基于模型预测控制的可变目标距离自适应巡航控制研究

Translated title of the contribution: A Model Predict Control based Adaptive Cruise Control of Variable Target Distance

Ya'nan Zhao, Taixiang Wang*, Li Gao, Haixin Sun, Xiancai Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

To solve the problems presented to the adaptive cruise system in the complex traffic environment, an adaptive cruise control algorithm with variable target distance control algorithm was proposed. The complex traffic conditions mainly consider as following two aspects. A side car cut into the front of the vehicle, causing the expected relative distance obtained from the target expected distance calculation model emerge a step change from the actual relative distance. Closing to the car in front, the target vehicle must start and stop constantly in congested road conditions, causing the speed, acceleration and relative distance of the target vehicle continue change, resulting in driving smoothness. For driving comfort and safety, the adaptive cruise control algorithm was arranged firstly to establish a discrete longitudinal kinematics prediction model based on the model predictive control theory. And then, considering the chassis acceleration response, the ultimate safe longitudinal following distance, the physical limitations of the vehicle itself, the driver's riding comfort and other optimal control objectives, the soft factor was introduced to obtain the feasible solution online. The algorithm was simulated and tested in real vehicles under different cut in conditions, comprehensive driving conditions and traffic jam creeping conditions, and the open-loop experiment of IDM algorithm was conducted with data. The comparison of research results shows that the adaptive cruise control algorithm considering the variable target distance of the cut in by the side vehicle can provide a maximum impact of −0.25 m/s3 on the longitudinal control under the acceleration cut in conditions of the side vehicle, lowering 50% than the IDM model . The maximum deceleration generated by longitudinal control in the traffic jam creeping condition can achieve −0.3 m/s2, lowering 30% than the IDM model. In the comprehensive condition and constant speed cruise condition, the algorithm can achieve stable longitudinal control of the vehicle, maintaining a safe distance, and the acceleration amplitude is not more than −0.36 m/s2, improving the driver's comfort, smoothness and safety effectively.

Translated title of the contributionA Model Predict Control based Adaptive Cruise Control of Variable Target Distance
Original languageChinese (Traditional)
Pages (from-to)499-509
Number of pages11
JournalBeijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
Volume43
Issue number5
DOIs
Publication statusPublished - May 2023

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