TY - GEN
T1 - Signal-free Intersection Cooperative Optimization Scheme for CAVs with Velocity-prioritized Emergency Vehicles
AU - Hua, Bikang
AU - Chen, Kaiyuan
AU - Chai, Runqi
AU - Chai, Senchun
AU - Xia, Yuanqing
AU - Liang, Wannian
N1 - Publisher Copyright:
© 2023 Technical Committee on Control Theory, Chinese Association of Automation.
PY - 2023
Y1 - 2023
N2 - This paper studies cooperative trajectory planning for multiple connected and automated vehicles (CAVs) traveling from and off multi-lane roads at a signal-free intersection with the consideration of velocity-prioritized emergency vehicles, such as ambulances and fire engines. In most of the current studies, the trajectory of each CAV is either fixed or in line with the topology of the fleet, whilst the velocity of each CAV is preset with an inflexible pattern, which severely limits the efficiency of the collaboration. Moreover, the priority of emergency vehicles is not well considered in the aforementioned strategies. This research is aimed to address the issues. The intersection control task is formulated as an optimal control problem (OCP), in which the velocities of the CAVs can be set with any reasonable aspiration, while there is no lane discipline at the intersection. When designing the control strategy, unmanned vehicles of various sizes with differentiated velocity priorities are taken into account. An adaptive stepwise optimization (ASO) method is proposed to improve the OCP solution efficiency.
AB - This paper studies cooperative trajectory planning for multiple connected and automated vehicles (CAVs) traveling from and off multi-lane roads at a signal-free intersection with the consideration of velocity-prioritized emergency vehicles, such as ambulances and fire engines. In most of the current studies, the trajectory of each CAV is either fixed or in line with the topology of the fleet, whilst the velocity of each CAV is preset with an inflexible pattern, which severely limits the efficiency of the collaboration. Moreover, the priority of emergency vehicles is not well considered in the aforementioned strategies. This research is aimed to address the issues. The intersection control task is formulated as an optimal control problem (OCP), in which the velocities of the CAVs can be set with any reasonable aspiration, while there is no lane discipline at the intersection. When designing the control strategy, unmanned vehicles of various sizes with differentiated velocity priorities are taken into account. An adaptive stepwise optimization (ASO) method is proposed to improve the OCP solution efficiency.
KW - Connected and automated vehicles (CAVs)
KW - Cooperative motion planning
KW - Intersection control
KW - Optimal control
KW - Trajectory optimization
UR - http://www.scopus.com/inward/record.url?scp=85175524928&partnerID=8YFLogxK
U2 - 10.23919/CCC58697.2023.10240951
DO - 10.23919/CCC58697.2023.10240951
M3 - Conference contribution
AN - SCOPUS:85175524928
T3 - Chinese Control Conference, CCC
SP - 6491
EP - 6496
BT - 2023 42nd Chinese Control Conference, CCC 2023
PB - IEEE Computer Society
T2 - 42nd Chinese Control Conference, CCC 2023
Y2 - 24 July 2023 through 26 July 2023
ER -