Maximizing Network Throughput under Stochastic User Equilibrium with Elastic Demand

Most of the existing studies adopt the fixed-demand equilibrium formulation to model drivers’ route choice when studying network throughput maximization problem. Travelers’ reactions to the increased origin-destination (O-D) travel cost and network congestion level are less considered in the problem. Note that travelers can cancel the trip or use other modes to travel if the road network is congested. This study aims to address this gap by analyzing the maximum network throughput problem using the formulation of Logit-based SUE with elastic demand (SUEED). The Logit-based SUEED problem not only models the drivers’ route choice according to the SUE principle, but also estimates the equilibrium O-D demand by factoring the effect of expected perceived O-D travel time on O-D demand. A bi-level programming problem is proposed to characterize the maximum network throughput based on the Logit-based SUEED problem. The sensitivity analysis for the Logit-based SUEED problem is presented and incorporated into the solution algorithm for the proposed problem. A numerical example demonstrates the effectiveness of the proposed sensitivity-based solution algorithm. This study finds that under the SUEED condition, the maximum network throughput decreases monotonically when travelers’ knowledge level of traffic conditions increases (less travel time perception error). It implies that promoting advanced traveler information system ATIS may not serve to foster more number of trips by travelers and make more use of physical network capacity.

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