Curve safe speed model considering driving style based on driver behaviour questionnaire-Reference-Cited by-同舟云学术

Curve safe speed model considering driving style based on driver behaviour questionnaire

Published:2019-08 Issue: Volume:65 Page:536-547
ISSN:1369-8478
Container-title:Transportation Research Part F: Traffic Psychology and Behaviour
language:en
Short-container-title:Transportation Research Part F: Traffic Psychology and Behaviour

Author:

Deng Zejian,Chu Duanfeng,Wu Chaozhong,He Yi,Cui Jian

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hubei Province

Fundamental Research Funds for the Central Universities

Publisher

Elsevier BV

Subject

Applied Psychology,Transportation,Automotive Engineering,Civil and Structural Engineering

Reference51 articles.

1. Data requirements for enhanced digital maps in an advanced curve-speed warning system;Aguil-Éra;Transportation Research Record: Journal of the Transportation Research Board,2004

2. Chen, X., Lu, M., Zhang, D., Chi, R., & Wang, J. (2010). Integrated safety speed model for curved roads. In FISITA. Proceedings of the 2010 world automotive congress (pp. 1–7). London: FISITA.

3. Chen, X., Chi, R., Wang, J., Pang, C., & Xiao, Q. (2011, October). Driver safe speed model based on BP neural network for rural curved roads. In International conference on computer and computing technologies in agriculture (pp. 92–102). Springer, Berlin Heidelberg.

4. Statistics Annals of Road Traffic Accident of People’s Republic of China (2014). Traffic Administration Bureau, Chinese Ministry of Public Security, 2015.

5. The driver behaviour questionnaire as a predictor of accidents: A meta-analysis;de Winter;Journal of Safety Research,2010

Cited by 51 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. 100 Drivers, 2200 km: A Natural Dataset of Driving Style toward Human-centered Intelligent Driving Systems;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

2. Advanced Curve Speed Planning with Sideslip and Rollover Prevention for Heavy Trucks;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

3. Path tracking with personalized handling stability constraints matched to driving styles;Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering;2024-05-10

4. Drivers’ Ability to Detect Traffic Signs on Curves with the Presence of Clutter in the Visual Field: A Systematic Review;Transportation Research Record: Journal of the Transportation Research Board;2024-03-29

5. Driver Steering Behaviour Modelling Based on Neuromuscular Dynamics and Multi-Task Time-Series Transformer;Automotive Innovation;2024-01-11