Lane departure on combined curves: driver heterogeneity, centrifugal risk, and crash prevention.

Xiaomeng Wang, Yujie Zhang, Yi Li, Xiebowen Yi, Xuesong Wang, Guangjie Hao

Abstract read

In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

6 authors.

Xiaomeng WangNational Engineering Research Center of Road Safety Control Technology, No. 5, Boxing 2nd Road Beijing Economic-Technological Development Area, Beijing, 100176, China. wangxm@shmtu.edu.cn.

Yujie ZhangCollege of Transport & Communications, Shanghai Maritime University, No. 1550, Haigang Avenue, Shanghai, 201306, China.

Yi LiLogistics Research Center, Shanghai Maritime University, No. 1550, Haigang Avenue, Shanghai, 201306, China.

Xiebowen YiCollege of Control Technology, Wuxi University of Technology, No. 1600 Gaolang West Road, Wuxi, 214121, Jiangsu, China.

Xuesong WangKey Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, No. 4800, Cao'an Road, Jiading District, Shanghai, 201804, China.

Guangjie HaoQinghai Transportation Construction Management Co., Ltd., No. 26 Wenjing Street, Xining, 810023, Qinghai, China. guangjie1.tech@outlook.com.

Funding

National Key R&D Program of China 2024YFE0115400Open Fund Project of National Engineering Research Center of Road Safety Control Technology 2024GCZXKFKT19AThe Natural Science Foundation of the Jiangsu Higher Education Institutions of China 21KJB580021The Soft Science Research Program of Shanghai Science and Technology Commission 25692104000

6 · The paper itself

Abstract

Lane departure crashes were more likely to result in severe traffic crashes. This objective of this study was to explore the effects of drivers' characteristics on the asymmetric lane departure behaviour in combined curves. A high degree of freedom driving simulator was used to collected vehicle operation data in a mountainous freeway. Totally 948 lane departure events were collected. The lane departure behaviour was classified into two categories based on centrifugal force direction: In the Direction of Centrifugal Force (IDCF) and Against the Direction of Centrifugal Force (ADCF). The average speed, maximum lateral departure and departure duration distance were analyzed. A Multivariate Adaptive Regression Splines (MARS) model was used to analyze nonlinear relationships between driver characteristics and maximum lane departure. It found that: (1) Sag-curves and crest-curves had higher average lane departure frequencies compared to downslope- and upslope-curves. (2) IDCF events showed greater departure (0.83 m > 0.41 m) and longer departure duration distance (70.07 m > 58.60 m) than ADCF events. (3) The years of driving, daily driving distance, driving experience, road expert type and departure duration distance had significantly influence on departure severity. Also, driver characteristics and lane departure duration distance had an interaction effect on departure severity. (4) Speed and road geometry design could jointly influence the degree of lane departure, e.g., speed significantly affects lane departure behaviour on downslope-curves and upslope-curves in the IDCF scenario. (5) The lane departure duration distance threshold (35.00-110.00 m), and speed threshold (86.77-108.63 km/h) were proposed for the lane departure process. The study provided a basis for the optimisation of ADAS systems, the development of targeted driver training for high-risk drivers, and the optimisation of visual guidance design for combined curves.

Indexed as

Centrifugal force directionCombined curvesDriver characteristicsLane departure behaviourMultivariate adaptive regression splines (MARS)Threshold value

Identifiers

PMID41680258

DOI10.1038/s41598-026-37251-1

PMCPMC12976100

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LicenceCC BY

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.