TY - GEN
T1 - Improved Adaptive Cruise Control for Autonomous Vehicles with Consideration of Crash Avoidance
AU - Zhang, Yu
AU - Chu, Yunfeng
AU - Dong, Mingming
AU - Gao, Li
AU - Qin, Yechen
AU - Wang, Zhenfeng
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Current Adaptive Cruise Control (ACC) systems are prone to risk of crash from surrounding unexpected cut-in vehicles. Hence, accurate risk evaluation for collisions and corresponding crash avoidance algorithms are highly desired. Therefore, in this work, we propose an accurate Time to Collision (TTC) calculation method using elliptical vehicle geometry, and evaluate the collision risks with surrounding vehicle, quantitatively. To avoid collision with multi-direction cut-in vehicle, a controller-switching mechanism based on TTC is first designed to switch back and forth between the performance-oriented controller and safety-oriented controller. Moreover, the proposed work is validated through simulations. The simulation results reveal that, for different scenarios (car-following, front-side and rear-side cut-in), proposed method can enhance the tracking performance while avoiding crash with surrounding vehicles from front-side and rear-side cut-in, effectively.
AB - Current Adaptive Cruise Control (ACC) systems are prone to risk of crash from surrounding unexpected cut-in vehicles. Hence, accurate risk evaluation for collisions and corresponding crash avoidance algorithms are highly desired. Therefore, in this work, we propose an accurate Time to Collision (TTC) calculation method using elliptical vehicle geometry, and evaluate the collision risks with surrounding vehicle, quantitatively. To avoid collision with multi-direction cut-in vehicle, a controller-switching mechanism based on TTC is first designed to switch back and forth between the performance-oriented controller and safety-oriented controller. Moreover, the proposed work is validated through simulations. The simulation results reveal that, for different scenarios (car-following, front-side and rear-side cut-in), proposed method can enhance the tracking performance while avoiding crash with surrounding vehicles from front-side and rear-side cut-in, effectively.
KW - Adaptive cruise control
KW - Crash avoidance
KW - controller-switching mechanism
KW - model predictive control
UR - http://www.scopus.com/inward/record.url?scp=85124674900&partnerID=8YFLogxK
U2 - 10.1109/CVCI54083.2021.9661195
DO - 10.1109/CVCI54083.2021.9661195
M3 - Conference contribution
AN - SCOPUS:85124674900
T3 - 2021 5th CAA International Conference on Vehicular Control and Intelligence, CVCI 2021
BT - 2021 5th CAA International Conference on Vehicular Control and Intelligence, CVCI 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th CAA International Conference on Vehicular Control and Intelligence, CVCI 2021
Y2 - 29 October 2021 through 31 October 2021
ER -