Unleashing the potential of price-based congestion management schemes: a unifying approach to compare alternative models under multiple objectives

A wide range of price-based congestion management schemes were proposed in the literature ranging from marginal cost road pricing to trip based multimodal pricing. The underlying models were formulated under different theoretical assumptions and with varying, and sometimes conflicting objectives. This paper presents a unifying framework under which different approaches can be compared based on their respective assumptions. The unifying modelling framework is referred to as trip pricing model, which extends path-differentiated pricing to multimodal paths, i.e., trips on whatever mode or combinations of modes, and generalizes road pricing schemes (which are shown to be a special case). By setting both positive (tolls) and negative (incentives) prices, revenue-neutral schemes are also shown to be special cases, with no a-priori assumption on which paths/modes to toll/incentivize. For model comparison, the pricing design problem is formulated in a multi-objective optimization framework, which combines traffic efficiency, environmental sustainability, users' acceptance, social and spatial equity, as pricing objectives. The trip pricing scheme is compared with traditional road pricing schemes, and with their revenue-neutral variants. First-best and second-best pricing schemes, designed in single- and multi-objective optimization frameworks, are compared on the Nguyen-Dupuis network. Results suggest a vast potential for multi-objective trip congestion pricing over single-objective road pricing. In addition, the application of both positive and negative prices is shown to significantly increase the expected acceptance of pricing schemes and to preserve efficiency and sustainability objectives. The results should promote the design of more effective pricing policies, i.e., set of pricing rules easier to communicate, based on now available technologies of passengers' tracking and pricing.