Hierarchical density-based clustering methods for tolling zone definition and their impact on distance-based toll optimization

Abstract

Real-time network control strategies such as congestion pricing have been used in a number of metropolitan areas around the world for traffic congestion mitigation. Recent advances in Global Navigation Satellite System (GNSS) technology have led to increasing interest in distance- or usage-based road pricing as an effective alternative to traditional facility-, cordon- and area-based pricing that typically rely on fixed infrastructure. In this paper, we propose the use of feature-variant clustering methods, OPTICS and HDBSCAN*, as a systematic approach for tolling zone definition to operationalize distance-based tolling schemes. Subsequently, we develop a framework for predictive distance-based toll optimization to evaluate network performance for the various tolling zone definitions derived from the aforementioned feature-variant clustering methods. In this framework, for a specific tolling zone definition, tolling function parameters are optimized using a simulation-based Dynamic Traffic Assignment (DTA) model operating within a rolling horizon scheme. Predictive optimization is integrated with the guidance information generation. Behavioral models capture drivers’ responses to the tolls in terms of trip cancellation and choices of mode, route and departure time. Experiments on the real-world Expressway and Major Arterials network of Singapore demonstrate improved effectiveness of distance-based toll optimization given tolling zone definitions derived from feature-variant clustering, compared to fixed cordon-based pricing, adaptive cordon-based pricing, as well as distance-based pricing with ad hoc tolling zone definitions. Further, the results indicate that the use of the marginal link cost tolls as a clustering feature produces the most robust tolling zone definitions and yields significant improvements in social welfare over ad hoc zone definitions and cordon-pricing. Finally, experiments on the Boston CBD network also demonstrate the effectiveness of distance-based toll optimization schemes on urban traffic networks.