柏海舰  (副教授)

硕士生导师

出生日期:1980-12-31

入职时间:2010-07-14

所在单位:道路与交通工程系

职务:系副主任

学历:研究生(博士)毕业

办公地点:屯溪路校区三立苑420

性别:男

学位:博士学位

在职信息:在职

主要任职:教学

毕业院校:东南大学

学科:交通运输工程其他专业
交通信息工程及控制
交通运输规划与管理

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X. Chen, W. Zhang, H. Bai*. A sigmoid-based car-following model to improve acceleration stability in traffic oscillation and following failure in free flow

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影响因子:23.6

DOI码:10.1109/TITS.2024.3393490

发表刊物:IEEE Transactions on Intelligent Transportation Systems

关键字:IDM, traffic oscillation, excessive acceleration,asymmetric driving, traffic flow stability

摘要:This paper presents an improved Intelligent Driving Model (Sigmoid-IDM) to address the issues of excessive acceleration in traffic oscillation and following failure in free flow. The Sigmoid-IDM utilizes a Sigmoid function to enhance the starting-following characteristics, improve the output strategy of the spacing term, and stabilize the steady-state velocity in free flow. Furthermore, the model’s asymmetry is enhanced by introducing cautious following distance, caution driving factor, and segmentation function. The anti-interference ability of the Sigmoid-IDM is demonstrated through local stability and string stability analyses. The model parameters were calibrated using the Hefei dataset and High D data across various traffic scenarios: start-up, stop-go, and free-flow. The Sigmoid-IDM outperforms the IDM by significantly reducing errors and enhancing performance metrics. Specifically, in start-up and stop-go scenarios, the Sigmoid-IDM achieves a 28.57% and 19.04% reduction in Root Mean Square Error (RMSE) for acceleration, respectively. Comfort error during start-up is also lowered by 18.1%. In the free-flow scenario, the RMSE for spacing and velocity decreases by 15.64% and 16.36%, respectively. Furthermore, the Sigmoid-IDM demonstrates a more pronounced asymmetric behavior than the IDM, offering a more accurate representation of human drivers’ following patterns. The model’s efficacy was further validated through circular road simulation and Simulink-Carsim co-simulation, confirming its ability to accurately simulate the transition from synchronized flow to wide moving jams under variable parameters, as well as the traceability of its trajectory planning.

论文类型:期刊论文

学科门类:工学

文献类型:J

页面范围:1 - 19

ISSN号:1524-9050, 1558-0016

是否译文:

发表时间:2024-05-06

收录刊物:SCI

发布期刊链接:https://ieeexplore.ieee.org/document/10521562/

上一条: X. Chen, W. Zhang, H. Bai*. LFF: An attention allocation-based following behavior framework in lane-free environments

下一条: X. Chen, W. Zhang, H. Bai*. Two-Dimensional Following Lane-Changing (2DF-LC): A Framework for Dynamic Decision-Making and Rapid Behavior Planning