Alternate traffic restriction (ATR) schemes manage traffic congestion by prohibiting a proportion of cars from entering a predetermined ATR area during specific time periods. Under the ATR scheme, Park-and-Ride (P&R) often becomes more popular as travelers can park cars at P&R facilities and avoid driving into the ATR area. This paper proposes a multi-objective bi-level model that jointly optimizes the P&R facility locations and the ATR scheme (the ATR areas and the proportion of restricted private cars). The upper-level model minimizes the total travel cost and total emission cost, and maximizes consumer surplus. The lower-level model characterizes the user equilibrium of travel modes and route choices. The non-dominated sorting genetic algorithm is adapted to solve the proposed multi-objective bi-level model, where a gradient project algorithm is used for solving the lower-level model. Numerical studies are conducted to test and illustrate the applicability of the model and algorithms.
- alternate traffic restriction
- bi-level programming
- multi-objective optimisation
- Park-and-ride location
ASJC Scopus subject areas