Abstract: Urban road congestion and the prevalence of shared concepts have brought the rise of carpooling. Passengers with similar travel routes share the same car, which can increase the vehicle’s seat resources, save costs and relieve traffic pressure. Taking the problem of multi-vehicle static carpooling without transfer with time window constraints as the research background, the objective function of passenger-vehicle matching and path optimization is established from three aspects: vehicle usage fee, travel cost on the way and penalty cost of arrival time window, constructing model constraint conditions based on vehicle capacity, passenger departure and arrival time windows, no detours, no overlap between passenger and vehicle matching, etc. The evolution strategy algorithm is used to solve the problem, and the coding and decoding rules are designed according to the model characteristics. The decoding results can obtain the matching relationship between the vehicle and the passengers and the traveling path at the same time, and the cross-mutation operation is used to update the iterative individual population to obtain the optimal solution. Using MATLAB to solve the calculation example to verify the feasibility of the model and the effectiveness of the algorithm, the results show that the algorithm can quickly respond to the static carpooling problem, and can provide the matching relationship between passengers and vehicles and the path of the vehicle in a short time, the carpooling scheme can save more costs than traveling alone.

Key words: urban traffic, trip matching, route optimization, evolutionary strategy algorithm