[Purposes] The paper aims to reduce the commuting risk of car?free employees and improve commuting efficiency. [Methods] First, taking the largest number of people participating in carpooling as the first optimization goal, and the minimum commuting carpooling time as the second optimization goal, and considering factors such as the rated passenger capacity of the vehicle, staff working time restrictions and detour time, constructing a unit commuter carpooling vehicle path optimization model. Then, based on the genetic algorithm, the optimal ride?sharing path is solved. Finally, the case analysis, parameter sensitivity analysis and impact analysis of employees' residence dispersion degree are carried out. [Findings] The average commuting time of employees in carpooling is reduced by 24.77 minutes compared with non?carpooling employees, and the matching success rate of carpooling has reached 97.14%. The number of carpooling groups and the car ownership rate of employees have a great impact on the carpooling effect within a certain range. And the carpooling efficiency is better when employees live in concentrated locations. [Conclusions] Carpooling can effectively provide commuting assistance for car?free employees and reduce employees' commuting time.