Market diffusion and social influences of automated cars: Integrated approach from traffic engineering and transport economics

2018 Fiscal Year Final Research Report

• Project/Area Number: 17K18949
• Research Category: Grant-in-Aid for Challenging Research (Exploratory)
• Allocation Type: Multi-year Fund
• Research Field: Social systems engineering, Safety engineering, Disaster prevention engineering, and related fields
• Research Institution: Tokyo Institute of Technology
• Principal Investigator: Fukuda Daisuke 東京工業大学, 環境・社会理工学院, 准教授 (70334539)
• Co-Investigator(Kenkyū-buntansha): 瀬尾 亨 東京大学, 大学院工学系研究科(工学部), 助教 (90774779)
• Project Period (FY): 2017-06-30 – 2019-03-31
• Keywords: 自動運転 / 交通工学 / 交通行動分析

Outline of Final Research Achievements

Firstly, we developed a theoretical traffic model that describes physical relationship between market diffusion rate of autonomous vehicles and traffic flow and then conducted some numerical simulations. Some findings are obtained: (1) Autonomous driving does not necessarily mitigate urban traffic congestion; (2) There are some multiple equilibria in the demand-supply interaction between autonomous vehicles and road infrastructure. Next, we empirically investigated the determinants of Japanese usage intention for new transportation services with Fully Autonomous Driving. The survey analysis result implied that the usage intention would be activated by the positive attitude for new products while the tendency toward avoiding general risk would negatively affect the usage intention. Regarding the conditions of other customers sharing the same vehicle, we found that the existence of a few stranger of the same sex would significantly reduce the negative impact of longer travel time.

Free Research Field

交通工学

Academic Significance and Societal Importance of the Research Achievements

前半の理論分析より，自動運転車の普及を検討するにあたっては，短期的な観点から効率性を少し犠牲にして安全性を確保すると，長期的な観点では効率性が大きく損なわれる場合がある可能性が示唆されたことは学術的にも実務的にも有益な知見であると考える．後者の実証分析からは，一般に日本人に対する完全自動運転ライドシェアを含めシェアリングビジネスのハードルが高いとされる中で，どのような心理的要因が利用意向に大きな影響を与えているのかを明らかにしたことは，今後の適切な自動運転車の普及戦略を考える上で有益であると考えられる．