An s-shaped three-parameter (S3) traffic stream model with consistent car following relationship

Cheng, Qixiu; Liu, Zhiyuan; Lin, Yuqian; Zhou, Xuesong

doi:10.1016/j.trb.2021.09.004

Cited by 68 publications

(11 citation statements)

References 65 publications

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“…The scheduling problem considered in this study is quite trivial, and more complicated scenario and more operational constraints should be considered. In addition, traffic dynamics (Cheng et al 2021(Cheng et al , 2022Zhou et al 2022) can be taken into consideration for the bus scheduling problem in future studies.…”

Section: Discussionmentioning

confidence: 99%

Joint Optimization of Bus Scheduling and Targeted Bus Exterior Advertising

Huang

Wang

2023

J. Transp. Eng., Part A: Systems

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Bus exterior advertising provides a powerful way to establish brand awareness since it can reach a mass of audiences with a high frequency. For a certain advertisement category, the advertising effectiveness is largely depended upon its exposure times to the target audience who takes interests of the advertisement, which is termed as targeted advertising. Given that the distribution of target audiences over a city varies among different advertisement categories, a practical way of enhancing overall advertising effectiveness is to deploy the bus with certain advertisement category to the bus line that best fits it "target area". This gives rise to a decision-making problem of targeted bus exterior advertising and bus scheduling. In this paper, the problem is formulated as a bi-objective optimization model with objectives of maximizing the quantified advertising effectiveness and minimizing the number of bus fleet size to cover all trips. The advertising effectiveness is quantified using the audience demographic data. The deadheading of buses is also enabled in the scheduling process to facilitate both objectives. The NSGA-II-LNS algorithm is developed to solve the bi-objective problem with the incorporation of large neighborhood search operators into the framework of the NSGA-II to improve This material may be downloaded for personal use only. Any other use requires prior permission of the American Society of Civil Engineers. This material may be found at https://ascelibrary.org/doi/10.1061/JTEPBS.TEENG-7812. This is the Pre-Published Version. 2 solution quality. Various experiments are set up to verify the proposed model and solution algorithm.

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Section: Discussionmentioning

confidence: 99%

Joint Optimization of Bus Scheduling and Targeted Bus Exterior Advertising

Huang

Wang

2023

J. Transp. Eng., Part A: Systems

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“…In this paper, the model-driven adopted of a new Sshaped three-parameter (S3) trafc fow model [60] to estimate the relationships among three fundamental variables (i.e., fow, speed, and density). Tis trafc fow model could capture the fow-speed-density relationship simultaneously under all possible densities, especially at high densities.…”

Section: Model-driven Method Te Fundamental Diagram (Fd)mentioning

confidence: 99%

Incorporating Traffic Flow Model into A Deep Learning Method for Traffic State Estimation: A Hybrid Stepwise Modeling Framework

Pan

Guo²,

Chen

et al. 2022

Journal of Advanced Transportation

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Traffic state estimation (TSE), which reconstructs the traffic variables (e.g., speed, flow) on road segments using partially observed data, plays an essential role in intelligent transportation systems. Generally, traffic estimation problems can be divided into two categories: model-driven approaches and data-driven approaches. The model-driven method is commonly used to solve TSE efficiently and calibrate the parameters of these models. The data-driven method requires a large amount of historical observed traffic data in order to improve performance accurately. In order to combine the advantages of model-driven and data-driven methods, this paper proposed a hybrid framework incorporating the traffic flow model into deep learning (TFMDL) modeling that contains both model-driven and data-driven components. This paper focuses on highway TSE with observed data from loop detectors. We build a hybrid cost function to adjust the weights of model-driven and data-driven proportions. We then evaluate the proposed framework using the open-access performance measurement system (PMS) dataset on a corridor of US I-405 in Los Angeles, California. The experimental results show the advantages of the proposed TFMDL approach in performing better than several benchmark models in terms of estimation accuracy and data efficiency.

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“…Due to the complexity of urban traffic conditions and the diversity and uncertainty of pedestrian behaviors, the selection of intersections for investigation will directly affect the analysis of pedestrian crosswalk violations [ 34 , 35 , 36 , 37 ]. For the purpose of this study, this investigation is limited to the crosswalks of signal intersections, and it is necessary to investigate the pedestrian characteristics and environmental factors of external road traffic.…”

Section: Methodsmentioning

confidence: 99%

A Geographical and Temporal Risk Evaluation Method for Red-Light Violations by Pedestrians at Signalized Intersections: Analysis and Results of Suzhou, China

Xing

Zhang

Cheng

et al. 2022

IJERPH

Self Cite

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Red-light violations of pedestrians crossing at signal intersections is one of the key factors in pedestrian traffic accidents. Even though there are various studies on pedestrian behavior and pedestrian traffic conflicts, few focus on the risk of different crosswalks for the violating pedestrian group. Due to the spatio-temporal nature of violation risk, this study proposes a geographical and temporal risk evaluation method for pedestrian red-light violations, which combines actual survey and video acquisition. First, in the geographical-based risk evaluation, the pedestrian violation rate at signal intersections is investigated by Pearson correlation analysis to extract the significant influencing factors from traffic conditions, built environment, and crosswalk facilities. Second, in the temporal-based risk evaluation, the survival analysis method is developed to quantify the risk of pedestrian violation in different scenarios as time passes by. Finally, this study selects 16 typical signalized intersections in Suzhou, China, with 881 pedestrian crosswalk violations from a total size of 4586 pedestrians as survey cases. Results indicate that crossing distance, traffic volume on the crosswalk, red-light time, and crosswalk-type variables all contribute to the effect of pedestrian violation from a geographical perspective, and the installation of waiting refuge islands has the most significant impact. From the temporal perspective, the increases in red-light time, number of lanes, and traffic volume have a mitigating effect on the violations with pedestrian waiting time increases. This study aims to provide a development-oriented path by proposing an analytical framework that reconsiders geographical and temporal risk factors of violation. The findings could help transport planners understand the effect of pedestrian violation-related traffic risk and develop operational measures and crosswalk design schemes for controlling pedestrian violations occurring in local communities.

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An s-shaped three-parameter (S3) traffic stream model with consistent car following relationship

Cited by 68 publications

References 65 publications

Joint Optimization of Bus Scheduling and Targeted Bus Exterior Advertising

Joint Optimization of Bus Scheduling and Targeted Bus Exterior Advertising

Incorporating Traffic Flow Model into A Deep Learning Method for Traffic State Estimation: A Hybrid Stepwise Modeling Framework

A Geographical and Temporal Risk Evaluation Method for Red-Light Violations by Pedestrians at Signalized Intersections: Analysis and Results of Suzhou, China

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