共享自动驾驶汽车使用意愿模型及其影响因素

为了构建共享自动驾驶汽车(shared autonomous vehicles，SAV) 的使用意愿模型并分析其影响因素，通过使用时机和使用频率来体现公众对SAV的使用意愿；采用验证性因子分析将态度潜变量转化为潜变量得分，以此将态度潜变量引入传统的有序Logit模型；提出SAV使用意愿的有序Logit模型构建方法，并建立基于个人属性、通勤特征、态度潜变量的SAV使用意愿模型.研究发现:是否使用过滴滴拼车、工作单位停车费、自动驾驶态度对使用时机和3种价格(1，2，3元/km) 下的使用频率有显著影响；使用过滴滴拼车、工作单位收取停车费、支持自动驾驶的群体倾向于频繁地、更早地使用SAV出行；公众期望以1元/km或 2元/km即不超过目前滴滴拼车的价格使用SAV.

Use Intention Model of Shared Autonomous Vehicles and Its Impact Factors

In order to construct the use intention model of shared autonomous vehicles(SAV) and analyze its impact factors， use timing and use frequency were used to reflect the use intention for SAV. The attitude latent variables were converted into scores using confirmatory factor analyses and they were introduced into the traditional ordered Logit model. The method of modeling SAV use intention by using the ordered Logit models was proposed. Taking personal attributes， commuting characteristics and attitude latent variables as explanatory variables， the SAV use intention models were established. The results showed that the factors such as whether or not to use carpooling like Didi， paying parking fees at the work place and autonomous vehicles(AV) attitude have significant impacts on use timing and use frequency at different prices(1，2 and 3 yuan/km); the groups that use carpooling like Didi， pay parking fees at the work place and support AV tend to use SAV more frequently and earlier in future; the publics expect to use SAV at a price lower than the current price of the carpooling， i.e.1 or 2 yuan/km.