Urban Traffic Control Meets Decision Recommendation System: A Survey and Perspective

Urban traffic control is a multifaceted and demanding task that necessitates extensive decision-making to ensure the safety and efficiency of urban transportation systems. Traditional approaches require traffic signal professionals to manually intervene on traffic control devices at the intersection level, utilizing their knowledge and expertise. However, this process is cumbersome, labor-intensive, and cannot be applied on a large network scale. Recent studies have begun to explore the applicability of recommendation system for urban traffic control, which offer increased control efficiency and scalability. Such a decision recommendation system is complex, with various interdependent components, but a systematic literature review has not yet been conducted. In this work, we present an up-to-date survey that elucidates all the detailed components of a recommendation system for urban traffic control, demonstrates the utility and efficacy of such a system in the real world using data and knowledge-driven approaches, and discusses the current challenges and potential future directions of this field.

I. Introduction

Traffic congestion, a persistent issue during the global urbanization process, has garnered significant attention from both academic and engineering communities. Numerous studies have been conducted on urban traffic control, operations, and management. However, the majority of these studies focus on optimizing signal timing at isolated intersections, neglecting regional or city-level solutions [1]. In recent years, the development of data-dependent models for optimizing signal timings has been observed, but these models are still flawed due to the non-recurrent and ad-hoc nature of urban traffic flow [2]. Consequently, professional traffic engineers are often required to adjust signal hyperparameters during congestion [3]. Although their presence is imperative for handling traffic congestion under certain circumstances, human resources are limited and must be utilized efficiently to facilitate city-level traffic control in practice. In this context, a recommendation system for traffic control presents a feasible solution.