CN

Bai Haijian

Associate professor

Supervisor of Master's Candidates

Date of Birth:1980-12-31

Date of Employment:2010-07-14

School/Department:道路与交通工程系

Administrative Position:系副主任

Education Level:Postgraduate (Doctoral)

Business Address:屯溪路校区三立苑420

Gender:Male

Degree:Doctoral degree

Status:Employed

Academic Titles:教学

Alma Mater:东南大学

Discipline:Other specialties in Traffic and Transportation Engineering
Transportation Information Engineering and Control
Transportation Planning and Management

Paper Publications

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

Release time:2024-05-09 Hits:

Impact Factor:23.6

DOI number:10.1109/TITS.2024.3393490

Journal:IEEE Transactions on Intelligent Transportation Systems

Key Words:IDM, traffic oscillation, excessive acceleration,asymmetric driving, traffic flow stability

Abstract: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.

Indexed by:Journal paper

Discipline:Engineering

Document Type:J

Page Number:1 - 19

ISSN No.:1524-9050, 1558-0016

Translation or Not:no

Date of Publication:2024-05-06

Included Journals:SCI

Links to published journals:https://ieeexplore.ieee.org/document/10521562/

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