thus confirming the feasibility and effectiveness of the AVIL platform for AV AEB testing. Simultaneously, the testing time and repeatability of the latter performed better. The findings of this study provide a new safe, effective, and fast solution to AV testing, and the practicability of this method has been verified.
      PubDate: Tue, 20 Apr 2021 08:35:00 +000
       
  • A Timetable Optimization Model for Urban Rail Transit with Express/Local
           Mode
    • Abstract: Nowadays, an express/local mode has be studied and applied in the operation of urban rail transit, and it has been proved to be beneficial for the long-distance travel. The optimization of train patterns and timetables is vital in the application of the express/local mode. The former one has been widely discussed in the various existing works, while the study on the timetable optimization is limited. In this study, a timetable optimization model is proposed by minimizing the total passenger waiting time at platforms. Further, a genetic algorithm is used to solve the minimization problems in the model. This study uses the data collected from Guangzhou Metro Line 14 and finds that the total passenger waiting time at platforms is reduced by 9.3%. The results indicate that the proposed model can reduce the passenger waiting time and improve passenger service compared with the traditional timetable.
      PubDate: Tue, 20 Apr 2021 07:50:01 +000
       
  • A Two-Phase Gradient Projection Algorithm for Solving the Combined Modal
           Split and Traffic Assignment Problem with Nested Logit Function
    • Abstract: This study provides a gradient projection (GP) algorithm to solve the combined modal split and traffic assignment (CMSTA) problem. The nested logit (NL) model is used to consider the mode correlation under the user equilibrium (UE) route choice condition. Specifically, a two-phase GP algorithm is developed to handle the hierarchical structure of the NL model in the CMSTA problem. The Seoul transportation network in Korea is adopted to demonstrate an applicability in a large-scale multimodal transportation network. The results show that the proposed GP solution algorithm outperforms the method of the successive averages (MSA) algorithm and the classical Evan’s algorithm.
      PubDate: Mon, 19 Apr 2021 09:05:01 +000
       
  • Vehicle Routing Problem for Collaborative Multidepot Petrol Replenishment
           under Emergency Conditions
    • Abstract: In recent years, emergency events have affected urban distribution with increasing frequency. For example, the 2019 novel coronavirus has caused a considerable impact on the supply guarantee of important urban production and living materials, such as petrol and daily necessities. On this basis, this study establishes a dual-objective mixed-integer linear programming model to formulate and solve the cooperative multidepot petrol emergency distribution vehicle routing optimization problem with multicompartment vehicle sharing and time window coordination. As a method to solve the model, genetic variation of multiobjective particle swarm optimization algorithm is considered. The effectiveness of the proposed method is analyzed and verified by first using a small-scale example and then investigating a regional multidepot petrol distribution network in Chongqing, China. Cooperation between petrol depots in the distribution network, customer clustering, multicompartment vehicle sharing, time window coordination, and vehicle routing optimization under partial road blocking conditions can significantly reduce the total operation cost and shorten the total delivery time. Meanwhile, usage of distribution trucks is optimized in the distribution network, that is, usage of single- and double-compartment trucks is reduced while that of three-compartment trucks is increased. This approach provides theoretical support for relevant government departments to improve the guarantee capability of important materials in emergencies and for relevant enterprises to improve the efficiency of emergency distribution.
      PubDate: Mon, 19 Apr 2021 08:20:01 +000
       
  • The Automatic Detection of Pedestrians under the High-Density Conditions
           by Deep Learning Techniques
    • Abstract: The automatic detection and tracking of pedestrians under high-density conditions is a challenging task for both computer vision fields and pedestrian flow studies. Collecting pedestrian data is a fundamental task for the modeling and practical implementations of crowd management. Although there are many methods for detecting pedestrians, they may not be easily adopted in the high-density situations. Therefore, we utilized one emerging method based on the deep learning algorithm. Based on the top-view video data of some pedestrian flow experiments recorded by an unmanned aerial vehicle (UAV), we produce our own training datasets. We train the detection model by using Yolo v3, a very popular deep learning model among many available detection models in recent years. We find the detection results are good; e.g., the precisions, recalls, and F1 scores could be larger than 0.95 even when the pedestrian density is as high as . We think this approach could be used for the other pedestrian flow experiments or field data which have similar configurations and can also be useful for automatic crowd density estimation.
      PubDate: Mon, 19 Apr 2021 08:05:00 +000
       
 
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