journal article·2025-03-26Open access

Unveiling Driving Risks and Geometric Parameter Relationships in Urban Underground Road Curves: A Real Vehicle Experiment

Zhanji Zheng, Yuxuan Xu, Zhenke Wang, Jiaqiang Rao, Heshan Zhang, Jin Xu

Applied Sciences· Volume 15· Issue 7

Abstract

To clarify the operational characteristics and driving risks of urban underground road curves, a real vehicle driving experiment involving 20 subjects was conducted at the Jiefangbei Underground Ring Road in Chongqing. High-precision instruments were utilized to collect driving data, including vehicle speed, lateral acceleration, and longitudinal acceleration. Significance tests were performed on lateral acceleration, longitudinal acceleration, entering curve deceleration, and exiting curve acceleration. The driver behavior risk at curves was evaluated using G-G diagrams, and the distribution characteristics of curve danger points were determined. Subsequently, models were established for the relationships between lateral acceleration, entering curve deceleration, exiting curve acceleration, and curve geometric parameters. The results show that: (1) significant differences exist in lateral and longitudinal acceleration under different radius ranges; (2) the sections with the highest curve danger levels in urban underground road curves primarily concentrate within the circular curve sections of curves; (3) the number of driving risk points per unit length (m) is not correlated with curve type, but significantly related to curve radius range; (4) the relationship models between entering curve deceleration, exiting curve acceleration, and curve parameters are upward-opening quadratic functions, whereas the relationship model between lateral acceleration and curve parameters comprises two quadratic functions with different orientations.
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Research context

OpenAlex topics: Traffic and Road Safety · Automotive and Human Injury Biomechanics · Underground infrastructure and sustainability

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Traffic & Transportation, Chongqing Jiaotong University, Chongqing 400074, China

Chongqing Key Laboratory of Intelligent Integrated and Multidimensional Transportation System, Chongqing Jiatong University, Chongqing 400074, China

Funding

National Natural Science Foundation of China · China Postdoctoral Science Foundation · Natural Science Foundation of Chongqing, China · Innovative Plan of the Department of Housing and Urban-Rural Development of Guangdong Province

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