Welcome to Journal of Automotive Safety and Energy,

Journal of Automotive Safety and Energy ›› 2024, Vol. 15 ›› Issue (3): 309-320.DOI: 10.3969/j.issn.1674-8484.2024.03.003

• Automotive Safety • Previous Articles     Next Articles

Real-time human-like speed planning method for curve entry considering experienced driving behaviors

CHEN Qitong1(), ZHAO Dong1, LIU Congzhi2,*(), LI Liang3   

  1. 1. School of Technology, Beijing Forestry University, Beijing 100083, China
    2. College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China
    3. State Key Laboratory of Intelligent Green Vehicle and Mobility (Former: State Key Laboratory of Automotive Safety and Energy), Tsinghua University, Beijing 100084, China
  • Received:2023-02-23 Revised:2024-03-15 Online:2024-06-30 Published:2024-07-01

Abstract:

A human-like safe-speed-planning method was proposed for vehicle curve entry considering coasting and safe-speed based on the chaos theory and the real curve driving velocity data to improve the safety, the comfort and the travel efficiency of autonomous vehicles. A comfort mode and an efficiency mode were constructed through formulating the curve-entry speed-planning problem of autonomous vehicles as the multi-objective optimization problems. A singularity velocity was defined to simplify the constraint condition with high-order and non-linear characteristics and to improve its computation efficiency. The results show that both the lateral accelerations and the longitudinal accelerations satisfied the friction circle constraint for the proposed strategy, with guaranteeing the driving safety in different curve scenarios. Compared with the method regardless of coasting, the maximum longitudinal acceleration, which are generated by the proposed strategy, was reduced by 9.76% in the comfort mode with the travel efficiency being improved by 61.73%. In the efficiency mode, the longitudinal accelerations values are the acceleration threshold, which satisfy the acceleration constraint with an increase of 88% in traffic efficiency. Therefore, both the comfort mode and the efficiency mode achieve a balance between comfort and travel efficiency.

Key words: autonomous vehicle, coasting driving behaviors, vehicle curve-entry speed, human-like speed planning, multi-objective optimization, coasting driving behaviors, safe speed model

CLC Number: