Optimization of the Replacement of Self-driving Bus Fleets based on Heuristic Algorithm

Abstract:
With the gradual introduction of self-driving technology into the public transport system, the gradual replacement of regular bus to self-driving bus has become inevitable. In order to solve the problem of bus fleet replacement, analyze the impact of financial subsidy policy on bus team automation, this paper considers the financial subsidy and self-driving bus group variable, capacity control and other factors, with the minimum life cycle cost of bus fleet as the optimization goal, establish the mixed integer planning model of bus team replacement, and use CPLEX software to solve the model, to obtain the best and most accurate solution. Taking the 2019 Beijing No. 651 bus team as an example, the optimal vehicle acquisition scheme and vehicle phase-out scheme are obtained. The results show that financial subsidies promote the automation of public transport.