Integrating congestion pricing and transit investment planning
economics - value of time, economics - pricing, policy - congestion, planning - service improvement, ridership - behaviour
Congestion pricing, Bi-level optimization, User equilibrium, Transit headway reduction
This paper develops a mathematical model and solution procedure to identify an optimal zonal pricing scheme for automobile traffic to incentivize the expanded use of transit as a mechanism to stem congestion and the social costs that arise from that congestion. The optimization model assumes that there is a homogenous collection of users whose behavior can be described as utility maximizers and for which their utility function is driven by monetary costs. These monetary costs are assumed to be the tolls in place, the per mile cost to drive, and the value of their time. We assume that there is a system owner who sets the toll prices, collects the proceeds from the tolls, and invests those funds in transit system improvements in the form of headway reductions. This yields a bi-level optimization model which we solve using an iterative procedure that is an integration of a genetic algorithm and the Frank–Wolfe method. The method and solution procedure is applied to an illustrative example.
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Chen, R., & Nozick, L. (2016). Integrating congestion pricing and transit investment planning. Transportation Research Part A: Policy and Practice, Vol. 89, pp. 124–139.