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          簡思思: Assessing the economic impacts of labor and leisure time in autonomous vehicles

          發布時間:2019-12-20  

          報告地點:屯溪路校區三立苑331

          :簡思思 助理教授

          報告時間20191225日上午11:00-12:00

          工作單位:香港科技大學

          舉辦單位:汽車與交通工程學院

          報告人簡介:

          簡思思博士本科畢業于中南大學,碩士畢業于新加坡南洋理工大學,博士畢業于新南威爾士大學?,F任香港科技大學土木與環境工程系助理教授。主要從事交通網絡建模和交通行為建模等方面的研究。先后在《Transportation Research Part A》、《Transportation Research Part C》、《Accident Analysis & Prevention》、《Networks and Spatial Economics》等期刊上發表SCI論文10余篇。

          報告簡介

          Previous studies have analyzed the impacts of the introduction of autonomous vehicles on transport networks and estimated the safety, congestion, freight, parking and vehicle ownership impacts to social welfare and the economy. However, there appears to be a gap in the literature on the economic impacts of individuals allocating travel time in an autonomous vehicle to leisure and labor activities. This additional labor time could then have flow-on impacts to productivity and the broader economy. This paper addresses this gap through the development of a novel microeconomic model incorporating time use in autonomous vehicles. The model captures an individual’s consumption behavior, demand for leisure and supply of labor while accounting for the allocation of travel time to labor and leisure. It is an extension of existing microeconomic models of time use for three features: (1) travel utility, (2) mode choice with endogenous value of time, and (3) labor while travelling. A preliminary version of the model is then implemented in an integrated computable general equilibrium and transport model for Sydney, Australia, and is briefly tested to understand the order of magnitude of impacts. From this model, the introduction of autonomous vehicles without travel time allocated to labor and leisure results in a total welfare gain of A$6,274.70 million per year for Sydney residents, and with travel time allocated to labor and leisure, a total welfare gain of A$26,413.63 million per year. Further work is required to finalize the implementation of the model, validate the results and perform sensitivity analyses. 

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