Subjects -> TRANSPORTATION (Total: 212 journals)
    - AIR TRANSPORT (9 journals)
    - AUTOMOBILES (26 journals)
    - RAILROADS (10 journals)
    - ROADS AND TRAFFIC (9 journals)
    - SHIPS AND SHIPPING (39 journals)
    - TRANSPORTATION (119 journals)

TRANSPORTATION (119 journals)                     

Showing 1 - 53 of 53 Journals sorted alphabetically
Accident Analysis & Prevention     Hybrid Journal   (Followers: 117)
Analytic Methods in Accident Research     Hybrid Journal   (Followers: 8)
Applied Mobilities     Hybrid Journal   (Followers: 2)
Archives of Transport     Open Access   (Followers: 18)
Asian Transport Studies     Open Access  
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: 15)
Danish Journal of Transportation Research / Dansk Tidsskrift for Transportforskning     Open Access   (Followers: 2)
Decision Making : Applications in Management and Engineering     Open Access   (Followers: 1)
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     Hybrid Journal   (Followers: 11)
IET Intelligent Transport Systems     Hybrid Journal   (Followers: 11)
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: 5)
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: 14)
International Journal of Mobile Communications     Hybrid Journal   (Followers: 9)
International Journal of Ocean Systems Management     Hybrid Journal   (Followers: 3)
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: 18)
International Journal of Transportation Engineering     Open Access   (Followers: 1)
International Journal of Transportation Science and Technology     Open Access   (Followers: 11)
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: 1)
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: 279)
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: 10)
Journal of Transport and Land Use     Open Access   (Followers: 25)
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: 12)
Journal of Transportation and Logistics     Open Access   (Followers: 4)
Journal of Transportation Safety & Security     Hybrid Journal   (Followers: 11)
Journal of Transportation Security     Hybrid Journal   (Followers: 3)
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: 19)
Open Journal of Safety Science and Technology     Open Access   (Followers: 17)
Open Transportation Journal     Open Access  
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: 6)
Transport     Open Access   (Followers: 17)
Transport and Telecommunication     Open Access   (Followers: 5)
Transport in Porous Media     Hybrid Journal   (Followers: 1)
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: 33)
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: 6)
Transportation Research Interdisciplinary Perspectives     Open Access   (Followers: 3)
Transportation Research Part A: Policy and Practice     Hybrid Journal   (Followers: 41)
Transportation Research Part B: Methodological     Hybrid Journal   (Followers: 39)
Transportation Research Part C: Emerging Technologies     Hybrid Journal   (Followers: 31)
Transportation Research Procedia     Open Access   (Followers: 7)
Transportation Research Record : Journal of the Transportation Research Board     Full-text available via subscription   (Followers: 36)
Transportation Safety and Environment     Open Access   (Followers: 2)
Transportation Science     Full-text available via subscription   (Followers: 25)
Transportation Systems and Technology     Open Access  
TRANSPORTES     Open Access   (Followers: 6)
Transportmetrica A : Transport Science     Hybrid Journal   (Followers: 8)
Transportmetrica B : Transport Dynamics     Hybrid Journal   (Followers: 1)
Transportrecht     Hybrid Journal   (Followers: 1)
Travel Behaviour and Society     Full-text available via subscription   (Followers: 11)
Travel Medicine and Infectious Disease     Hybrid Journal   (Followers: 4)
Urban Development Issues     Open Access   (Followers: 3)
Urban, Planning and Transport Research     Open Access   (Followers: 32)
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]
  • Profit Maximization Model with Fare Structures and Subsidy Constraints for
           Urban Rail Transit
    • Abstract: This paper analyzes government subsidies based on the service design (i.e., headway) and fare structures of an urban rail transit system while considering necessary financial support from the government. To capture the interactions among the operator performance, government subsidies, and passengers in an urban rail transit system, a profit maximization model with nonnegative profit constraint is formulated to determine the optimal fare and headway solutions. Then, the social welfare that results from the operator profit maximization model is analyzed. Finally, a numerical example from Changsha, China, is employed to verify the feasibility of the proposed model. The major results consist of optimized solutions for decision variables, i.e., the fares and train headways, as well as subsidies to the operator. The fare elasticity factor under two fare structures significantly affects fares and demand. As the fare elasticity factor increases, the social welfare gradually decreases and a deficit occurs at low fares and demand, while subsidies rise from 0 to ¥24658.00 and ¥38089.16 under the flat fare and distance-based fare structures.
      PubDate: Mon, 25 Jan 2021 16:50:01 +000
  • Vehicle Assignment considering Battery Endurance for Electric Vehicle
           Carsharing Systems
    • Abstract: On-demand station-based one-way carsharing is widely adopted for battery electric vehicle sharing systems, which is regarded as a supplement of urban mobility and a promising approach to the utilization of green energy vehicles. The service model of these carsharing systems allows users to select vehicles based on their own judgment on vehicle battery endurance, while users tend to pick up vehicles with the longest endurance distances. This phenomenon makes instant-access systems lose efficiency on matching available vehicles with diverse user requests and limits carsharing systems for higher capacity. We proposed a vehicle assignment method to allocate vehicles to users that maximize the utility of battery, which requires the system to enable short-term reservation rather than instant access. The methodology is developed from an agent-based discrete event simulation framework with a first-come-first-serve logic module for instant access mode and a resource matching optimization module for short-term reservation mode. Results show that the short-term reservation mode can at most serve 20% more users and create 47% more revenue than instant access mode under the scenario of this research. This paper also points out the equilibrium between satisfying more users by efficiently allocating vehicles and distracting users by disabling instant access and suggests that the reservation time could be 15 minutes.
      PubDate: Mon, 25 Jan 2021 14:20:00 +000
  • Research on Optimization Model of Logistics Transportation Truck Path
           considering Environmental Impact: Experimental Data from Xiqing District,
    • Abstract: In recent years, the prohibition of trucks which could cause environmental pollution on urban roads has become widespread in China. However, some truck restriction policies might lead to a reduction in logistics transportation efficiency. With the help of big data, technology companies have developed many truck applications, such as HCB, truck home, and truck help, to provide the drivers available traffic information. In this context, this paper put forward a truck path optimization model considering environmental impact (TPOM-EI), which is solved by a heuristic algorithm—ant colony optimization (ACO) algorithm. Most previous studies focused on unilateral benefits rather than overall benefits; this paper aims to propose a path optimization model based on real-time minimization of social and transportation costs. Finally, data of Xiqing Economic and Technological Development Zone in Tianjin city (XQ-EDZ) have been used to demonstrate the applicability of the proposed algorithm. The results show that logistics truck path has a huge impact on social costs, and real-time activities in various areas will also change the path of a truck. This research will also help logistics truck drivers to choose the best route in real time.
      PubDate: Wed, 20 Jan 2021 07:20:01 +000
  • A Data-Driven Scalable Method for Profiling and Dynamic Analysis of Shared
           Mobility Solutions
    • Abstract: The advent of Internet of Things will revolutionise the sharing mobility by enabling high connectivity between passengers and means of transport. This generates enormous quantity of data which can reveal valuable knowledge and help understand complex travel behaviour. At the same time, it challenges analytics platforms to discover knowledge from data in motion (i.e., the analytics occur in real time as the event happens), extract travel habits, and provide reliable and faster sharing mobility services in dynamic contexts. In this paper, a scalable method for dynamic profiling is introduced, which allows the extraction of users’ travel behaviour and valuable knowledge about visited locations, using only geolocation data collected from mobile devices. The methodology makes use of a compact representation of time-evolving graphs that can be used to analyse complex data in motion. In particular, we demonstrate that using a combination of state-of-the-art technologies from data science domain coupled with methodologies from the transportation domain, it is possible to implement, with the minimum of resources, the next generation of autonomous sharing mobility services (i.e., long-term and on-demand parking sharing and combinations of car sharing and ride sharing) and extract from raw data, without any user input and in near real time, valuable knowledge (i.e., location labelling and activity classification).
      PubDate: Tue, 19 Jan 2021 15:20:01 +000
  • Digital Twins and Road Construction Using Secondary Raw Materials
    • Abstract: Secondary raw materials (SRMs) tend to be a valuable replacement for finite virgin materials especially since construction works (i.e., building and civil engineering work such as road construction) require vast quantities of raw materials. Using SRM originating from recycling a broad range of inorganic waste materials (e.g., mining waste, different industrial wastes, construction, and demolition waste) has been recognized as a promising, generally more cost-efficient, and environmentally friendly alternative to the exploitation of natural resources. Despite the benefits of using SRM, several challenges need to be addressed before using SRM even more. One of them is the long-term durability and little-known response of construction works built using such alternative materials. In this paper, we present the activities to establish a fully functioning digital twin (DT) of a road constructed using SRM. The first part of the paper is devoted to the theoretical justification of efforts and ways of establishing the monitoring systems, followed by a DT case study where an integrated data environment synthesizing a Building Information Model and monitored data is presented. Although the paper builds upon a small scale, the case study is methodologically designed to allow parallels to be drawn with much larger construction projects.
      PubDate: Tue, 19 Jan 2021 15:20:01 +000
  • Parking Demand vs Supply: An Optimization-Based Approach at a University
    • Abstract: Parking management has always been a major concern for universities and other activity centers. Nowadays, many universities are suffering from a lack of campus parking capacity. To tackle this problem, it is necessary to take parking lots assignment into consideration, regarding intercampus users’ needs. These users have different ages, physical characteristics, expectations, and administrative positions that should be considered before any parking assignment. Here, a new method is proposed to optimize parking lots management for those universities where staff (academic and administrative), in contrast to students, are allowed to park inside the campus area. For this purpose, first, the probability of using a specific parking lot by each group is determined. For staff, this is done based on their choices, revealed by the relative frequency of using parking lots. This probability for students can be calculated using a fuzzy inference system model. To develop the model, a survey is conducted to extract students’ preferences, regarding parking spaces assignment inside the campus area. Afterward, an integer linear programming model with the objective function of maximizing parking probability is employed, considering several related constraints. The proposed model is applied to Shahid Bahonar University of Kerman (SBUK), Iran, as the case study. According to the results, it can be concluded that the proposed method can help to reduce wandering time of finding an appropriate parking space for both staff and students. In addition, the proposed application can help increase the satisfaction level of staff and students with regard to parking management.
      PubDate: Tue, 19 Jan 2021 14:05:01 +000
  • Determining the Operator for the Public Toll Road
    • Abstract: After the BOT road operation contract expires, generally, the road will be transferred to the government, and then the government operates the road independently without charging costs from its users. Facing the huge amount of the operation cost, Chinese government tends to continue to charge the road users to guarantee the high quality of road operation. Then, the government will have to decide whether a private firm or government itself would be suitable to operate the road. A model is presented for decision-making through balancing interests between the government and the private firm with an introduction of an intermediate variable, i.e., bidding price. Three scenarios are investigated in the model, including the optimization of government operation, the optimization of private firm operation, and government operation with an improper decision of the intermediate variable. Improper intermediate variable will result in a higher toll charged by the government than by a private firm. The method of avoiding an improper decision is investigated. The result shows that the intermediate variable should be determined to be the government operation cost, based on which the private operator could be chosen, if available. With consideration of the private operator’s profit to be guaranteed by the government, the maximum subsidy should be equal to the minimum private operator’s profit to be disclosed when the contract is signed.
      PubDate: Mon, 18 Jan 2021 17:35:02 +000
  • Implications of a Narrow Automated Vehicle-Exclusive Lane on Interstate 15
           Express Lanes
    • Abstract: The main objective of this study is to evaluate the safety and operational impacts of an innovative infrastructure solution for safe and efficient integration of Automated Vehicle (AV) as an emerging technology into an existing transportation system. Filling the gap in the limited research on the effect of AV technology on infrastructure standards, this study investigates implications of adding a narrow reversible AV-exclusive lane to the existing configuration of I-15 expressway in San Diego, resulting in a 9 ft AV reversible lane and, in both directions, two 12-feet lanes for HOV and FasTrak vehicles. Given the difference between the operation of AVs and human-driven vehicles and reliance of AVs on sensors as opposed to human capabilities, the question is should we provide narrower AV-exclusive roadways assuming AVs are more precise in lateral and longitudinal lane keeping behaviour' To accomplish the goal of the project, a historical crash data analysis and a traffic simulation analysis were conducted. Crash data analysis revealed that unsafe speed, improper turning, and unsafe lane change are the most recurring primary collision factors on I-15 ELs. AVs’ automated longitudinal and lateral control systems could potentially reduce these types of collisions on an AV-exclusive lane with proper infrastructure features for AV sensor operation (e.g., distinct lane marking). Microsimulation findings indicated an AV-exclusive lane may increase traffic flow and density by up to 14% and 24%, respectively. It also showed that average speed is reduced. However, this could lead to the speed differential increase between the exclusive lane and adjacent lane requiring careful consideration if additional treatments or barriers are needed. The results of this study contribute to infrastructure adaptation to AV technology and future AV-exclusive lanes implementations.
      PubDate: Mon, 18 Jan 2021 11:50:00 +000
  • Dynamic Spatiotemporal Causality Analysis for Network Traffic Flow Based
           on Transfer Entropy and Sliding Window Approach
    • Abstract: With the rapid development of sensor and communication technologies, a large amount of spatiotemporal traffic data has been accumulated, presenting the characteristics of big data. The potential information and regularity of traffic state evolution can be extracted from the huge traffic flow time series data and applied to intelligent transportation systems. This study proposes a dynamic spatiotemporal causality modeling approach to analyze traffic causal relationships for the large-scale road network. Transfer entropy algorithm is utilized to detect the spatiotemporal causality of network traffic states based on the extensive traffic time series data, which could measure the amount and direction of information transmission. A combination of Gaussian kernel density estimation and sliding window approach is proposed to calculate the transfer entropy and construct dynamic spatiotemporal causality graphs based on the causality significance test. The indexes of affected coefficient, influence coefficient, input degree, and output degree are defined to evaluate the causal interaction of traffic states among different road segments and identify the critical roads and potential bottlenecks of the existing road network. Experimental results based on real-world traffic sensor data indicate that the structures of traffic causality graphs are time-varying; the traffic cause-effect interaction among different road segments during the peak time is more significant than that during the nonpeak time; and the critical road segments can be identified, which are mainly located at the intersections of arterial roads, undertaking the convergence and dispersion of large traffic flows.
      PubDate: Mon, 18 Jan 2021 10:35:00 +000
  • Multiobjective Optimization of Cable Forces and Counterweights for
           Universal Cable-Stayed Bridges
    • Abstract: In cable-stayed bridges, especially asymmetric bridges, counterweights are always made to work together with cable pretension forces to get a reasonable finished state. To solve the optimization problem of the cable-stayed bridge considering the counterweights, the integrated optimization method (IOM) for estimating cable forces and counterweights is proposed. In this method, the counterweights are proposed to act on the anchor points. After that, the summary of the minimum weighted total bending energy and the summary of the counterweights are considered as two objective functions of a multiobjective problem. Finally, the dynamic weighted coefficient method is used to solve this problem and realize the Pareto solution set. IOM presents detailed procedures in a simple numerical model and is then applied to the Yong-ding special-shaped cable-stayed bridge. The results show that not only IOM can realize the priority selection of the loading position of the counterweights but also get a better reasonable finish state because of the introduction of the counterweight dimension; the dynamic weighted coefficient method can quickly find the Pareto optimal solution set and be further screened by decision-makers; counterweight is very helpful to reduce torsion and other spatial effects in cable-stayed bridges. IOM can be used as a universal optimization method for cable-stayed bridges.
      PubDate: Fri, 15 Jan 2021 13:50:01 +000
  • A Decision-Making Method for Ship Collision Avoidance Based on Improved
           Cultural Particle Swarm
    • Abstract: In the process of ship collision avoidance decision making, steering collision avoidance is the most frequently adopted collision avoidance method. In order to obtain an effective and reasonable steering angle, this paper proposes a decision-making method for ship collision avoidance based on improved cultural particle swarm. Firstly, the ship steering angle direction is to be determined. In this stage, the Kalman filter is used to predict the ship’s trajectory. According to the prediction parameters, the collision risk index of the ship is calculated and the situation with the most dangerous ship is judged. Then, the steering angle direction of the ship is determined by considering the Convention on the International Regulations for Preventing Collisions at Sea (COLREGs). Secondly, the ship steering angle is to be calculated. In this stage, the cultural particle swarm optimization algorithm is improved by introducing the index of population premature convergence degree to adaptively adjust the inertia weight of the cultural particle swarm so as to avoid the algorithm falling into premature convergence state. The improved cultural particle swarm optimization algorithm is used to find the optimal steering angle within the range of the steering angle direction. Compared with other evolutionary algorithms, the improved cultural particle swarm optimization algorithm has better global convergence. The convergence speed and stability are also significantly improved. Thirdly, the ship steering angle direction decision method in the first stage and the ship steering angle decision method in the second stage are integrated into the electronic chart platform to verify the effectiveness of the decision-making method of ship collision avoidance presented in this paper. Results show that the proposed approach can automatically realize collision avoidance from all other ships and it has an important practical application value.
      PubDate: Fri, 15 Jan 2021 13:35:00 +000
  • Traffic Flow Characteristics and Lane Use Strategies for Connected and
           Automated Vehicles in Mixed Traffic Conditions
    • Abstract: Managed lanes, such as a dedicated lane for connected and automated vehicles (CAVs), can provide not only technological accommodation but also desired market incentives for road users to adopt CAVs in the near future. In this paper, we investigate traffic flow characteristics with two configurations of the managed lane across different market penetration rates and quantify the benefits from the perspectives of lane-level headway distribution, fuel consumption, communication density, and overall network performance. The results highlight the benefits of implementing managed lane strategies for CAVs: (1) A dedicated CAV lane significantly extends the stable region of the speed-flow diagram and yields a greater road capacity. As the result shows, the highest flow rate is 3400 vehicles per hour per lane at 90% market penetration rate with one CAV lane. (2) The concentration of CAVs in one lane results in a narrower headway distribution (with smaller standard deviation) even with partial market penetration. (3) A dedicated CAV lane is also able to eliminate duel-bell-shape distribution that is caused by the heterogeneous traffic flow. (4) A dedicated CAV lane creates a more consistent CAV density, which facilitates communication activity and decreases the probability of packet dropping.
      PubDate: Wed, 13 Jan 2021 13:50:01 +000
  • Drivers’ Yielding Behavior in Different Pedestrian Crossing
           Configurations: A Field Survey
    • Abstract: Although in recent years road victims have been reported to decrease, the growing number of pedestrians involved in road accidents still remains a social concern. This work analyzes the drivers’ behavior in approach to two different configurations of pedestrian zebra crossing: marked by (1) white stripes over the pavement (named “white zebra crossing”) and (2) white stripes on a red-colored pavement (named “red and white zebra crossing”). Even though the latter configuration is nowadays quite widespread on urban environment, there is no scientific evidence of its actual effectiveness in conditioning drivers’ yielding behavior. This study was aimed at verifying the effectiveness of the red and white zebra crossing on improving road safety at pedestrian crossings. A set of synchronized cameras were used to record drivers’ behavior while approaching the pedestrian crossings. By reconstructing the speed profile of each surveyed driver (309 in total), it was possible to analyze the driver-pedestrian interaction. Data were used to study the driver yielding behavior, to analyze how it is affected by vehicle dynamic constraints, and to identify the significant explanatory variables of a logistic regression model for predicting the drivers’ likelihood of yielding the pedestrian on the different crossing configurations. As a result, significant differences in terms of yielding behavior on the two pedestrian crossing configurations were observed: a higher yielding rate (about 20% higher) and a higher tendency to yield to the pedestrian were reported for the red and white zebra crossing, especially for the most critical conditions of driver-pedestrian interaction. Moreover, the analysis of yielding behavior with respect to vehicle dynamics constraints highlighted that drivers approaching the red and white zebra crossing experienced more opportunities to yield. As a confirmation, logistic regression model showed that the yielding likelihood is significantly and positively affected by the presence of the red and white zebra crossing configuration.
      PubDate: Tue, 12 Jan 2021 07:20:01 +000
  • Joint Impact of Rain and Incidents on Traffic Stream Speeds
    • Abstract: Unpredictable and heterogeneous weather conditions and road incidents are common factors that impact highway traffic speeds. A better understanding of the interplay of different factors that affect roadway traffic speeds is essential for policymakers to mitigate congestion and improve road safety. This study investigates the effect of precipitation and incidents on the speed of traffic in the eastbound direction of I-64 in Virginia. To the best of our knowledge, this is the first study that studies the relationship between precipitation and incidents as factors that would have a combined effect on traffic stream speeds. Furthermore, using a mixture model of two linear regressions, we were able to model the two different regimes that the traffic speed could be classified into, namely, free-flow and congested. Using INRIX traffic data from 2013 through 2016 along a 25.6-mi section of Interstate 64 in Virginia, results show that the reduction of traffic speed only due to incidents ranges from 41% to 75% if the road is already congested. In this case, precipitation was found to be statistically insignificant. However, regardless of the incident impact, the effect of light rain in free-flow conditions ranges from insignificant to a 4% speed reduction while the effect of heavy rain ranges from a 0.6% to a 6.5% speed reduction when the incident severity is low but has a roughly double effect when the incident severity is high.
      PubDate: Mon, 11 Jan 2021 15:20:01 +000
  • Cooperative Hypercube Queuing Model for Emergency Service Systems
    • Abstract: As a useful descriptive tool for emergency service effectiveness, the hypercube queuing model has been applied in systems of many countries, such as the SAMU system in Brazil. However, the traditional hypercube queuing model and its extended forms assume that the service provider performs independent services, lacking a compelling description of the situation where emergency vehicles perform cooperative services (e.g., NEPPHE in China). To this end, we assume that vehicles in the same fleet simultaneously start and end services and propose a cooperative hypercube queuing (CHQ) model that can describe the state of emergency systems which apply multivehicle dispatches. In order to verify the accuracy of the model, we apply Arena simulation software in Wuhan case. The results show that the CHQ model can illustrate cooperative performance effectively. Sensitivity analyses under more general parameters are conducted to reveal insights into the model application.
      PubDate: Fri, 08 Jan 2021 15:20:01 +000
  • A Collaborative Reservation Mechanism of Multiple Parking Lots Based on
           Dynamic Vehicle Path Planning
    • Abstract: With the development of wireless communication and artificial intelligence technology, online parking reservation system can effectively save drivers’ searching time for vacant spaces. However, in the environment with multiple candidate parking lots around the destination, how to coordinate and maximize parking space resources to reduce the travel time is still a practical issue for urban drivers. In order to solve this problem, a collaborative reservation mechanism based on dynamic vehicle path planning is proposed in this paper. By the aid of the dedicated backbone network with a clear division of work responsibilities, the information of traffic and parking lots is collected in real time, based on which the travel time prediction and empty spaces evaluation are executed separately, and then the optimal decision of path planning and parking lot selection can be made and adjusted dynamically by a step-by-step acknowledgement mechanism. The simulation results show that, based on collaborative working and overall planning, our proposed reservation mechanism can effectively raise the utilization rate of the parking lots resources and significantly reduce the travel time for drivers under different traffic environments. Compared to current mechanisms, the collaborative parking reservation mechanism reveals higher feasibility and applicability. It can assist in design and operation of urban traffic management and space resource utilization.
      PubDate: Fri, 08 Jan 2021 15:05:00 +000
  • Conditions for Setting Exclusive Pedestrian Phases at Two-Phase Signalized
           Intersections considering Pedestrian-Vehicle Interaction
    • Abstract: In order to analyze the effectiveness of setting exclusive pedestrian phase (EPP) under different vehicle yielding rates, the effect of EPPs on traffic efficiency is studied and a setting condition of EPP considering pedestrian-vehicle interaction is proposed in this paper. First, the main factors influencing the behavior of vehicles and pedestrians during pedestrian-vehicle interaction are analyzed, and a pedestrian-vehicle interaction (PVI) model at the crosswalk of urban road is established. Second, assuming that vehicle arrival obeys the Poisson distribution, the delay models of vehicle passengers and pedestrians crossing the street at the intersection are established, and taking the total delay of traffic participants as the main index, the setting condition of EPP are proposed. Third, based on the video of pedestrian-vehicle interaction at crosswalks, the parameters of the proposed model are calibrated. Through sensitivity analysis, the change of the total delay of traffic participants is analyzed under different conditions of pedestrian and vehicle arrival rates. Finally, by introducing pedestrian-vehicle interaction rules, a cellular automata (CA) simulation platform of pedestrian-vehicle interaction in crosswalk is established; based on the field data of Shanghai, a simulation model of intersection is established, and the total delay, queue length, and vehicle throughput under conventional signal control plan and EPP plan are compared. The results show that the pedestrian-vehicle interaction process has a great influence on the total delay of traffic participants at intersections, and pedestrian-vehicle interaction should be considered in the setting conditions of EPP. Under the same condition of vehicular flow, the more the pedestrian flow is, the smaller the delay increment will be. The higher the vehicle yielding rate is, the smaller the delay increment will be after setting EPP.
      PubDate: Wed, 06 Jan 2021 14:20:01 +000
  • Effect of Warning System on Interactive Driving Behavior at Unsignalized
           Intersection under Fog Conditions: A Study Based on Multiuser Driving
    • Abstract: The intersection collision warning system (ICWS) is an emerging technology designed to assist drivers in avoiding collisions at intersections. ICWS has an excellent performance in reducing the number of collisions and improving driving safety. Previous studies demonstrated that when visibility was low under fog conditions, ICWS could help drivers timely detect hazardous conflicting vehicles. However, the influences of ICWS on interactive driving behavior at unsignalized intersection between different vehicles have barely been discussed. This study aimed to investigate the patterns of drivers’ interactive behaviors with the assistance of a new kind of ICWS under fog conditions based on Multiuser Driving Simulation. The Multiuser Driving Simulation allowed multiple drivers to operate in the same simulation scenario at the same time, and it could capture drivers’ interactions preferably. Forty-eight licensed drivers completed the driving simulation experiment in three fog conditions (no fog, light fog, and heavy fog) and two warning conditions (warning and no warning), in which the drivers drove in a straight-moving situation at unsignalized intersection with potential collision risks caused by the encounter of two vehicles. The results verified that warning and fog conditions were significant factors that affected the interactive driving behavior in the unsignalized intersection collision avoidance process, including the driver’s decision, TTC of action point, average acceleration (deceleration) rate, and postencroachment time. Compared to conditions without ICWS, the ICWS could help drivers make collision avoidance actions earlier and change the speed more smoothly. In addition, with the help of Multiuser Driving Simulation, associations between decision driving behaviors of vehicles were discussed with caution. The results revealed the decision-making mechanism of drivers in the process of interaction with other drivers. Under the influence of fog, interactive driving processes were fraught with increased risk at unsignalized intersection. However, the ICWS helped drivers interact more harmoniously, safely, and efficiently. The findings shed some light on the further development of ICWS and the study on interactive driving behavior.
      PubDate: Wed, 30 Dec 2020 07:05:00 +000
  • A Mixed-Flow Cellular Automaton Model for Vehicle Nonstrict Priority
           Give-Way Behavior at Crosswalks
    • Abstract: The vehicle nonstrict priority give-way behavior (VNPGWB) is a common part of traffic interaction between motorized and nonmotorized vehicles in many countries. This study proposes a mixed-flow cellular automaton model to simulate the passing of vehicles in front of bicycles at crosswalks. The mixed-flow model combines a vehicle model with a bicycle model, using nonstrict priority give-way and strict give-way two driving behaviors defined as relating to the decision point rule and the launching rule, respectively. Simulation results showed that as the vehicle and bicycle inflow rates increased, a critical inflow rate divided vehicle and bicycle traffic flow into free flow and saturated flow conditions. The values of vehicle saturation flow decreased from 0.34 to 0.05, and the values of bicycle saturation flow decreased from 0.54 to 0.44, indicating that the mixed traffic flow has a negative effect on vehicle and bicycle saturated flow. Results also showed that VNPGWB effectively improves vehicle saturation flow over that of the strict give way. The advantage of VNPGWB is more significant when vehicles and bicycles are in saturation traffic flow.
      PubDate: Tue, 29 Dec 2020 08:20:01 +000
  • A Big-Data-Driven Framework for Parking Demand Estimation in Urban Central
    • Abstract: Parking planning is a key issue in the process of urban transportation planning. To formulate a high-quality planning scheme, an accurate estimate of the parking demand is critical. Most previous published studies were based primarily on parking survey data, which is both costly and inaccurate. Owing to limited data sources and simplified models, most of the previous research estimates the parking demand without consideration for the relationship between parking demand, land use, and traffic attributes, thereby causing a lack of accuracy. Thus, this study proposes a big-data-driven framework for parking demand estimation. The framework contains two steps. The first step is the parking zone division method, which is based on the statistical information grid and multidensity clustering algorithms. The second step is parking demand estimation, which is extracted by support vector machines posed in the form of a machine learning regression problem. The framework is evaluated using a case in the city center in Cangzhou, China.
      PubDate: Tue, 29 Dec 2020 08:05:01 +000
  • Developing Roadway Safety Models for Winter Weather Conditions Using a
           Feature Selection Algorithm
    • Abstract: Inclement winter weather such as snow, sleet, and freezing rain significantly impacts roadway safety. To assess the safety implications of winter weather, maintenance operations, and traffic operations, various crash frequency models have been developed. In this study, several datasets, including for weather, snowplow operations, and traffic information, were combined to develop a robust crash frequency model for winter weather conditions. When developing statistical models using such large-scale multivariate datasets, one of the challenges is to determine which explanatory variables should be included in the model. This paper presents a feature selection framework using a machine-learning algorithm known as the Boruta algorithm and exhaustive search to select a list of variables to be included in a negative binomial crash frequency model. This paper’s proposed feature selection framework generates consistent and intuitive results because the feature selection process reduces the complexity of interactions among different variables in the dataset. This enables our crash frequency model to better help agencies identify effective ways to improve roadway safety via winter maintenance operations. For example, increased plowing operations before the start of storms are associated with a decrease in crash rates. Thus, pretreatment operations can play a significant role in mitigating the impact of winter storms.
      PubDate: Tue, 29 Dec 2020 06:50:00 +000
  • Theoretical Research on Longitudinal Profile Design of Superhighways
    • Abstract: To improve driving safety on superhighways, longitudinal profile design parameters of a superhighway are calculated via force analysis while a car is driven on a slope. The calculations consider characteristics of drivers, cars, and roads. According to the vehicle type, design speed, and natural conditions, the maximum longitudinal slope of a superhighway is calculated and compared with those of an ordinary superhighway and high-speed railway. Based on analysis of the vehicle climbing performance, braking performance, and driver visual characteristics, the maximum and minimum slope lengths of a superhighway are calculated. By analyzing the elements of vertical curves, the minimum radius and minimum length of the vertical curves of a superhighway are calculated by considering factors such as mitigating the impact at the slope bottom, driving at night, and driving time along vertical curves. Analysis and calculation results show that when the maximum longitudinal slope is 2.50%, 2.25%, and 2.00%, the minimum slope length is 450 m, 400 m, and 350 m, respectively, and the minimum vertical curve length is 145 m, 130 m, and 115 m, respectively, and the superhighway travel requirements can be satisfied at speeds of 180 km/h, 160 km/h, and 140 km/h, respectively.
      PubDate: Mon, 28 Dec 2020 14:35:01 +000
  • Can I Trust You' Estimation Models for e-Bikers Stop-Go Decision
           before Amber Light at Urban Intersection
    • Abstract: Electric bike (e-bike) riders’ inappropriate go-decision, yellow-light running (YLR), could lead to accidents at intersection during the signal change interval. Given the high YLR rate and casualties in accidents, this paper aims to investigate the factors influencing the e-bikers’ go-decision of running against the amber signal. Based on 297 cases who made stop-go decisions in the signal change interval, two analytical models, namely, a base logit model and a random parameter logit model, were established to estimate the effects of contributing factors associated with e-bikers’ YLR behaviours. Besides the well-known factors, we recommend adding approaching speed, critical crossing distance, and the number of acceleration rate changes as predictor factors for e-bikers’ YLR behaviours. The results illustrate that the e-bikers’ operational characteristics (i.e., approaching speed, critical crossing distance, and the number of acceleration rate change) and individuals’ characteristics (i.e., gender and age) are significant predictors for their YLR behaviours. Moreover, taking effects of unobserved heterogeneities associated with e-bikers into consideration, the proposed random parameter logit model outperforms the base logit model to predict e-bikers’ YLR behaviours. Providing remarkable perspectives on understanding e-bikers’ YLR behaviours, the predicting probability of e-bikers’ YLR violation could improve traffic safety under mixed traffic and fully autonomous driving condition in the future.
      PubDate: Thu, 24 Dec 2020 07:35:02 +000
  • A 3D Image Reconstruction Model for Long Tunnel Geological Estimation
    • Abstract: Long tunnels often collapse during the construction period. To ensure personnel safety, the geological characteristics must be predicted before tunnel face excavation. In this study, the ground-penetrating radar (GPR) technique is introduced to obtain information regarding the tunnel excavation face at a certain interval. The amplitude of the radar echo signal is expressed as a function of the position and travel time. A B-scan strategy is selected for the GPR to obtain tunnel information. A frequency-domain (-k) focusing algorithm, namely, a synthetic aperture radar focusing algorithm, is applied to focus scattered radar signals to obtain focused images. A low-pass filter is designed to remove noises from the original signals. The contours of target objects are extracted from the background information using the edge detection technique. Space coordinate values of the objects are converted to polar coordinates using the Hough transform algorithm for 3D modeling. Visual C++ and AutoCAD are combined to develop a 3D CAD model to help managers in controlling the construction process. The system creates 3D visualization model images and evaluates the geological characteristics of the tunnel excavation faces. The Taigu Tunnel located in the Shanxi Province of China is taken as a case study. A procedure for the geological analysis of this tunnel is introduced in detail, and a 3D image model is built. The results show that the 3D model can help predict rock compositions and locate potential hazards. Moreover, it has better accuracy than conventional models and can be applied to similar transportation construction projects.
      PubDate: Wed, 23 Dec 2020 15:50:00 +000
  • The Approach to Carbon Emission Quotas of Road Transportation: A Carbon
           Emission Intensity Perspective
    • Abstract: Carbon trading is an effective measure for the road transportation to reduce energy consumption and carbon emissions. Carbon emission quotas are the primary concern to ensuring the efficiency of carbon trading. However, the existing studies have mostly focused on carbon emission quotas in different regions, i.e., countries and provinces. Few literature studies simulate carbon quota allocation in the road transportation. A novel approach from the perspective of carbon emission intensity of vehicle is proposed, on the basis of data envelopment analysis (DEA) model. Unlike other studies, the idea of allocation of baseline excitation is introduced and the intensity is included in the model as the baseline. Firstly, the Delphi method is employed to select input and output indicators. Secondly, carbon emission intensity is determined by the cumulative distribution function (CDF). Furthermore, the carbon emission quotas in road transportation in 30 provinces of China are used to validate the model. The results show that (1) the carbon emission intensity of commercial trucks and buses in China’s road transport industry is 75.04 g/t·km and 13.12 g/p·km, respectively; (2) the provinces of Shanghai, Guangdong, and Xinjiang have the greatest carbon reduction potential and Henan, Hunan, and Anhui have the largest increase in emission quotas; (3) compared with traditional “history responsibility” and “baseline” methods, the proposed approach increases allocation efficiency by 19% and 14%, respectively; and (4) the approach can make the carbon emission quotas play the role of incentive while taking fairness into account and can more effectively promote the implementation of carbon trading system in road transportation.
      PubDate: Wed, 23 Dec 2020 09:20:01 +000
  • Forecast and Analysis of Coal Traffic in Daqin Railway Based on the
           SARIMA-Markov Model
    • Abstract: With the continuous advancement of China’s supply-side structural reform, the country’s energy consumption structure has undergone considerable changes, including an overall reduction in fossil energy use and a rapid increase in clean energy application. In the context of China’s coal overcapacity, port and rail capacities are difficult to change in the short term. This study forecasts the monthly coal traffic of Daqin Railway on the basis of the seasonal autoregressive integrated moving-average Markov model and then uses the monthly coal transport data of this railway from September 2009 to November 2019 as samples for model training and verification. Coal traffic from December 2019 to September 2020 is accurately predicted. This study also analyzes the effects of China’s industrial structure adjustment, clean energy utilization, and low-carbon usage on the coal transport volume of Daqin Railway. In addition, the characteristics of seasonal fluctuation and the development trend of Daqin Railway’s coal traffic are explored. This study provides a reference for adjusting the train operation chart of Daqin Railway’s coal transport and developing a special coal train operation plan. It can determine the time of coal transport peak warning, improve the efficiency of coal transport management, and eventually realize a reasonable allocation of resources for Daqin Railway.
      PubDate: Wed, 23 Dec 2020 09:05:01 +000
  • Collaborative Strategies and Simulation of Vehicle Group Behaviors for
           Off-Ramp Areas
    • Abstract: With the increase of vehicle ownership and the rapid growth of urban traffic, the problem of congestion in the off-ramp area of the main expressway has become the main factor restricting overall section efficiency and inducing traffic accidents. This paper focuses on the problem of group collaborative lane-changing behaviors of off-ramp vehicles and through vehicles in off-ramp areas and proposes four kinds of vehicle group collaborative strategies based on different road space balance conditions. According to a three-lane expressway scene, a VISSIM-based simulation model is built and the optimization scheme is simulated and evaluated. The simulation results show that with the increase of traffic flow in off-ramp areas, a flow-balance strategy for downstream lanes where off-ramp vehicles merge with the outside lane in advance is more advantageous. When vehicles are leaving the main road, if traffic flow is heavy, the flow-balance strategy for lanes where off-ramp vehicles merge with the outside lane in advance (for example, the proportion of off-ramp vehicles in three lanes is 0 : 0 : 1) is better; otherwise, when the traffic flow on the main road is relatively small, the flow-balance strategy for lanes where off-ramp vehicles are distributed in lanes with different ratios (e.g., 1 : 3 : 6) is better. What is more, for future traffic management in connected vehicle environments, it can be concluded that collaborative vehicle lane-changing strategies with different traffic flow states can help to enhance traffic efficiency.
      PubDate: Wed, 23 Dec 2020 06:05:01 +000
  • Evaluation of Road Service Performance Based on Human Perception of
           Vibration While Driving Vehicle
    • Abstract: Road surface monitoring is a significant issue in providing smooth road infrastructure for vehicles, and the key to road condition monitoring is to detect road potholes that affect driving comfort and transportation safety. This paper presents a simple, efficient, and accurate way to evaluate road service performance based on the acquisition of road vibration data by vibration sensors installed in vehicles. Inspired by the discrete fast Fourier transform, the vibration acceleration is processed, and the RMS value of vibration acceleration at 1/2 octave is calculated, after which the road vibration level is calculated. The vibration level is optimized according to the human body’s sensitivity to different frequencies of vibration, resulting in road service performance indicators that can reflect the human body’s real feelings. According to the road service performance index values on the road grading, combined with GPS data on the electronic map color block labeling, the results obtained for the road condition warning, road maintenance, driver route selection have an important significance.
      PubDate: Tue, 22 Dec 2020 15:20:00 +000
  • A New Hybrid Butterfly Optimization Algorithm for Green Vehicle Routing
    • Abstract: In the industrial sector, transportation plays an essential role in distribution. This activity impacts climate change and global warming. One of the critical problems in distribution is the green vehicle routing problem (G-VRP). This study focuses on G-VRP for a single distribution center. The objective function is to minimize the distribution costs by considering fuel costs, carbon costs, and vehicle use costs. This research aims to develop the hybrid butterfly optimization algorithm (HBOA) to minimize the distribution costs on G-VRP. It was inspired by the butterfly optimization algorithm (BOA), which was by combining the tabu search (TS) algorithm and local search swap and flip strategies. BOA is a new metaheuristic algorithm that has been successfully applied in various engineering fields. Experiments were carried out to test the parameters of the proposed algorithm and vary the speed of vehicles. The proposed algorithm was also compared with several procedures of prior study. The experimental results proved that the HBOA could minimize the total distribution cost compared to other algorithms. Moreover, the computation time is also included in the analysis.
      PubDate: Tue, 22 Dec 2020 08:20:01 +000
  • An Alternative Method for Traffic Accident Severity Prediction: Using Deep
           Forests Algorithm
    • Abstract: Traffic safety has always been an important issue in sustainable transportation development, and the prediction of traffic accident severity remains a crucial challenging issue in the domain of traffic safety. A huge variety of forecasting models have been proposed to meet this challenge. These models gradually evolved from linear to nonlinear forms and from traditional statistical regression models to current popular machine learning models. Recently, a machine learning algorithm called Deep Forests based on the decision tree ensemble has aroused widespread concern, which was proposed for the first time by a research team of Nanjing University. This algorithm was proved to be more accurate and robust in comparison with other machine learning algorithms. Motivated by this benefit, this study employs the UK road safety dataset to propose a novel method for predicting the severity of traffic accidents based on the Deep Forests algorithm. To verify the superiority of our proposed method, several other machine learning algorithm-based perdition models were implemented to predict traffic accident severity with the same dataset, and the prediction results show that the Deep Forests algorithm present good stability, fewer hyper-parameters, and the highest accuracy under different level of training data volume. It is expected that the findings from this study would be helpful for the establishment or improvement of effective traffic safety system within a sustainable transportation system, which is of great significance for helping government managers to establish timely proactive strategies in traffic accident prevention and effectively improve road traffic safety.
      PubDate: Mon, 21 Dec 2020 14:05:01 +000
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