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The Development of Augmented Vehicle Pedestrian Connection for Decision-Making in Autonomous Driving and Pedestrian Safety

Status: Complete

Lead Researcher(s)

Bochen Jia
Assistant Professor of Industrial and Manufactuing Systems Engineering, College of Engineering and Computer Science, The University of Michigan-Dearborn

Yi Lu Murphey
Associate Dean for Graduate Education and Research and Professor of Electrical and Computer Engineering, College of Engineering and Computer Science, The University of Michigan-Dearborn

Weidong Xiang
Professor of Electrical and Computer Engineering, College of Engineering and Computer Science, The University of Michigan-Dearborn

Shan Bao
Associate Professor of Industrial and Manufacturing Systems Engineering, College of Engineering and Computer Science, the University of Michigan-Dearborn, Associate Research Scientist, Human Factors, University of Michigan Transportation Research Institute and Intermittent Lecturer in Industrial and Operations Engineering, College of Engineering

Project Team

Project Abstract

Explored practical solutions to improving the efficiency and accuracy of autonomous vehicle decision-making and pedestrian’s safety through
the development of vehicle-pedestrian integration system. Developed a practical system to increase pedestrian positioning accuracy.

1. Developed a human factor-based big data analytic method to classify the pedestrian behavior.
2. Developed a zone model to detect pedestrian vehicle interaction threshold.
3. Completed field tests to evaluate the existing hardware capacity and proposed system.

Project Outcome

1. An advanced pedestrian positioning system that can be attached to personal wearable devices.
2. An algorithm to classify pedestrian behavior.
3. An algorithm to identify effective range for pedestrian-vehicle interaction.
4. A complete V2P system (at pedestrian end).


BUDGET YEAR: 2016-05-01
IMPACT: SAFETY
RESEARCH CATEGORY: SIMULATION & TESTING