ABSTRACT

New mobility services, including carsharing and automated vehicles (AVs), are changing mobility. Gathering evidence on the prospective adoption and uncertainty surrounding new technologies is critical, but technological changes outpace the speed with which planners can inform policy. This study demonstrates the feasibility of bridging planners’ programming and experimentation responsibilities in navigating uncertainty by developing forecasting tools which account for new technologies and fuse data from a large-scale Canadian household travel survey, the Transportation Tomorrow Survey (2016), with a one-time, internet-based survey with questions related to new mobility services. This study uses a fused nested logit model to explore the characteristics of consumers with propensities towards AV ownership and carshare membership in the Greater Toronto and Hamilton Area. Findings indicate joint effects of these two technologies. This approach of utilizing smaller-scale, issue-focused surveys in conjunction with traditional regional household travel surveys offers significant potential for planners to prepare more nimbly for uncertainty.

摘要

新的出行服务，包括汽车共享和自动驾驶汽车（AVs），正在改变着出行方式。收集有关新技术可能被采用和不确定性的证据至关重要，但是技术变革的速度超过了计划制定者制定政策的速度。这项研究通过开发预测工具来证明在规划不确定性的过程中架起计划者的编程和实验职责的可行性，该预测工具应解释新技术并融合大型加拿大家庭旅行调查《运输明天调查》（2016年）中的数据，并采用以下方法：时间，基于互联网的调查，涉及与新的出行服务相关的问题。这项研究使用融合的嵌套logit模型来探索在大多伦多地区和汉密尔顿地区倾向于拥有自动驾驶汽车和共享汽车的消费者的特征。研究结果表明了这两种技术的共同作用。这种将小规模，以问题为重点的调查与传统的区域家庭旅行调查相结合的方法，为计划人员提供了更大的潜力，使他们可以更加灵活地为不确定性做准备。