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.

中文翻译：

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基于环境平衡策略和用户利益导向的通勤拼车服务模式

除了省钱和提供便利外，拼车还能为社会带来环境效益；因此，促进和改善日常拼车服务非常重要。然而，一些与拼车匹配率和环境保护相关的冲突一直在影响用户满意度。为拓宽拼车服务范围，提高服务灵活性，开发了以环境和用户利益为导向的拼车服务模式，包括混合用户群体、不同用户类型、多始发地和目的地对、时间窗口和用户态度，并考虑成本和用户的时间效率要求，以保证个人利益，提供更合理的匹配。建立了一个 0-1 非线性优化模型来描述该模型，并建立了一种基于邻近匹配原理的改进遗传算法，旨在寻找最优解。最后，通过成都市的案例模拟，验证了所提出模型的有效性以及不同用户态度对碳排放和匹配率的影响，从中发现所提出的拼车模式能够提供更系统的拼车计划，避免因时间和效率损失而导致的潜在错配增加的碳排放，并保证最大的社会效益。