首页期刊导航|Journal of advanced transportation
期刊信息/Journal information
Journal of advanced transportation
Institute for Transportation Inc.
Journal of advanced transportation

Institute for Transportation Inc.

不定期

0197-6729

Journal of advanced transportation/Journal Journal of advanced transportationSCI
正式出版
收录年代

    Performance Assessment of a Rehabilitation Transportation Reservation Matching Service with Market Design Mechanisms

    Chen Yu LanChih Peng ChuCheng Chieh (Frank) ChenChung Cheng Lu...
    1.1-1.18页
    查看更多>>摘要：Government agencies provide huge amount of subsidies to support the rehabilitation transportation service over the past decade in eastern Taiwan; however, low demand request fulfillment rate, limited medical and transportation resources, long travel distances, and an extremely high percentage of dead mileages are still the main challenges faced by rehabilitation transportation service providers. This study applies the market design theory to match the rehabilitation buses with the requests of patients, so as to improve resource utilization efficiency in rural areas. The developed market design mechanisms aim to allocate resources to those who need them most in a matching manner, by using the deferred acceptance algorithm and the top trading cycle approach. The model is initialized with the requests of those who choose the rehabilitation bus based on their desired boarding time slots. On the other hand, the service providers of the rehabilitation bus would determine patients’ schedule based on their disability level, willingness to share the ride, number of fulfilled appointments during this month, and the travel distance of this trip as the order of preference. Since the current vehicle dispatching rule is to reserve seats of a rehabilitation bus on the “first-come-first-served” basis, and it cannot fully satisfy patients need. In accordance with the historical data, 63 of 72 demand requests could successfully reserve the seats. In the “first-come, first-served” mode, 48 requests obtained the first-ranking shift (i.e., their desired time slots), and the sum of their disability level score is 155. In the market design matching mode, 57 requests obtained the first-ranking shift, and the sum of their disability level score is 170, which demonstrates that the proposed market design matching mechanism outperforms than the conventional rules.
      原文链接:
    • NETL
    • NSTL
    • Wiley-Hindawi

    Retracted: Optimization Drive on a Flat Tire Vehicular System for Autonomous E-Vehicles Using Network Distribution Simulations

    Journal of Advanced Transportation
    1.1-1.1页
      原文链接:
    • NETL
    • NSTL
    • Wiley

    Vessel Trajectory Data Compression Algorithm considering Critical Region Identification

    Xinliang ZhangShibo ZhouZhenning Li
    1.1-1.18页
    查看更多>>摘要：Vessel trajectory data are currently the most important data source for vessel trajectory data mining research. However, vessel AIS data have a short sampling time interval and a large amount of data redundancy, which hampers the efficient utilization of AIS data. In order to effectively remove redundant information from AIS data and improve its usage efficiency, a compression algorithm for vessel trajectory data compression algorithm considering critical region identification (VATDC_CCRI) is proposed. The VATDC_CCRI algorithm identifies the critical regions of a vessel’s trajectory by analyzing the distribution of node variation rates. It employs the Douglas–Peucker (DP) algorithm to compress the data in these critical regions, reducing the distortion of the trajectory after compression. Additionally, the algorithm utilizes a sliding window approach to process the initial trajectory to improve the quality of the compressed vessel trajectories and retain as many spatiotemporal characteristics of the original trajectories as possible. It combines the feature nodes from the crucial regions in the vessel’s trajectory with the results obtained from the sliding window algorithm, effectively compressing the vessel’s trajectory. Experiments conducted on individual and multiple trajectories demonstrate that the VATDC_CCRI algorithm achieves higher compression rates and exhibits faster processing speeds compared to other classical vessel trajectory compression algorithms while preserving the shape of the vessel’s trajectory significantly.
      原文链接:
    • NETL
    • NSTL
    • Wiley-Hindawi

    Analysis of Traffic Volume and Travel-Time Relationship Using Continuous One-Hour Values on Urban Expressway

    Motohiro FujitaAtsuki ArataniShinji YamadaJing Zhao...
    1.1-1.12页
    查看更多>>摘要：To make more efficient use of the expanded freeway and urban expressway networks, various measures such as bottleneck management and wide-area congestion pricing based on traffic data obtained from traffic detectors, including traffic volume and travel time, have been considered. Generally, the congestion status of the data varies from day to day. This study proposes a method for analyzing a graph of traffic volume and travel time to visually and intuitively grasp the change in the daily traffic situation using continuous one-hour values. These values are continuously generated hourly values obtained by shifting data every minute. Twenty-four hours 1 minute data for 128 days on 32 segments with detectors in the Nagoya Expressway Network in Japan were used to draw a continuous one-hour value graph. A number of graphs showed loops of continuous one-hour values with congestion and a smooth variation characteristic of values over time. These graphs provide an accurate estimate of the daily maximum one-hour traffic volumes and facilitate a sequential understanding of the congestion pattern changes on successive route segments. Hourly travel-time prediction models were constructed to macroscopically examine congestion measures over a range of several hours. These models were fabricated with high accuracy using multiple regression analysis based on the characteristics of continuous one-hour values. Exploratory predictive analysis of hourly travel-time models has allowed us to study and discuss various congestion factors in road structures and traffic flows, and it has been found to be easy to grasp the phenomenon and ensure accuracy and operability.
      原文链接:
    • NETL
    • NSTL
    • Wiley-Hindawi

    Do Expressway Interchanges Increase Crash Injury Severities? Insights Using Temporal Instability and Unobserved Heterogeneity

    Fang WangChenzhu WangSaid M. EasaSiqi Lian...
    1.1-1.20页
    查看更多>>摘要：Expressway crashes in interchange areas are a critical concern in China, posing significant economic and social challenges. Utilizing three years of crash data from the Beijing–Shanghai Expressway, this study investigates the transferability and heterogeneity of crash characteristics between interchange and noninterchange areas, as well as the temporal shifts in factors influencing injury severity levels. The research employs four series of random parameters logit models to estimate three potential crash injury severity outcomes of severe injury, minor injury, and no injury (based on the most severely injured individual in each crash) and to identify key determinants, encompassing driver, vehicle, roadway, environmental, temporal, traffic, and crash attributes. Likelihood ratio tests and out-of-sample predictions are utilized to assess the temporal stability and transferability of crash area characteristics. Additionally, the marginal effects of various determinants are calculated to understand their influence across different year periods and crash types. Key variables such as overspeed, single-vehicle, AADT (annual average daily traffic volume), Lsmin, and other crash type indicators are identified as significant random parameters, demonstrating heterogeneity in means and variances. Notable distinctions are observed between interchange and noninterchange crashes, indicating nontransferability, with most significant indicators revealing temporal instabilities. Furthermore, factors such as multivehicle involvement, buses, and nighttime conditions are identified as risk indicators, notably increasing the likelihood of severe injuries. These insights are invaluable for expressway designers and decision-makers, aiding in understanding the contributing mechanisms of various elements. This study suggests that stricter enforcement measures are crucial to prevent random lane changes, particularly at interchange entrances and exits. Additionally, effective management strategies and enforcement countermeasures should be implemented to mitigate crash injury outcomes in both interchange and noninterchange areas.
      原文链接:
    • NETL
    • NSTL
    • Wiley-Hindawi

    Revealing the Impacts of the Pandemic on Travel Behavior by Examining Pre- and Post-COVID-19 Surveys

    Zoltán György VargaTamás TettamantiDomokos Esztergár-KissMichela Le Pira...
    1.1-1.12页
    查看更多>>摘要：Recently, the topic of travel behavior and social media usage has been widely discussed. The current study specifically focuses on how specific factors, such as the sociodemographic variables, the number of friends, the social media usage, and the ICT usage, influence their travel patterns based on survey results conducted in pre- and post-COVID-19 times. The effect of the COVID-19 pandemic is taken into consideration to better understand the impact of restrictions on travel attitudes. Statistical analysis is carried out to investigate the survey data. The results show that the pandemic has made a huge impact on general travel behavior, especially in terms of transport mode choice shifting towards individual modes, such as car and walking. The location choice of the participants has a significant connection to the available transport mode and the price range of the place, together with the retrieved information from the ICT devices. Based on the results, it can be seen that the pandemic has deepened the number of close friendships, but younger people do not tend to choose trendy places anymore. In addition, the results show that there is no direct connection between the number of friends and the number of meetings, and the daily online meetings have not replaced all personal meetings.
      原文链接:
    • NETL
    • NSTL
    • Wiley-Hindawi

    Optimizing Electric Truck Routing and Charging with Soft Time Windows Using Vehicle-to-Grid Technology

    Jong-Hyun RyuSeong Wook HwangGianfranco Fancello
    1.1-1.10页
    查看更多>>摘要：Due to the rapid increase in the use of electric vehicles and instability in energy supply, the application of vehicle-to-grid (V2G) technology has gained attention in the freight transportation sector. V2G has the potential to increase the efficiency of power grid and make additional profits by utilizing surplus power from electric vehicle batteries. This paper proposes an optimization model for electric trucks (ETs) to provide operational decision-making support for the freight transportation sector. The objective of the model is to minimize the total net cost, which includes charging cost, discharging reward, and time penalties, while considering changes in ET charging cost and the system marginal price. Furthermore, we conduct sensitivity analysis in the vehicle routing problem with soft time windows using ETs in the V2G system.
      原文链接:
    • NETL
    • NSTL
    • Wiley-Hindawi

    Exploring the Behavior-Driven Crash Risk Prediction Model: The Role of Onboard Navigation Data in Road Safety

    Xiao-chi MaJian LuYiik Diew WongJaehyun (Jason) So...
    1.1-1.16页
    查看更多>>摘要：Driving behavior has frequently been overlooked in previous road traffic crash research. Hereby, abnormal (extreme) driving behavior data transmitted by the onboard navigation systems were collected for vehicles involved in traffic crashes, including sharp-lane-change, sharp-acceleration, and sudden-braking behaviors. Using these data in conjunction with expressway crash records, multiple classification learners were trained to establish a behavior-driven risk prediction model. To further investigate the influence of driving behavior on crash risk, partial dependence plots (PDPs) were applied. Regression analyses indicate that models have a stronger effect when derivative features such as frequency of specific deviant behavior, speed, and acceleration in the behavior process are included. The behavioral RUSBoost model surpasses other models, achieving an AUC prediction metric of 0.782 and outperforming traditional traffic-flow-driven machine learning models. PDP analysis demonstrates that the sudden-braking behavior is the leading contributory factor of expressway crashes, particularly when the acceleration exceeds 0.5 G. This study confirms the potential of predicting crash risks through augmenting behavior data from navigation software; the findings lay a foundation for countermeasures.
      原文链接:
    • NETL
    • NSTL
    • Wiley-Hindawi

    Minimum Cost Flow-Based Integrated Model for Electric Vehicle and Crew Scheduling

    Yindong ShenYuanyuan LiTao Liu
    1.1-1.23页
    查看更多>>摘要：Vehicle and crew scheduling is vital in public transit planning. Conventionally, the issues are handled sequentially as the vehicle scheduling problem (VSP) and crew scheduling problem (CSP). However, integrating these planning steps offers additional flexibility, resulting in improved efficiency compared with sequential planning. Given the ever-growing market share of electric buses, this paper introduces a new model for integrated electric VSP and CSP, called EVCSPM. This model employs the minimum cost flow formulations for electric VSP, set partitioning for CSP, and linking constraints. Due to the nonlinear integer property of EVCSPM, we propose a method that hybrids a matching-based heuristic and integer linear programming solver, GUROBI. The numerical results demonstrate the efficiency of our methodology, and the integrated model outperforms the sequential model in real-life scenarios.
      原文链接:
    • NETL
    • NSTL
    • Wiley-Hindawi

    Automated Lane-Level Road Geometry Estimation Using Microscopic Trajectory Data

    Junhua WangChengmin LiTing FuLanfang Zhang...
    1.1-1.14页
    查看更多>>摘要：Vehicle trajectory data is in high demand for transportation research due to its rich detail. Lane information is an important aspect of trajectory data, which is typically obtained using sensors such as cameras or LiDAR, which are able to extract road lane features. However, some sensors for trajectory tracking (e.g., MMW radar sensors) are unable to provide lane information. Vehicle detection and trajectory tracking systems based on these sensing technologies can integrate with lane information through manual calibration during initial installation, but this process is labor-intensive and requires frequent recalibration as the sensors gradually become deviated by wind and vibration. This has posed a challenge for trajectory tracking, particularly for real-time applications. To address this challenge, this paper proposes a method for estimating lane-level road geometrics using microscopic trajectory data. The method involves segmenting the trajectory points using direction vectors and clustering them and fitting a series of cluster center points. The mean error (ME) of the distance between the estimated result and the ground truth reference is used to measure the accuracy of the lane-level road geometrics estimation in different conditions. Results show that when the average trajectory data includes at least approximately 30 points per meter in each segment, the ME is always less than 0.1 m. The method has also been tested on MMW wave radar data and found to be effective. This demonstrates the feasibility of our approach for dynamic calibration of road alignment in vehicle trajectory tracking systems.
      原文链接:
    • NETL
    • NSTL
    • Wiley-Hindawi