Stochastic User Equilibrium with Endogenous Dynamic Charging Pricing and Heterogeneous Preferences
Abstract
: The rapid growth of electric vehicles (EVs) has made the spatial allocation of charging demand a critical operational challenge in urban networks. Effective pricing mechanisms must account for heterogeneous user preferences, road congestion, and charging-station capacity limits. This paper proposes a stochastic user equilibrium framework with endogenous dynamic charging pricing for a traffic-charging network. Charging prices combine an exogenous base electricity price with an endogenous, capacity-induced premium, so that prices respond dynamically to local charging congestion. Electricity supply enters only through charging-station capacity limits and base electricity prices, consistent with capacity-constrained charging infrastructure. EV users are classified into four groups according to trip purpose and behavioral objective. A heterogeneous stochastic user equilibrium model is then formulated using the multinomial Logit choice rule to describe differentiated travel and charging decisions. The equilibrium conditions are reformulated as a mixed complementarity problem, enabling a unified solution for multi-group route choice, demand conservation, and capacity-constrained endogenous pricing. Numerical experiments on a 12-node traffic-charging hybrid network demonstrate that the proposed mechanism provides self-adaptive spatial regulation. Under low-load conditions, all shadow prices remain zero and user choices are not disturbed. Under medium-load conditions, a shadow price of 0.61 CNY/kWh activates only at the bottleneck station. Under high-load conditions, shadow prices of 1.16–3.32 CNY/kWh activate at three stations in proportion to congestion severity. The results confirm that heterogeneous user groups respond differently to price signals, bounded rationality prevents infeasible demand concentration, and capacity investment and price regulation function as complementary instruments within the unified equilibrium framework.