Traffic Signal Control via Reinforcement Learning for Reducing Global Vehicle Emission

Bálint Kővári, Lászlo Szőke, Tamás Bécsi, Szilárd Aradi and Péter Gáspár
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Bálint Kővári: Department of Control for Transportation and Vehicle Systems, Budapest University of Technology and Economics, H-1111 Budapest, Hungary
Lászlo Szőke: Robert Bosch Kft., H-1103 Budapest, Hungary
Tamás Bécsi: Department of Control for Transportation and Vehicle Systems, Budapest University of Technology and Economics, H-1111 Budapest, Hungary
Szilárd Aradi: Department of Control for Transportation and Vehicle Systems, Budapest University of Technology and Economics, H-1111 Budapest, Hungary
Péter Gáspár: System and Control Lab, Institute for Computer Science and Control, H-1111 Budapest, Hungary

Sustainability, 2021, vol. 13, issue 20, 1-18

Abstract: The traffic signal control problem is an extensively researched area providing different approaches, from classic methods to machine learning based ones. Different aspects can be considered to find an optima, from which this paper emphasises emission reduction. The core of our solution is a novel rewarding concept for deep reinforcement learning (DRL) which does not utilize any reward shaping, hence exposes new insights into the traffic signal control (TSC) problem. Despite the omission of the standard measures in the rewarding scheme, the proposed approach can outperform a modern actuated control method in classic performance measures such as waiting time and queue length. Moreover, the sustainability of the realized controls is also placed under investigation to evaluate their environmental impacts. Our results show that the proposed solution goes beyond the actuated control not just in the classic measures but in emission-related measures too.

Keywords: deep reinforcement learning; emission-reduction; sustainability; traffic signal control (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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