Open AccessTime‐dependent lane change trajectory optimisation considering comfort and efficiency for lateral collision avoidance
Author(s) -
Li Xianyu,
Guo Zhongyin,
Su Donglan,
Liu Qiang
Publication year - 2021
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/itr2.12045
Subject(s) - trajectory , acceleration , computer science , quintic function , collision , process (computing) , simulation , collision avoidance , control theory (sociology) , artificial intelligence , physics , computer security , control (management) , astronomy , classical mechanics , quantum mechanics , nonlinear system , operating system
Lateral collision is one of the top two accidents in the world and often occurs in the lane change. Trajectory optimisation is an effective method to solve traffic conflicts in the lane‐changing process. However, current trajectory optimisation methods are not friendly to human‐computer‐based driving assistance. This study proposes a time‐dependent lanechange trajectory optimisation considering comfort and efficiency. First, spacing constraints between the lane‐changing vehicle and surrounding vehicles are determined and quantified. Second, lane‐changing trajectory data are obtained by driving simulation experiments and extracted by data features. Third, a quintic multinomial model of lane‐changing trajectory is proposed. The results reveal that the predicted trajectory is close to the observed value. Then, the obtained trajectory is optimised by the objective function considering lane‐changing efficiency and comfort. Finally, a case study is used to demonstrate the application of the model. When a lane‐changing vehicle changes a lane at an initial speed of 90 km/h to the faster lane at the terminal speed of 110 km/h, the optimal lane‐changing time is 3.4 s, with the lateral acceleration 1.79 m/s 2 and the maximum yaw angle 0.081 rad.