Balanced strategy based on environment and user benefit-oriented carpooling service mode for commuting trips

Besides saving money and providing convenience, carpooling can result in environmental benefits to society; therefore, it is important to promote and improve daily carpooling services. However, some conflicts related to carpooling match rates and environmental protection have been influencing user satisfaction. To broaden the carpooling service scope and improve service flexibility, an environment and user benefit-oriented carpooling service model was developed that included mixed user groups, different user types, multiple origin and destination pairs, a time window and user attitudes, and considered the cost and time efficiency requirements of the users to guarantee individual benefits and provide more reasonable matches. A 0–1 nonlinear optimization model was built to describe the model and an improved genetic algorithm based on a nearby matching principle designed to find the optimal solution. Finally, a case simulation from Chengdu city was conducted to demonstrate the effectiveness of the proposed model and the influence of different user attitudes on the carbon emissions and match rates, from which it was found that the proposed carpooling mode was able to provide a more systematic carpooling plan, avoid the increased carbon emissions from potential mismatching due to time and efficiency losses, and guarante the maximum social benefit.