论文标题
最近合并乘车公司后,探索慕尼黑市运输模式的偏好
Exploring Preferences for Transportation Modes in the City of Munich after the Recent Incorporation of Ride-Hailing Companies
论文作者
论文摘要
在过去的几年中,骑车公司(RH)公司的增长以多种方式影响了城市流动性。尽管对此类服务的好处有广泛的说法,但对该主题进行了有限的研究。本文评估了慕尼黑运输用户支付RH服务的意愿。意识到直接从RH公司获得数据的困难,设计了一项既定的偏好调查。该数据集包括来自500名通勤者的响应。在8公里的旅行方案中,使用RH服务及其类似模式(自动和运输)在8公里的旅行方案中,社会人口统计学属性,当前的旅行行为和运输模式偏好被收集。使用多项式logit模型来估计跨收入组使用RH服务的时间和成本系数,然后用来估计RH的时间价值(fot)。该模型的结果表明,在18至39岁,大型家庭和较少汽车的家庭中,RH服务的受欢迎程度。收入较高的群体还愿意为使用RH服务支付更多费用。为了检查RH服务对慕尼黑市模态拆分的影响,我们使用增量logit将RH作为新模式纳入了现有的嵌套logit模式选择模型。旅行时间,旅行成本和投票被用作通勤者在RH和其最接近的Metro之间进行选择时做出的选择的措施。总共在四个不同的拥塞水平和四个价格水平上评估了20个方案,以反映可接受的成本和时间权衡的需求。
The growth of ridehailing (RH) companies over the past few years has affected urban mobility in numerous ways. Despite widespread claims about the benefits of such services, limited research has been conducted on the topic. This paper assesses the willingness of Munich transportation users to pay for RH services. Realizing the difficulty of obtaining data directly from RH companies, a stated preference survey was designed. The dataset includes responses from 500 commuters. Sociodemographic attributes, current travel behavior and transportation mode preference in an 8 km trip scenario using RH service and its similar modes (auto and transit), were collected. A multinomial logit model was used to estimate the time and cost coefficients for using RH services across income groups, which was then used to estimate the value of time (VOT) for RH. The model results indicate RH services popularity among those aged 18 to 39, larger households and households with fewer autos. Higher income groups are also willing to pay more for using RH services. To examine the impact of RH services on modal split in the city of Munich, we incorporated RH as a new mode into an existing nested logit mode choice model using an incremental logit. Travel time, travel cost and VOT were used as measures for the choice commuters make when choosing between RH and its closest mode, metro. A total of 20 scenarios were evaluated at four different congestion levels and four price levels to reflect the demand in response to acceptable costs and time tradeoffs.