Abstract
Uncertainty, a critical factor of causing congestion and extra travel costs in the commute, can be mitigated by providing information. This paper studies the welfare effects of accurate pre-trip information on departure time and route choices in the morning commute under binary stochastic bottleneck capacity. We consider a classical two-route network. Each route has a single bottleneck where congestion occurs during the rush hours. The two routes’ bottleneck capacities vary from day-to-day due to events such as bad weather, accidents, and temporary road closures. We derive all equilibrium solutions in consideration of the differences between routes in free-flow travel time, the shadow value of travel time, the severity of bottleneck capacity reductions, and the degree of correlation between two routes in travel conditions. Furthermore, we investigate the benefit changes from zero-information to full-information and prove that accurate pre-trip information about the bottleneck conditions is strictly welfare-improving. Finally, these theoretical results are supplemented by case studies that show examples of benefit gains from pre-trip information.
Highlights
Traffic congestion occurs when traffic demand exceeds road capacity and produces many negative impacts such as travel delay, excess greenhouse gas (GHG) emissions, and road rage [1]–[3]
We investigate the effects of accurate pre-trip information on departure time and route choices under binary stochastic bottleneck capacity and find that accurate pre-trip information is strictly welfare-improving
We find that the travel costs caused by the free-flow travel cost difference between the two routes depend on the shadow value of travel time, but they relate to the shadow values of schedule early and delay time (β and γ) in the two regimes
Summary
Traffic congestion occurs when traffic demand exceeds road capacity and produces many negative impacts such as travel delay, excess greenhouse gas (GHG) emissions, and road rage [1]–[3]. Arnott et al [32] studied the effects of information on departure time and route choices under stochastic bottleneck capacity They found if there are a random number of commuters, both perfect and noisy information might increase travel costs in contrast to no information. We study the effects of accurate pre-trip information on commuters’ departure time and route choices under binary stochastic bottleneck capacity. To this end, we consider a classical one origin-destination (OD) pair with two routes and two bottlenecks, a network commonly used in these studies.
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