An investigation on coordination of lane departure warning based on driver behaviour characteristics

被引：4
作者：
Zheng H. [1 ]
Zhao M. [1 ]
机构：
[1] State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, Jilin
来源：
International Journal of Vehicle Autonomous Systems | 2020年 / 15卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Driver characteristics; Future offset distance; Lane departure warning system; LDWS; Simulator experiments; Time lane crossing;
D O I：
10.1504/IJVAS.2020.104823
中图分类号：
学科分类号：
摘要：
As an important part of Advanced Driver Assistance Systems (ADAS), Lane Departure Warning System (LDWS) plays a significant role in lane departure prevention and reducing traffic accidents caused by lane departure. In order to improve the warning effect of the system as well as driver acceptance, this paper describes an LDWS algorithm for personalised driving assistance. The proposed combination algorithm consists of a multimode Time to Lane Crossing (TLC) and a Future Offset Distance (FOD) based on driver behaviour characteristics. To detect driver's lane change intention, the steering behaviour has been developed incorporating vehicle states and road curvature. Driving simulator tests are conducted to validate the lane departure warning algorithm with multi-mode based on TLC and FOD under various driving situations. The obtained test results are consistent with the expected performance. © 2020 Inderscience Enterprises Ltd.
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收藏
页码：77 / 99
页数：22
相关论文
共 15 条
  • [1] Angkititrakul P., Terashima R., Wakita T., On the use of stochastic driver behavior model in lane departure warning, IEEE Transactions on Intelligent Transportation Systems, 12, 1, pp. 174-183, (2011)
  • [2] Biassoni F., Ruscio D., Cicerim R., Limitations and automation: The role of information about device-specific features in ADAS acceptability, Safety Science, 85, pp. 179-186, (2016)
  • [3] Clanton J.M., Bevly D.M., Hodel A.S., A low-cost solution for an integrated multisensor lane departure warning system, IEEE Transactions on Intelligent Transportation Systems, 10, 1, pp. 47-59, (2009)
  • [4] Jung C.R., Kelber C.R., Lane following and lane departure using a linear-parabolic model, Image and Vision Computing, 23, 13, pp. 1192-1202, (2005)
  • [5] Lefevre S., Vasquez D., Laugier A.C., A survey on motion prediction and risk assessment for intelligent vehicles, ROBOMECH Journal, pp. 1-14, (2014)
  • [6] Lin N., Research on the Identification Algorithm of Driver Behavior Characteristics for "Car Adapts to Driver" X-by-wire Vehicle, (2016)
  • [7] Lin N., Zong C., Tomizuka M., Song P., Zhang Z., An overview on study of identification of driver behavior characteristics for automotive control, Mathematical Problems in Engineering, pp. 1-15, (2014)
  • [8] Liu Y., Ji X., Matching strategy of electric power steering assistant characters based on the vehicle inherent road feel, Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering, 225, 11, pp. 1481-1491, (2011)
  • [9] Liu Y., Ji X., Ryouhei H., Mizuno T., Function of shoulder muscles of driver in vehicle steering maneuver, Science China Technological Sciences, 55, 12, pp. 3445-3454, (2012)
  • [10] Narote S.P., Bhujbal P.N., Narote A.S., Dhane D.M., A review of recent advances in lane detection and departure warning system, Pattern Recognition, 73, pp. 216-234, (2018)
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