公共卫生事件持续期通勤合乘设计及组织效率影响分析

为探究城市公共卫生事件下，考虑特殊时期的交通服务需求，通勤合乘模式解决通勤出行的可行性及组织效率，以2020年新型冠状病毒感染的肺炎（新冠肺炎）疫情为背景，基于疫情期乘客出行偏好网络问卷调研数据，分析民众出行偏好及对不同出行模式的暴露风险感知。意愿调研显示，71%的私家车主及无私家车群体均对与同单位人员发生合乘有较高的参与意愿，60%的私家车主表示愿意提供合乘服务，73%的无私家车通勤人群表示愿意接受合乘服务。在单位层面组织通勤合乘，有需求、有条件、有基础，具有良好可行性。以问卷数据为基础构建二元Logit模型对合乘出行驱动因素影响分析，研究发现疫情持续期出行者对交通方式主观感知风险将对合乘选择行为影响较为显著。结合出行群体在疫情持续期的交通方式选择偏好，提出基于健康管理的通勤合乘组织设计的公益互助、安心、用户群体固定、预约共享、合乘人数控制原则和服务水平要求。通过不同场景下合乘仿真，对该模式的预期效率进行解析，得出由单位组织的通勤合乘模式相较商业顺风车而言，前者“N对1”的配对需求与后者“N对N”配对相比，大幅提高了配对成功率。在不同拥车率条件下，存在一个成行率较高的合理员工规模，且该合理规模不是很大。员工住地较为分散的成行率均低于住地聚集场景，当拥车率达到65%的水平时，不论员工住地分布集聚还是分散，均可达到较高的成行率。面对公共卫生事件持续期，探索通过城市交通组织模式创新来破解通勤的流动需求与风险管控难题，为城市治理提供参考。

Impact Analysis of Commuting Rideshare Design and Organizational Efficiency During Public Health Emergencies

To explore the feasibility and organizational efficiency of applying ridesharing to commutes during public health emergencies, this study analyzed the public's willingness and perception of the exposure risks of different travel modes based on an online questionnaire for passenger travel preferences during COVID-19. The survey shows that approximately 71% of both car owners and car-free groups have a high willingness to share rides with people from the same company. 60% of car owners are happy to offer rideshare services, while 73% of car-free employees show a willingness to join a carpool. Utilizing ridesharing in company is feasible and available, with proper demand and foundation. A study on the driving factors behind ridesharing based on a questionnaire and binary logit model shows that a traveler's subjective perception of travel mode risk has a significant influence on the rideshare choice. Considering the travel mode preferences of groups during COVID-19, this paper proposes the principles of mutual benefit, reassurance, shared appointments, shared ridership control, and requirements for levels of service based on the health management of the rideshare commuting mode. Through simulations of carpooling in different scenarios, the expected efficiency of the mode was analyzed. Compared to the “N to N” pairing in commercial ridesharing, the “N to 1” pairing in the commuting rideshare mode organized by the company greatly improved the efficiency. For different rates of car ownership, there generally exists a proper staff size, usually not large, corresponding to an optimum pairing rate. The pairing rate in distributed residences is lower than that in concentrated residences. When the car ownership rate reaches 65%, the pairing rate can be high in both distributed and concentrated residences. During public health emergencies, exploring urban transportation innovations to solve commuting mobility needs as well as risk management and control will provide a reference for resilient urban governance.