TY - GEN
T1 - Automatic lane change maneuver in dynamic environment using model predictive control method
AU - Li, Zhaolun
AU - Jiang, Jingjing
AU - Chen, Wen Hua
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/10/24
Y1 - 2020/10/24
N2 - The lane change maneuver is one of the typical maneuvers in various driving situations. Therefore the automatic lane change function is one of the key functions for autonomous vehicles. Many researches have been conducted in this field. Most existing work focused on the solutions for the static environment and assume that the surrounding vehicles are running at constant speeds. However, in reality, if not all the vehicles on the road are fully autonomous, the situation could be much more complicated and the ego vehicle has to deal with the dynamic environment. This paper proposes a Model Predictive Control (MPC)-based method to achieve automatic lane change in a dynamic environment. A two-wheel dynamic bicycle model, which combines the longitudinal and lateral motion of the ego vehicle, together with a utility function, which helps to automatically determine the target lane have been used in the algorithm. The simulation results have demonstrated the capability of the proposed algorithm in a dynamic environment.
AB - The lane change maneuver is one of the typical maneuvers in various driving situations. Therefore the automatic lane change function is one of the key functions for autonomous vehicles. Many researches have been conducted in this field. Most existing work focused on the solutions for the static environment and assume that the surrounding vehicles are running at constant speeds. However, in reality, if not all the vehicles on the road are fully autonomous, the situation could be much more complicated and the ego vehicle has to deal with the dynamic environment. This paper proposes a Model Predictive Control (MPC)-based method to achieve automatic lane change in a dynamic environment. A two-wheel dynamic bicycle model, which combines the longitudinal and lateral motion of the ego vehicle, together with a utility function, which helps to automatically determine the target lane have been used in the algorithm. The simulation results have demonstrated the capability of the proposed algorithm in a dynamic environment.
UR - http://www.scopus.com/inward/record.url?scp=85102412463&partnerID=8YFLogxK
U2 - 10.1109/IROS45743.2020.9341729
DO - 10.1109/IROS45743.2020.9341729
M3 - Conference article published in proceeding or book
AN - SCOPUS:85102412463
T3 - IEEE International Conference on Intelligent Robots and Systems
SP - 2384
EP - 2389
BT - 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020
Y2 - 24 October 2020 through 24 January 2021
ER -