TY - GEN
T1 - Robust Optimal ECO-driving Control with Uncertain Traffic Signal Timing
AU - Sun, Chao
AU - Shen, Xinwei
AU - Moura, Scott
N1 - Publisher Copyright:
© 2018 AACC.
PY - 2018/8/9
Y1 - 2018/8/9
N2 - This paper proposes a robust optimal eco-driving control strategy considering multiple signalized intersections with uncertain traffic signal timing. A spatial vehicle velocity profile optimization formulation is developed to minimize the global fuel consumption, with driving time as one state variable. We introduce the concept of 'effective red-light duration' (ERD), formulated as a random variable, to describe the feasible passing time through signalized intersections. A chance constraint is appended to the optimal control problem to incorporate robustness with respect to uncertain signal timing. The optimal eco-driving control problem is solved via dynamic programming (DP). Simulation results demonstrate that the optimal eco-driving can save fuel consumption by 50-57 % while maintaining arrival time at the same level, compared with a modified intelligent driver model as the benchmark. The robust formulation significantly reduces traffic intersection violations, in the face of uncertain signal timing, with small sacrifice on fuel economy compared to a non-robust approach.
AB - This paper proposes a robust optimal eco-driving control strategy considering multiple signalized intersections with uncertain traffic signal timing. A spatial vehicle velocity profile optimization formulation is developed to minimize the global fuel consumption, with driving time as one state variable. We introduce the concept of 'effective red-light duration' (ERD), formulated as a random variable, to describe the feasible passing time through signalized intersections. A chance constraint is appended to the optimal control problem to incorporate robustness with respect to uncertain signal timing. The optimal eco-driving control problem is solved via dynamic programming (DP). Simulation results demonstrate that the optimal eco-driving can save fuel consumption by 50-57 % while maintaining arrival time at the same level, compared with a modified intelligent driver model as the benchmark. The robust formulation significantly reduces traffic intersection violations, in the face of uncertain signal timing, with small sacrifice on fuel economy compared to a non-robust approach.
UR - http://www.scopus.com/inward/record.url?scp=85052568995&partnerID=8YFLogxK
U2 - 10.23919/ACC.2018.8430781
DO - 10.23919/ACC.2018.8430781
M3 - Conference contribution
AN - SCOPUS:85052568995
SN - 9781538654286
T3 - Proceedings of the American Control Conference
SP - 5548
EP - 5553
BT - 2018 Annual American Control Conference, ACC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 Annual American Control Conference, ACC 2018
Y2 - 27 June 2018 through 29 June 2018
ER -