基于订单数据的新能源出租车出行需求影响因素分析OA

[Background]As the global energy structure transforms and the"dual carbon"strategy gains traction,new-energy taxis have emerged as an essential component of low-carbon transporta-tion systems.However,current studies on taxi order demand lack detailed distinctions among vehicle types,resulting in insufficient influencing mechanisms of order demand for new-energy taxis.[Method]An MDCEV model of new-energy taxi order demand was developed using medium-dis-tance travel as a benchmark to quantify how socioeconomic,built environment,and transportation network attributes shape short-and long-distance demand during peak periods,allowing for more tar-geted operational strategies and planning decisions.[Data]Real-world operational data for new-ener-gy taxis in Tianjin were used to cover various time periods,trip distances,and multidimensional envi-ronmental variables.[Result]Long-distance orders showed the highest saturation threshold during peak periods:high housing prices increased short-distance demand,while high population density de-creased long-distance orders.Points of interest(POI)such as charging stations and medical facilities,boosted short-distance trips,while office POI reduced long-distance demand during weekend peaks.Distance from the city center positively correlated with short-distance trips,whereas road density negatively affected long-distance trips.[Conclusion]The impact of various factors on new energy taxi travel demand varies significantly based on the time of day and trip distance.[Application]This paper can provide scientific support for targeted operational strategies for new-energy taxis and ur-ban transport planning,with the aim of promoting sustainable green mobility.