Human-centred design of next generation transportation infrastructure with connected and automated vehicles: a system-of-systems perspective

Abstract

During the transition period when connected and automated vehicles (CAVs) and human-driven vehicles (HDVs) coexist on the roadway, miscommunication and improper interactions may lead to accidents due to lack of awareness of each other’s intentions. The most promising approach to this problem is to view roadway transportation as a cyber-physical-social system consisting of CAV, HDV, and infrastructure subsystems. Although adaptations of infrastructure are as critical as the technological advances of vehicles, the role of infrastructure in CAV and HDV interactions has not been fully acknowledged. We consider the roadway transportation system from the system-of-systems perspective, taking a human-centred approach that integrates the behaviours of human drivers and CAVs with the design and enhancement of transportation infrastructure. We provide an overview of prior studies regarding information-processing and communication of the subsystems. Interactions between HDVs and infrastructure are summarised by human driving behaviours and HDV crash analysis. Interactions between HDVs and CAVs focus on how they perceive and predict actions of each other. Interactions between CAVs and infrastructure are characterised by possible adaptations of infrastructure to support CAV navigation. Lastly, we propose a human-centred framework to provide guidance for research on and design of next-generation transportation infrastructure with CAVs and HDVs.

Relevance to human factors/ergonomics theory

Implementation of CAVs on the roadways with HDVs requires a system-of-systems approach that includes the CAVs, HDVs, and transportation infrastructure. Humans must be at the center of this approach because their actions are central to the success of the entire system.

Keywords:

• Autonomous vehicles
• driverless vehicles
• mixed traffic
• roadway infrastructure

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 https://www.dmv.ca.gov/portal/vehicle-industry-services/autonomous-vehicles/autonomous-vehicle-collision-reports/

Additional information

Funding

This research was supported in part by the U.S. National Science Foundation through Grant EAGER SAI #2121967. The views presented in this paper are those of the authors alone.

Notes on contributors

Yiheng Feng

Yiheng Feng is Assistant Professor of Civil Engineering, Purdue University.

Yunfeng Chen

Yunfeng Chen is Assistant Professor of Construction Management Technology, Purdue University.

Jiansong Zhang

Jiansong Zhang is Assistant Professor of Construction Management Technology, Purdue University.

Chi Tian

Chi Tian is a PhD candidate in Construction Management Technology, Purdue University.

Ran Ren

Ran Ren is a PhD student in Construction Management Technology, Purdue University.

Tianfang Han

Tianfang Han is a PhD student in Cognitive Psychology, Purdue University

Robert W. Proctor

Robert W. Proctor is Distinguished Professor of Psychological Sciences, Purdue University.