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 alphabetically
Accident Analysis & Prevention     Hybrid Journal   (Followers: 128)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 8)
Applied Mobilities     Hybrid Journal   (Followers: 5)
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: 13)
Cities in the 21st Century     Open Access   (Followers: 17)
Communications in Transportation Research     Open Access  
Danish Journal of Transportation Research / Dansk Tidsskrift for Transportforskning     Open Access   (Followers: 1)
Decision Making : Applications in Management and Engineering     Open Access   (Followers: 1)
Economics of Transportation     Partially Free   (Followers: 16)
Emission Control Science and Technology     Hybrid Journal   (Followers: 1)
eTransportation     Open Access   (Followers: 1)
EURO Journal of Transportation and Logistics     Open Access   (Followers: 12)
European Journal of Transport and Infrastructure Research (EJTIR)     Open Access   (Followers: 1)
European Transport Research Review     Open Access   (Followers: 22)
Geosystem Engineering     Hybrid Journal  
IATSS Research     Open Access  
IEEE Open Journal of Intelligent Transportation Systems     Open Access   (Followers: 4)
IEEE Vehicular Technology Magazine     Full-text available via subscription   (Followers: 7)
IET Electrical Systems in Transportation     Open Access   (Followers: 13)
IET Intelligent Transport Systems     Open Access   (Followers: 11)
IET Smart Cities     Open Access  
IFAC-PapersOnLine     Open Access  
International Journal of Applied Logistics     Full-text available via subscription   (Followers: 5)
International Journal of Crashworthiness     Hybrid Journal   (Followers: 10)
International Journal of Electric and Hybrid Vehicles     Hybrid Journal   (Followers: 8)
International Journal of Heavy Vehicle Systems     Hybrid Journal   (Followers: 6)
International Journal of Intelligent Transportation Systems Research     Hybrid Journal   (Followers: 13)
International Journal of Mobile Communications     Hybrid Journal   (Followers: 8)
International Journal of Ocean Systems Management     Hybrid Journal   (Followers: 1)
International Journal of Physical Distribution & Logistics Management     Hybrid Journal   (Followers: 11)
International Journal of Services Technology and Management     Hybrid Journal   (Followers: 1)
International Journal of Sustainable Transportation     Hybrid Journal   (Followers: 18)
International Journal of Traffic and Transportation Engineering     Open Access   (Followers: 12)
International Journal of Transportation Engineering     Open Access   (Followers: 2)
International Journal of Transportation Science and Technology     Open Access   (Followers: 9)
International Journal of Vehicle Systems Modelling and Testing     Hybrid Journal   (Followers: 2)
Journal of Advanced Transportation     Hybrid Journal   (Followers: 12)
Journal of Big Data Analytics in Transportation     Hybrid Journal   (Followers: 2)
Journal of Intelligent and Connected Vehicles     Open Access   (Followers: 1)
Journal of Mechatronics, Electrical Power, and Vehicular Technology     Open Access   (Followers: 6)
Journal of Modern Transportation     Full-text available via subscription   (Followers: 7)
Journal of Navigation     Hybrid Journal   (Followers: 176)
Journal of Sport & Social Issues     Hybrid Journal   (Followers: 10)
Journal of Supply Chain Management Science (JSCMS)     Open Access   (Followers: 3)
Journal of Traffic and Transportation Engineering (English Edition)     Open Access   (Followers: 4)
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: 10)
Journal of Transport Geography     Hybrid Journal   (Followers: 22)
Journal of Transport History     Hybrid Journal   (Followers: 12)
Journal of Transportation and Logistics     Open Access   (Followers: 3)
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 9)
Journal of Transportation Security     Hybrid Journal   (Followers: 3)
Journal of Transportation Technologies     Open Access   (Followers: 13)
Journal of Waterway Port Coastal and Ocean Engineering     Full-text available via subscription   (Followers: 7)
Journal on Vehicle Routing Algorithms     Hybrid Journal  
Les Dossiers du Grihl     Open Access   (Followers: 1)
LOGI ? Scientific Journal on Transport and Logistics     Open Access  
Logistics     Open Access   (Followers: 1)
Logistics & Sustainable Transport     Open Access   (Followers: 4)
Logistique & Management     Hybrid Journal  
Maritime Transport Research     Open Access  
Mobility in History     Full-text available via subscription   (Followers: 7)
Modern Transportation     Open Access   (Followers: 11)
Nonlinear Dynamics     Hybrid Journal   (Followers: 19)
Open Journal of Safety Science and Technology     Open Access   (Followers: 16)
Open Transportation Journal     Open Access   (Followers: 1)
Packaging, Transport, Storage & Security of Radioactive Material     Hybrid Journal   (Followers: 2)
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: 11)
Promet : Traffic &Transportation     Open Access  
Public Transport     Hybrid Journal   (Followers: 18)
Recherche Transports Sécurité     Hybrid Journal   (Followers: 1)
Research in Transportation Business and Management     Partially Free   (Followers: 4)
Revista Transporte y Territorio     Open Access  
Romanian Journal of Transport Infrastructure     Open Access   (Followers: 1)
Sport, Education and Society     Hybrid Journal   (Followers: 12)
Sport, Ethics and Philosophy     Hybrid Journal   (Followers: 2)
Streetnotes     Open Access   (Followers: 2)
Synthesis Lectures on Mobile and Pervasive Computing     Full-text available via subscription   (Followers: 1)
Transactions on Transport Sciences     Open Access   (Followers: 4)
Transport     Open Access   (Followers: 16)
Transport and Telecommunication     Open Access   (Followers: 4)
Transport in Porous Media     Hybrid Journal  
Transport Problems     Open Access   (Followers: 4)
Transport Reviews: A Transnational Transdisciplinary Journal     Hybrid Journal   (Followers: 11)
Transportation     Hybrid Journal   (Followers: 32)
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: 16)
Transportation Letters : The International Journal of Transportation Research     Hybrid Journal   (Followers: 4)
Transportation Research Interdisciplinary Perspectives     Open Access   (Followers: 2)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 38)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 38)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 29)
Transportation Research Procedia     Open Access   (Followers: 6)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 29)
Transportation Safety and Environment     Open Access   (Followers: 1)
Transportation Science     Full-text available via subscription   (Followers: 26)
Transportation Systems and Technology     Open Access  
TRANSPORTES     Open Access   (Followers: 3)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 7)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 1)
Travel Behaviour and Society     Full-text available via subscription   (Followers: 9)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 2)
Urban, Planning and Transport Research     Open Access   (Followers: 33)
Vehicles     Open Access  
Vehicular Communications     Full-text available via subscription   (Followers: 4)
World Electric Vehicle Journal     Open Access   (Followers: 3)
World Review of Intermodal Transportation Research     Hybrid Journal   (Followers: 5)
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: 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]
  • Cluster Analysis of Daily Cycling Flow Profiles during COVID-19 Lockdown
           in the UK

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      Abstract: The COVID-19 pandemic and resulting government-enforced lockdown affected the travel behavior and lives of people worldwide. In this research, hierarchical cluster analysis (HCA) is used to quantify the impact on daily flow profiles of cyclists due to the public’s response to different levels of restrictions during a 6-month period of the COVID-19 pandemic in 2020. An inductive loop network in Tyne and Wear, the UK provided cycle flow data from 25 sites. A paired sample t-test was carried out between the “Pre-COVID-19” baseline year and 2020 to determine how cycling volumes changed at each site. The HCA was then performed on the diurnal hourly flow profiles to observe how they changed within the same time period. Finally, the relationship between diurnal flow profile and volume was assessed. Overall cycling volume in the study area increased by 38% during the lockdown. The highest increases were found at coastal sites, with more modest increases in suburban areas and reduced volumes at city center locations. The HCA of the diurnal flow profiles revealed that locations associated with noncommuting-shaped flows witnessed the largest increases while commuting profiles saw a decrease. As lockdown restrictions eased, flow profiles began to revert back to the prepandemic norm but never fully returned to prepandemic levels. The adoption of working from home postpandemic will change commuting behavior. The conclusions drawn from this study suggest consideration of noncommuting trips should be made when planning the design and location of future cycling schemes, and the HCA of flow profiles can assist in this decision-making process as a method to quantify changes in daily flow profiles of cycling.
      PubDate: Thu, 19 May 2022 08:20:01 +000
       
  • Thermal Straightening Control System for Variable-Section Automotive Leaf
           Springs Rolling Based on IoT Edge Computing

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      Abstract: With the rapid development of social economy in recent years, people’s living standards are also improving. The use of automobiles is becoming increasingly frequent, and people’s requirements for the safety, comfort, and energy saving of automobiles are also getting higher. This paper mainly studies the thermal straightening control system after the rolling of variable-section automotive leaf springs through edge computing based on the Internet of Things. This paper presents the basic concepts of IoT edge computing and the role they play in various aspects. The percentage of IoT development trends in 2011 was 6.7%. By 2020, the development trend percentage of IoT reached 68%, an increase of 61.3%. It can be seen that the development of the Internet of Things is very rapid. It can be seen that the straightening accuracy of the thermal straightening control system based on edge computing after the rolling of variable-section automotive leaf springs reaches 78%, and it is 29% higher than the traditional system straightening accuracy, which is only 49%. The safety of the thermal straightening control system of the variable-section automotive leaf spring after rolling based on edge computing reaches 95%, which is 33% higher than the safety of the traditional system. The thermal alignment control system for variable-section automotive leaf springs after rolling based on the edge computing of the Internet of Things is not only safer than the traditional system but also much higher in comfort and alignment accuracy than the traditional system. It can be seen that the thermal straightening control system for variable cross section automotive leaf springs after rolling based on IoT edge computing is more conducive to the development of the automotive industry.
      PubDate: Thu, 19 May 2022 07:05:00 +000
       
  • Dynamic Guidance Strategy for Pedestrian Travel in Large-Scale Activity
           under Harsh Environment

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      Abstract: Large-scale activities such as the Winter Olympics are usually held in areas with low temperature or other harsh environments, which greatly affects the spectating experience of pedestrians. In order to improve the travel efficiency and reduce the safety risk of pedestrians, an adaptive information-distribution strategy of VMS (variable message sign) for road networks is proposed to guide the pedestrians. In the proposed strategy, the dynamic feedback mechanism between the VMS information distribution and the state of crowded pedestrians is established, and the dynamic optimization model of the VMS information release layout is formulated. To evaluate the effectiveness of the strategy, a multiagent-based simulation method is proposed. Through numerical simulation, it is found that the guidance strategy can improve the movement efficiency by adjusting releasing duration of VMS information or improving the information obedience rate of pedestrians. In this paper, a large-scale competition area in the Xiaohaituo Mountain in Beijing was taken as an example to simulate the scenarios of ingress and egress with and without the strategy. The results show that the average walking time and the road congestion can be significantly reduced in the road network with the strategy, and the proportion of pedestrians with shorter travel time can be increased. Therefore, the research can provide theoretical foundation and data support for managers to guide passenger flows and improve the spectating experience.
      PubDate: Wed, 18 May 2022 10:05:00 +000
       
  • The Effect of Key Indicators on the Operation Costs for Public Toll Roads

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      Abstract: At the end of the build-operate-transfer road concession period, an optimal model for the operation of public toll roads is created based on user heterogeneity regarding the values of time for different road users. The impact of user heterogeneity on operation costs for government and private firms is subsequently analyzed on the following critical variables: user values of time, road volume/capacity ratio, and road capacity. Concerning the values of time for different road users, the mean residual and failure functions are established to describe three optimization hypotheses: maximization of social welfare with operation by the government, two extreme cases with operation by a private firm, and a Pareto-optimal solution with operation by a private firm. It is concluded that the mean residual values of the time function are a linear function of the user values of time under a Pareto-optimal operation by the government. It is also determined that private profit is related to the demand-related operational cost of the government and private firm under a Pareto-optimal operation by a private firm. These conclusions suggest relevant recommendations for the government on policymaking for the operation of public toll roads.
      PubDate: Mon, 16 May 2022 12:50:00 +000
       
  • Waiting Behavior and Arousal in Different Levels of Crowd Density: A
           Psychological Experiment with a “Tiny Box”

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      Abstract: Crowd density, defined as persons per square meter, is a basic measuring unit for describing and analyzing crowd dynamics and for planning pedestrian infrastructure. However, little is known about the relationship between crowd density and psychological stress and well-being. This study uses an experimental approach to determine whether higher crowd densities result in higher levels of stress in participants. In this experiment, which was a case study at the university, participants (N = 29) wait in a wooden box of 1 m2 for three minutes. Two, four, six, or eight participants are present simultaneously in the box. It is varied whether participants are supposed to remain silent or to speak with each other. Stress is conceptualized as arousal and measured as skin conductance level/electrodermal activity (EDA). A questionnaire is administered after the experiment, and the positioning of participants in the box is videotaped. The results show that the correlation between crowd density and physiological arousal is more complex than expected. The specific social situation in the box appears to play a more important role than merely the number of people waiting there. Furthermore, our data indicate a temporal trend: participants seem to adapt to the crowd density in the box. Video data analysis reveals that participants choose their positioning and orientation in the box carefully, but that this social choreography works less smoothly in higher densities. This study shows promising results for using EDA as a measurement of arousal in the context of crowd research. However, the limitations of this method and the experiments conducted are also discussed in detail to further improve this approach.
      PubDate: Mon, 16 May 2022 06:05:00 +000
       
  • An Occupancy-Based Adaptive Signal Control for a Congested Signalized
           Intersection in the Low CV Penetration Environment

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      Abstract: Adaptive signal control (ASC) is a well-researched topic that offers an efficient way for traffic management. It possesses a powerful ability to accommodate complex and constantly changing urban transportation networks. With the development of vehicular communication, CV-based ASC shows remarkable advantages compared with the traditional ASC system. Though the existing CV-based ASC strategies were proposed in the past few years, however, there are still issues to overcome. Most of the studies on CV-based ASC are based on the assumption of high CV penetration rate, which often result in poor performance when applied to low CV penetration environments. Besides, the lack of consideration for mixed traffic flow, which is in terms of both the vehicle types and CV penetration of different types of vehicles. To solve these issues, this paper developed an Occupancy-Based ASC strategy for a congested signalized intersection to optimize signal timing and reduce total passenger delay in the low CV penetration environment. Focused on the issues existing in the low CV penetration environment, a Maximum Likelihood Estimation (MLE) model was proposed to estimate vehicle arrivals, and two traffic models, MicroDM and MacroDM, were developed to model the mixed traffic flow and estimate passenger delay. With the purpose of offering fair treatment to passengers approaching the intersection, we proposed an Occupancy-Based Adaptive Signal Control strategy. By transforming the complex signal control problem into a mixed-integer linear programming problem, we found the optimal solution for minimizing total passenger delay. We then evaluated the proposed Occupancy-Based ASC strategy using simulation case studies. The results show that changing traffic status could be captured and estimated with the real-time CV trajectory data as input. Applying the Occupancy-Based ASC control strategy, phases with HOVs or more vehicles will be allocated more travel time. In particular, optimization results show that the proposed Occupancy-Based ASC strategy effectively balances passenger travel demands during peak volume periods.
      PubDate: Sat, 14 May 2022 17:20:03 +000
       
  • The Optimization Design of the Accurate Community Navigation Map for the
           

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      Abstract: In recent years, the development of e-commerce new retail formats is in full swing, and the terminal distribution has become a hot research topic under the background of new retail. The accuracy of the community navigation map is related to the low cost and high efficiency of terminal distribution and then affects the development of new e-commerce retail. However, in large communities, the existing navigation map software can only locate the main entrance of the community, and there is a lack of effective positioning for the location of buildings. Therefore, based on the existing navigation map, this paper expects to correct its application defects and carry out optimization design from the design principle, design idea, product function, product customization, and product application effect, so as to make the community navigation more accurate, faster, and more efficient, to help the low cost and efficient development of door-to-door distribution under the new retail of e-commerce.
      PubDate: Sat, 14 May 2022 17:05:03 +000
       
  • The Optimization of Path Planning for Express Delivery Based on Clone
           Adaptive Ant Colony Optimization

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      Abstract: In recent years, China's express delivery market has developed rapidly in the context of a booming economy. However, logistics costs are still high, which will affect the decision-making and policy making of relevant departments. Therefore, it is essential to optimize the last-mile assignment problem (LMAP) to meet the consumer’s demand for delivery time and reduce economic expenditure. The LMAP of express delivery requires multiple packages to be delivered to different destinations. Finding the path with the minimum delivery cost and time is an NP-hard problem, and it is impossible to obtain the optimal solution by enumerating all possible answers. This study proposes a new express delivery path planning method based on a clone adaptive ant colony optimization (CAACO) to find suboptimal solutions. Moreover, a new distribution cost fitness function constructed by weighing the economic expenditure and time of express delivery is designed. Specifically, a new adaptive operator and a novel clone operator are also designed to accelerate the speed of convergence. Finally, by comparing the performance of CAACO with ant colony optimization (ACO), simulated annealing (SA), and genetic algorithm (GA), the effectiveness of CAACO in solving the express LAMP is verified. In the simulation results, it is obvious that the economic expenditure and time of express delivery based on the CAACO are lower than ACO, SA, and GA, and the convergence speed is also faster than the SA and GA. It can be seen that CAACO has valuable benefits in solving LMAP.
      PubDate: Thu, 12 May 2022 17:20:02 +000
       
  • Real-Time Travel Time Prediction Based on Evolving Fuzzy Participatory
           Learning Model

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      Abstract: Urban expressways take on rapid and external transport in the city due to their fast, safe, and large capacity. Implementing intelligent and active traffic control can effectively improve the performance of urban traffic and mitigate the urban traffic congestion problem. Real-time traffic guidance is one critical way of intelligent active traffic control, and travel time is the most important input for real-time traffic guidance. We employed and improved a machine learning method called the evolving fuzzy participatory learning (ePL) model to predict the freeway travel time online in this paper. The ePL model has a promising nonlinear mapping potential, which is well suitable for the traffic prediction. We used generalized recursive least square (GRLS) to improve the estimation accuracy of the model’s parameters. This model is a fuzzy control model. Its output is the forecasting result which is also the fuzzy reasoning result. We tested this model by comparing it to other travel time prediction approaches, with the freeway data from the Caltrans Performance Measurement System. The results from the improved ePL model showed mean absolute error of 5.941 seconds, mean absolute percentage error of 1.316%, and root mean square error of 10.923 s. The performances are better than those of the baseline models including ARIMA and BPN. This model can be used to predict the travel time in the field to be used for active traffic control and traffic guidance.
      PubDate: Thu, 12 May 2022 11:50:01 +000
       
  • Truck and Unmanned Vehicle Routing Problem with Time Windows: A Satellite
           Synchronization Perspective

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      Abstract: We consider an important feature of satellite synchronization in the practical scenario of using unmanned vehicles (UVs) carried by trucks for “last-meter” delivery and introduce the truck and UV routing problem with time windows (TUVRP-TW) for optimizing the routes of a homogeneous fleet of truck-UV combinations. A UV that has been dispatched from its truck must be picked up by the same truck or must return by itself to the depot. Customers with time windows are classified into two types: truck-UV customers (TUCs) and UV customers (UCs). The TUCs where trucks dispatch or pick up the carried UVs are regarded as satellites. Fleet coordination and satellite synchronization are essential for modelling the TUVRP-TW. We classify satellite synchronization into inner-satellite synchronization and intersatellite synchronization. The inner-satellite synchronization generally considered in the literature focuses on synchronization operations at the same satellite. Intersatellite synchronization, which focuses on synchronization operations at various satellites, allows UVs to not return to the dispatched locations, if necessary. In the mixed-integer linear programming model of the TUVRP-TW, both binary variables for identifying the appointed satellites and continuous variables for time continuity constraints are introduced to ensure the interaction between truck routes and UV routes. A hybrid algorithm based on a greedy randomized adaptive search procedure (GRASP) and a variable neighborhood search (VNS) is provided. Based on generated instances and benchmark instances, computational experiments are conducted to evaluate the performance of the intersatellite synchronization, the performance of the developed formulation, and the applicability of the hybrid algorithm.
      PubDate: Thu, 12 May 2022 10:50:01 +000
       
  • Comparative Study on Characteristics of Urban Road Network in Station
           Catchment Area between China and Other Countries for Station-City
           Integration

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      Abstract: The urban road network is one of the most important factors affecting urban traffic operation in station catchment areas, as well as the main factor in station-city integration. China’s high-speed railway has developed rapidly, and station catchment areas encompassed by station-city integration have emerged as city planning and urban design aims. However, the differences in urban road network characteristics in the station catchment area between China and other countries have not been adequately researched yet. Considering 20 station catchment areas encompassed by the station-city integration as examples, this study analyzes the intersection quantity and network density in station catchment areas to compare the characteristics of urban road networks in China with those in Europe, North America, and Japan. Combined with the square block model calculation, we found the following. (1) The network density in non-China cases is concentrated in 16–22 km/km2. The Honkong West Kowloon Station and Shapingba Station approach this range, while the Shanghai Hongqiao Station and Hangzhou East Station feature considerably lower values than this range. (2) The intersection quantity in non-China cases is concentrated in 225 pcs/km2. Except for that of the Honkong West Kowloon Station, the values for the Shapingba Station, Shanghai Hongqiao Station, and Hangzhou West Station are lower than this range. (3) Developing small-scale blocks by gridding has an optimal effect on station catchment areas within the side-length range of 47.1–97.5 m. (4) The current situation of the entire urban road network and the specifications for the design codes of the road network exhibit a certain correlation with the road network characteristics of the station catchment areas.
      PubDate: Wed, 11 May 2022 10:50:02 +000
       
  • Heterogeneous Social Linked Data Integration and Sharing for Public
           Transportation

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      Abstract: Solid (social linked data) technology has made significant progress in social web applications developed, such as Facebook, Twitter, and Wikipedia. Solid is based on semantic web and RDF (Resource Description Framework) technologies. Solid platforms can provide decentralized authentication, data management, and developer support in the form of libraries and web applications. However, thus far, little research has been conducted on understanding the problems involved in sharing public transportation data through Solid technology. It is challenging to provide personalized and adaptable public transportation services for citizens because the public transportation data originate from different devices and are heterogeneous in nature. A novel approach is proposed in this study, in order to provide personalized sharing of public transportation data between different users through integrating and sharing these heterogeneous data. This approach not only integrates diverse data types into a uniform data type using the semantic web but also stores these data in a personal online data store and retrieves data through SPARQL on the Solid platform; these data are visualized on the web pages using Google Maps. To the best of our knowledge, we are the first to apply Solid in public transportation. Furthermore, we conduct performance tests of the new C2RMF (CSV to RDF Mapping File) algorithm and functional and non-functional tests to demonstrate the stability and effectiveness of the approach. Our results indicate the feasibility of the proposed approach in facilitating public transportation data integration and sharing through Solid and semantic web technologies.
      PubDate: Wed, 11 May 2022 05:35:00 +000
       
  • Energy Consumption Analysis of High-Speed Trains under Real Vehicle Test
           Conditions

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      Abstract: The study collected statistics on the actual operation of national railway electric multiple units (EMUs) and compared the energy consumption of different EMU models at different speed levels. An important method for studying the relationship between speed and energy consumption of EMUs has been constructed based on group method of data handling to reflect how the energy consumption of different EMU models changes with speed. The energy consumption of CRH2 and CRH380A EMUs on flat and sloping lines was compared. Moreover, the start-up energy consumption of CRH2 and CRH380A EMUs was compared. The effect of the number of stops of CRH2 and CRH3 EMUs on energy consumption was analyzed. Furthermore, an idea for improving the general expression and calculation methods of traction energy consumption of EMUs was proposed. Finally, suggestions on the construction of a traction energy consumption information system were provided, and the selection of different high-speed EMU models and the reasonable determination of the operating speed were discussed.
      PubDate: Wed, 11 May 2022 05:20:01 +000
       
  • Heterogeneous Driver Modeling and Corner Scenarios Sampling for Automated
           Vehicles Testing

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      Abstract: Virtual simulation-based testing of autonomous vehicles (AVs) needs massive challenging corner cases to reach high testing accuracy. Current methods achieve this goal by finding testing scenarios with low sampling frequency in the empirical distribution. However, these methods neglect modeling heterogeneous driving behavior, which actually is crucial for finding corner cases. To fill this gap, we propose an interpretable and operable method for sampling corner cases. Firstly, we initialize a testing scenario and allocate testing tasks to AV. Then, to simulate the variability in driving behaviors, we design utility functions with several hyperparameters and generate aggressive, conservative, and normal driving strategies by adjusting hyperparameters. By changing the heterogeneous driving behavior of surrounding vehicles (SVs), we can sample the challenging corner cases in the scenario. Finally, we conduct a series of simulation experiments in a typical lane-changing scenario. The simulation results reveal that by adjusting the occurrence frequency of heterogeneous SVs in the testing scenario, more corner cases can be found in limited rounds of simulations.
      PubDate: Wed, 11 May 2022 05:20:01 +000
       
  • An Improved CEEMDAN-FE-TCN Model for Highway Traffic Flow Prediction

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      Abstract: With the advent of the data-driven era, deep learning approaches have been gradually introduced to short-term traffic flow prediction, which plays a vital role in the Intelligent Transportation System (ITS). A hybrid predicting model based on deep learning is proposed in this paper, including three steps. Firstly, an improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) method is applied to decompose the nonlinear time series of highway traffic flow to obtain the intrinsic mode function (IMF). The fuzzy entropy (FE) is then calculated to recombine subsequences, highlighting traffic flow dynamics in different frequencies and improving prediction efficiency. Finally, the Temporal Convolutional Network (TCN) is adopted to predict the recombined subsequences, and the final prediction result is reconstructed. Two sensors of US101-S on the main road and on-ramp were selected to measure the prediction effect. The results show that the prediction error of the proposed model on two sensors is notably decreased on single-step and multistep prediction, compared with the original TCN model. Furthermore, the proposed improved CEEMDAN-FE-X framework can be combined with prevailing prediction methods to increase the prediction accuracy, among which the improved CEEMDAN-FE-TCN model has the best performance and strong robustness.
      PubDate: Tue, 10 May 2022 08:05:01 +000
       
  • Power Allocation Intelligent Optimization for Mobile NOMA Communication
           System

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      Abstract: Non-orthogonal multiple access (NOMA) technology can greatly improve user access and spectral efficiency. This paper considers the power allocation optimization problem of a two-user mobile NOMA communication system. Firstly, a mobile NOMA communication system model is established. Then, we analyze the outage probability (OP) of mobile NOMA communication system and the relationship between OP performance and user power allocation coefficient. Finally, the optimization objective function is established, and a power allocation optimization algorithm employing monarch butterfly optimization (MBO) is proposed. Compared with firefly algorithm and artificial fish swarm algorithm, the efficiency of MBO algorithm is increased by 20.7%, which can better improve the OP performance.
      PubDate: Tue, 10 May 2022 05:50:01 +000
       
  • Using a Machine Learning Approach to Predict the Thailand Underground
           Train’s Passenger

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      Abstract: In today’s world, data has become an asset for businesses. Many sectors use data technology to advance their businesses. Building management is one of the processes on which numerous studies have been conducted to assist building users. Thailand has progressed in terms of transportation infrastructure and public transportation. The Metropolitan Rapid Transit (MRT) system has more than one hundred million users per year. However, crowding is a concern in the present since crowding creates a problem and reduces customer pleasure. The goal of this research is to create a machine learning model for forecasting passenger demand over time. In addition, standard data collecting equipment was used to collect data from the Metropolitan Rapid Transit (MRT) Purple Line. This line has a total of 16 stations. Station name, date, day, month, period, number of passengers, holidays, weekends, and weather are among the nine factors. Analysis approaches included the analysis phase, classification, and regression algorithm. However, the regression algorithm’s accuracy is poor and therefore cannot be used. Before using machine learning classification methods, the K-means was used to cluster the types of passengers. In addition, for this investigation, three classification methods were used: artificial neural network, random forest, and decision tree. Furthermore, the findings revealed that the artificial neural network has a high predicting accuracy. The accuracy value stated is more than 0.85 for demand over time.
      PubDate: Tue, 10 May 2022 04:20:01 +000
       
  • Considering the Characteristics of Traffic Risk Factors and the Method of
           Establishing a Flexible Traffic System

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      Abstract: With the acceleration of urbanization and the development of the automobile industry, the contradiction between the traffic capacity of existing urban roads and the growing traffic demand has become increasingly acute. Traffic congestion is becoming increasingly prominent. The purpose of this article is to consider the characteristics of traffic risk factors and to study the method of establishing a flexible traffic system. It can relieve traffic congestion and provide a smooth and orderly traffic environment using intelligent transportation systems to control and direct traffic flow. Based on the large urban road network, this research uses the theory of coordinated control and learning mechanism, fuzzy control, dynamic reprogramming, and other theories to study phase sequence, balance peripheral load, and overall traffic flow. It also uses on-board sensors to optimize the collection and processing of network information, decompose traffic guidance work, select the optimal route, and autonomously guide the intelligent transportation system. Under the flexible demand scheme, the average load of the trunk road is reduced by a larger degree, which is 4% lower than that of the fixed demand scheme. At the same time, the average load of the branch has increased more, which is 4% higher than that of the fixed demand scheme. It can be seen that under the elastic demand scheme, the distribution of traffic flow in the road network is more balanced and the optimization effect of relieving traffic pressure on trunk roads and improving the utilization rate of branch roads is more significant.
      PubDate: Mon, 09 May 2022 14:50:01 +000
       
  • Analysis of the Relationship between Dockless Bicycle-Sharing and the
           Metro: Connection, Competition, and Complementation

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      Abstract: Dockless bicycle-sharing (DLBS) is one of the novel transportation modes emerging in recent years. As a newly arisen mode, dockless bicycle-sharing inevitably has influence on the existing components of the public transportation system, especially the metro system. A large number of scholars have explored the integration relationship between the two. However, through the evaluation and quantification of the dockless bicycle-sharing data and the metro automatic fare collection data, we find that the relationship between the two is not unique. Based on the location of origin and destination, the travel duration, and the travel distance, the dockless bicycle-sharing trips closely related to the metro were identified and categorized into three different temporal-spatial relationships: competition trips, connection trips, and complementation trips. Three indicators were proposed to characterize the relationship between the two systems. A case study was carried out in Shanghai, China. The proposed method was applied to investigate when, where, and to what extent the dockless bicycle-sharing trips compete with, integrate with, and complement the metro. The results show that dockless bicycle-sharing mainly integrates with and complements the metro. It is where the dockless bicycle-sharing trip takes place and the trip significantly determines its relationship with the metro. The findings provide significant implications regarding the design and management of dockless bicycle-sharing and the metro.
      PubDate: Mon, 09 May 2022 12:20:01 +000
       
  • Rebalancing Docked Bicycle Sharing System with Approximate Dynamic
           Programming and Reinforcement Learning

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      Abstract: The bicycle, an active transportation mode, has received increasing attention as an alternative in urban environments worldwide. However, effectively managing the stock levels of rental bicycles at each station is challenging as demand levels vary with time, particularly when users are allowed to return bicycles at any station. There is a need for system-wide management of bicycle stock levels by transporting available bicycles from one station to another. In this study, a bicycle rebalancing model based on a Markov decision process (MDP) is developed using a real-time dynamic programming method and reinforcement learning considering dynamic system characteristics. The pickup and return demands are stochastic and continuously changing. As a result, the proposed framework suggests the best operation option every 10 min based on the realized system variables and future demands predicted by the random forest method, minimizing the expected unmet demand. Moreover, we adopt custom prioritizing strategies to reduce the number of action candidates for the operator and the computational complexity for practicality in the MDP framework. Numerical experiments demonstrate that the proposed model outperforms existing methods, such as short-term rebalancing and static lookahead policies. Among the suggested prioritizing strategies, focusing on stations with a larger error in demand prediction was found to be the most effective. Additionally, the effects of various safety buffers were examined.
      PubDate: Mon, 09 May 2022 11:20:02 +000
       
  • Statistical Safety Performance Models considering Pavement and Roadway
           Characteristics

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      Abstract: Transportation agencies build statistical models and predict the average crash frequency to identify hazardous road sections and make informed decisions to reduce crashes. In this paper, safety performance models (SPFs) were built and evaluated considering various pavement and roadway characteristics, including pavement friction, which is seldom available for analysis. Four count data models—Poisson model, negative binomial (NB) model, hurdle-NB model (HNB), and zero-inflated NB (ZINB) model—were built based on roadway characteristics and crash data provided by the Oklahoma Department of Transportation (ODOT). Pavement friction, roadway geometry, surface condition characteristics, and traffic exposure were considered the contributing factors to traffic crashes. Established models were compared in terms of the goodness-of-fit, zero inflation, and statistical significance of factors. The HNB model exhibited promising fitting performance with a manageable number of influencing variables. Coefficients in the HNB model suggest that adequate pavement friction and the presence of shoulders can significantly reduce the crash frequency and thus improve roadway safety performance. Potential issues of the statistical models, such as unobserved heterogeneity and multicollinearity, were also discussed. The relation between roadway infrastructure characteristics (including pavement friction) and roadway safety revealed in this study could assist in choosing the proper statistical model for better decision-making and selecting appropriate preventive treatments for improved roadway safety.
      PubDate: Mon, 09 May 2022 08:20:01 +000
       
  • Design of Coupling Coil Parameters for Wireless Charging Tram Based on
           Electromagnetic Safety

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      Abstract: As a new type of urban rail transit tram, wireless charging tram uses high frequency electromagnetic field to conduct inductive power transmission, which gets rid of the traditional overhead catenary network, but inevitably causes electromagnetic radiation to the surrounding environment. Research shows that excessive electromagnetic radiation will affect the normal operation of equipment and the safety of human body. This paper analyzes the structure and coil configuration of the dynamic charging system for wireless charging tram. Aiming at the problem of electromagnetic radiation, a mathematical model with minimum electromagnetic radiation as the target and system parameters as the constraint condition is established. Finally, the system parameters of the electromagnetic coupling mechanism of the wireless charging tram are designed and optimized. The simulation and experimental results show that the method can meet the operating requirements of the system and reduce the electromagnetic radiation to the surrounding environment.
      PubDate: Mon, 09 May 2022 07:50:01 +000
       
  • Vehicle Path Recognition Approach Based on Incomplete Automatic Vehicle
           Identification

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      Abstract: Vehicle path recognition is one of the key methods used in urban traffic research, such as traffic flow characteristics analysis. Automatic vehicle identification (AVI) is often used for vehicle path recognition and is suitable for mixed traffic flow with connected automated vehicles (CAVs). However, there still remain issues in overcoming the difficulty of vehicle path identification caused by the discontinuity of AVI data and solving the problem of low precision of AVI application. To model the vehicle path, this paper selects the AVI system of Yicheng Town, Linfen City, Shanxi Province, as a test bed. The travel modes of private cars and taxis are discussed, and the quantified indicators of the model are determined. By combining the analytic hierarchy process (AHP) with the entropy weight method (EWM) to get the weights of the indicators, the path recognition model under incomplete AVI data is proposed. Finally, based on the path recognition model proposed in this paper, case studies are carried out for the private car and taxi path recognition, respectively. The validity of the path identification through practical studies and the effect of the number of missing nodes of AVI equipment on the accuracy of the model are discussed. The results show that the recognition of the travel path using the proposed model is consistent with the actual travel path. The accuracy of the proposed model is more than 60% when the number of missing nodes is less than 7 in total 31 nodes. Considering the decision models for private cars and taxis, respectively, the proposed model provides a method for vehicle path recognition based on incomplete AVI data.
      PubDate: Mon, 09 May 2022 05:35:01 +000
       
  • Resilience of Urban Road Network to Malignant Traffic Accidents

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      Abstract: Malignant traffic accidents are typical devastating events suffered by the urban road network. They cause severe functional loss when loading on the urban road network is high, exerting a significant impact on the operation of the city. The resilience of a road network refers to its ability to maintain a certain level of capacity and service when disturbed by external factors and to recover after a disturbance event, which is a crucial factor in the construction of transportation infrastructure systems. A comprehensive understanding of the adverse effects of malignant traffic accidents on the urban road network is imperative, and resilience is a concept employed to systematically explain this. This study investigates the impact of malignant traffic accidents on the resilience of the urban road network. A simulation is carried out focusing on an ideal urban road network, describing the temporal and spatial distribution of the average speed of road sections in the network. Inspired by the simulation experiment results, the ideal resilience curve is summarized, and the theory of resilience concept portrayal is innovatively developed into “6R” (redundancy, reduction, robustness, recovery, reinforcement, and rapidity). Combining the topological and “6R” resilience attributes of the urban road network, the urban road network resilience evaluation system is constructed, which yields an all-round and full-process evaluation for the urban road network with malignant traffic accidents. Results show that under malignant traffic accidents, the resilience of high-class surface roads, such as primary roads, is the poorest, suggesting that more attention and resources must be devoted to high-class surface roads. This study on the urban road network deepens the understanding and portrayal of its resilience and proposes an evaluation method to analyze its performance under disruption events.
      PubDate: Fri, 06 May 2022 05:05:00 +000
       
  • Data Imputation for Detected Traffic Volume of Freeway Using Regression of
           Multilayer Perceptron

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      Abstract: Traffic volume data are the important part of research and application of intelligent transportation systems (ITS). However, data loss often happens due to various factors in the real world, which may cause large deviations in prediction or bad accuracy of optimizations. Imputation is a valid way to handle missing values. A multilayer perceptron-multivariate imputation of chain equation (MLP-MICE) regression imputation method optimized by the limit-memory-BFGS algorithm is proposed, considering the temporal and spatial characteristics of traffic volume. Also, 32 groups of simulated imputation experiments based on the detected traffic volume of road sections in the Guangdong freeway system are conducted, which take the scenarios of continuous missing and jumped missing into account. The results of the experiments show that the MLP-MICE can optimize the imputation performance in the missing value of traffic volume with the MAPE of imputation results from 6.38% to 30%. Meanwhile, the proposed model has higher imputation accuracy for the traffic volume data with a lower degree of mutation. Lastly, the performance of the proposed model of imputation in short-term traffic volume prediction is discussed using the support vector machine. The results of it show that the MAPE of prediction under the proposed model is much lower than all-zero imputation. Therefore, the proposed model in this study is positive on improving the accuracy of traffic volume prediction and intelligent traffic control and management.
      PubDate: Thu, 05 May 2022 16:20:01 +000
       
  • Innovative Smart Road Stud Sensor Network Development for Real-Time
           Traffic Monitoring

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      Abstract: Intelligent transportation infrastructure has gained significant research attention recently. In this paper, an innovative sensor network of smart road stud (SRS) is developed to enhance traffic detection infrastructure characterized by its functionality in traffic data collection, long/short range wireless data transmission, self-sustained power supply, and remote custom controlled lighting-based traffic guidance. Compared to the traditional traffic detectors and road studs, SRS nodes are installed on lane lines instead of lane center to enable the additional applications besides the detection function, such as traffic monitoring, congestion warning, routing guidance, and so on. SRS detects vehicles based on three-axis geomagnetic sensors. A vehicle detection algorithm is proposed correspondingly under different operation scenarios to count vehicles in two adjacent lanes. Its detecting accuracy can be further improved by a sensor network of multiple SRSs working cooperatively. Field test results show that the vehicle detection accuracy based on the SRS network is about 98% per lane, which is the same level as the commercial detector installed in center of lane, even under the non-standard driving behaviors such as crossing lane line. The high performance, value-added service, and low cost enable wide-range applications of SRS networks as part of intelligent traffic detection infrastructure.
      PubDate: Thu, 05 May 2022 12:20:01 +000
       
  • Coordinated Development of Urban Intelligent Transportation Data System
           and Supply Chain Management

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      Abstract: With the development of the urban economy, the number of people using various means of transportation is also increasing, resulting in a huge workload of the traffic data system and prone to errors. Supply chain management can formulate a reasonable production plan according to the comprehensive information data generated by the supply chain management system, such as market demand analysis, purchasing demand analysis, and supplier assessment and evaluation. Therefore, this paper proposes the coordinated development of urban intelligent transportation data system and supply chain management, so as to improve the overall efficiency of the logistics system and the level of customer service. This paper aims to study the importance and advantages of the coordinated development of urban intelligent transportation data system and supply chain management. As can be seen from the data in Table 2, the percentage of people using a car increased by 18.2% in 2015, and by 2020, the percentage of people using a car increased by 36.9%. As shown in Figure 10, the traditional urban traffic data management system has the disadvantages of large amount of data and various and complex data types. Among them, the percentage of large amount of data is between 70% and 75%, and the percentage of diverse and complex data is between 62% and 68%. It can be seen that the number of people using cars is increasing, resulting in an increasing workload for the transportation system. On this basis, the intelligent traffic data system should be used to solve this problem and the coordinated development of the intelligent traffic data system and supply chain management can achieve a win-win situation.
      PubDate: Thu, 05 May 2022 10:05:01 +000
       
  • Evaluation Method of Ecological Tourism Carrying Capacity of Popular
           Scenic Spots Based on Set Pair Analysis Method

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      Abstract: By making adaptive adjustments to the tourism activities and tourism structure carried out in the tourist area, the natural resources of the scenic area can be protected while pursuing economies of scale. Moreover, it achieves a benign interaction between scenic spot development, planning, carrying capacity, and benefits, so that the scenic spot can develop sustainably under the condition of grasping the carrying capacity and restrictive conditions. This paper combines the set pair analysis method to evaluate the ecological tourism carrying capacity of scenic spots, so as to improve the quantitative effect of ecological tourism carrying capacity of scenic spots. In addition, this paper introduces the fuzzy analytic hierarchy process to determine the weight of the evaluation indicators and combines the set pair analysis method to establish a comprehensive evaluation model. The research results show that the evaluation method of ecotourism carrying capacity of popular scenic spots based on set pair analysis proposed in this paper has a good effect.
      PubDate: Thu, 05 May 2022 10:05:01 +000
       
  • Influential Factor Analysis and Prediction on Initial Metro Network
           Ridership in Xi’an, China

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      Abstract: To satisfy the adaptability of forecasting the short-term and abrupt volume of the initial metro network, we build the multiple enter linear regression (MELR) model to explore the determinants and forecast the intensity during the twice expansion of the initial metro network in Xi’an. We further compare the prediction of the metro transport capacity between the MELR models with exponential smoothing and autoregressive integrated moving average (ARIMA) models. Results show that the passenger intensity significantly fluctuates with the months and days, and MELR model is more adapted for the short-term prediction of the abrupt volume than the ARIMA model during the new metro line opening and the old line expands, which avoids the drawback of time series models that need a huge database. This study provides a guide for the prediction of initial metro network volume and accurate purchase of the rail vehicles during the metro planning and expends stages.
      PubDate: Thu, 05 May 2022 07:20:01 +000
       
  • Two Stop-Line Method for Modern T-Shape Roundabout: Evaluation of Capacity
           and Optimal Signal Cycle

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      Abstract: Uncoordinated traffic flows at the traditional roundabouts, especially with a small circumference and fewer lanes, are often heavily affected by congestion, which escalates fuel consumption, CO2 emissions, idling, and travel delay. An intriguing way to mitigate such uncoordinated flows at junctions would be facilitated through optimal traffic signalization. For this purpose, this paper presents a novel holistic Three-Leg Signalized Roundabout (TLSR) model based on two signalized stop lines (2SL). The first stop line is placed at each entry curve of a roundabout with effectual lane markings as usual. Hereafter, the second stop line is set exclusively in the circulatory roadway to improve left-turning mobility with an additional “short-lane model” to deal with heavy traffic, following specific patterns for smooth vehicle merging. The capacity and optimal signal cycle relationships are derived to evaluate the performance of the proposed TLSR-2SL, considering the internal space constraints of the roundabout. Under the various scenarios, the parameters’ sensitivity tests demonstrate that signal cycle and central radius play a significant role in enhancing the roundabout’s operational performance. From the executed simulation, the proposed framework improves the traffic flow by 15% and controls the relative error within 10% compared to benchmark methods.
      PubDate: Wed, 04 May 2022 13:05:00 +000
       
 
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