Stochastic Ridesharing User Equilibrium with Weibit Choice Model

As one of the most promising travel modes in the modern urban transportation network, ridesharing is widely favored because of its convenience and lower travel costs. In the literature on ridesharing equilibrium modeling, the deterministic user equilibrium (DUE) and logit-based stochastic user equilibrium (SUE) are often adopted in the role choice or route choice. Although SUE models tackle the inability of DUE models that cannot consider perception errors, the logit-based SUE model assumes the perception variance is fixed for all travel modes or travel routes. In order to deal with the homogenous perception variance issue, this study proposes a weibit-based SUE model to characterize the mode choice and route choice in the stochastic ridesharing user equilibrium (SRUE) problem. In the proposed model, we focus on the travelers' conversion among three modes (i.e., solo driver, ridesharing driver, ridesharing passenger) and explicitly consider the relationship between origin-destination (O-D) supply (i.e., the number of ridesharing drivers) and O-D demand (i.e., the number of ridesharing passengers). Moreover, we consider a non-additive path cost function that consists of travel time, monetary cost, ridesharing compensation, a nd/or inconvenient cost in the SRUE problem. We customize a solution framework for solving this novel model efficiently. Numerical examples are conducted to illustrate the applicability of the weibit-based SRUE model.