Robust Optimal ECO-driving Control with Uncertain Traffic Signal Timing. Sun, C., Shen, X., & Moura, S. In 2018 Annual American Control Conference (ACC), pages 5548–5553, June, 2018. 24 citations (Semantic Scholar/DOI) [2022-07-07] ISSN: 2378-5861doi abstract bibtex 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.
@inproceedings{sun_robust_2018,
title = {Robust {Optimal} {ECO}-driving {Control} with {Uncertain} {Traffic} {Signal} {Timing}},
doi = {10.23919/acc.2018.8430781},
abstract = {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.},
booktitle = {2018 {Annual} {American} {Control} {Conference} ({ACC})},
author = {Sun, Chao and Shen, Xinwei and Moura, Scott},
month = jun,
year = {2018},
note = {24 citations (Semantic Scholar/DOI) [2022-07-07]
ISSN: 2378-5861},
keywords = {/unread, Clocks, Fuels, Optimization, Robustness, Timing, Uncertainty, Vehicles},
pages = {5548--5553},
}
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