Journal of South China University of Technology(Natural Science) >

2025 , Vol. 53 >Issue 2: 38 - 47

DOI: https://doi.org/10.12141/j.issn.1000-565X.240346

Traffic Safety

Complex Scenario Construction Method for Navigation Pilot Based on Natural Driving Behaviour

  • WU Biao ,
  • REN Hongze ,
  • ZHENG Lianqing ,
  • ZHU Xichan ,
  • MA Zhixiong
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  • College of Automotive Studies，Tongji University，Shanghai 201804，China
武彪（1987—），男，博士生，主要从事智能网联汽车安全分析研究。E-mail： biao.wu@tongji.edu.cn

Received date: 2024-07-01

  Online published: 2024-09-29

Supported by

the National Key R & D Program of China(2022YFB2503404)

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Abstract

As the focus of research and development of intelligent connected vehicles, the test and evaluation of autonomous driving systems must focus on the real performance of vehicles in complex weather and complex traffic flow scenarios. This research proposed a method for constructing complex scenarios based on weather complexity and traffic complexity to meet the testing requirements of intelligent driving systems in challenging traffic environments. Using natural driving data from China’s large-scale field operational test project (China-FOT), the study analyzed vehicle dynamics parameters such as speed, longitudinal acceleration, lateral acceleration, and yaw rate. By fitting safety boundary envelopes, driving behavior risk levels were defined, and hazardous scenarios in natural driving were identified. These scenarios help clarify the fundamental scene types related to the functional safety of navigation-based intelligent driving. A traffic interaction coupling method, incorporating multiple dynamic target features, was applied to construct complex scenario types. The quantified natural weather factors were used to construct influence indicators, such as light factor, rainfall factor, fog factor, which are employed to characterize the weather complexity through the distribution of natural driving behavior characteristics. The complexity parameters, including encounter angle, relative distance, relative speed, were constructed using the Support Vector Machines and K-fold cross validation methods to characterize the traffic state of the complex scenarios. In order to ascertain the complexity of the test scenario, a closed field vehicle test was conducted, during which the real test performance evaluation parameters were employed to verify the rationality of the complex scenario construction. This research indicates the necessity to construct a test scenario that can accurately portray the real-world complex traffic environment for the navigation pilot driving functions. This will facilitate the optimization and iteration of the autonomous driving system of intelligent connected vehicles.

Key words： natural driving behavior character; complex scenario; weather complexity; traffic complexity; support vector machine; information entropy theory

Cite this article

WU Biao , REN Hongze , ZHENG Lianqing , ZHU Xichan , MA Zhixiong . Complex Scenario Construction Method for Navigation Pilot Based on Natural Driving Behaviour[J]. Journal of South China University of Technology(Natural Science), 2025 , 53(2) : 38 -47 . DOI: 10.12141/j.issn.1000-565X.240346

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