为解决现有定制公交路线规划模型数据来源窄且未充分考虑碳减排需求的问题，首先基于高德地图平台提供的互联网大数据挖掘定制公交潜在客户群体与通勤需求，然后用燃油消耗量表征碳排放量，在考虑乘客利益与公交营运企业利益等约束条件的前提下，以燃油消耗量最少为目标构建定制公交路线规划模型，最后采用遗传算法进行模型求解。针对广州的实例分析结果表明，仅需4台定制公交即可满足早高峰期间1个时段内南往北途经广州大桥的69名来自11个不同小区私家车通勤用户的出行需求，且该方案可在乘客出行时长无显著增长的前提下减少约89.36%的燃油消耗，表明所建模型可有效解决以碳减排为目标的定制公交线路规划问题。

In order to solve the problem of narrow data sources for the existing customized bus route planning model and the lack of consideration for carbon emission reduction, firstly, the potential customer groups and commuting needs of customized buses was explored based on the internet big data provided by Amap. Secondly, fuel consumption was used to characterize carbon emissions, and a customized bus route planning model was constructed with the object of minimum fuel consumption, considering the constraints such as the interests of passenger and bus operators. Finally, the model was solved with genetic algorithm. The results of a case study in Guangzhow showed that, during the morning rush hour, only 4 customized buses were required to meet the travel needs of 69 private car commuters from 11 different communities crossing Guangzhou Bridge from south to north, and the fuel consumption was reduced by 89.36% with no significant increase in passenger travel time, which indicated that the proposed model could effectively solve the problem of customized bus route planning with the target of carbon emission reduction.