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Dynamic Map Update Using Connected Vehicle Data

Status: Complete

Lead Researcher(s)

Henry Liu
Professor of Civil and Environmental Engineering, College of Engineering and Research Professor, Engineering Systems, University of Michigan Transportation Research Institute-Administration

Project Team

Project Abstract

To develop a system that can utilize connected vehicle (CV) data collected by the roadside equipment (RSE) to automatically and dynamically update geometric intersection description (GID) map at lane level, in order to support various CV applications and automated vehicle technology. We will leverage our experience from a recent research project funded by Crash Avoidance Metrics Partnership(CAMP), titled“Automatic Intersection Map Generation”to develop estimation algorithms to dynamically detect temporary lane closure and modification and to dynamically update GID map. A statistical approach will be developed to monitor lane occupancies and traffic speeds, and detect abnormal traffic patterns, and then estimate traffic lane closures and modification. The estimation algorithm will be integrated in the Connected Vehicle based ControllerInterface Device (CV-CID) developed by the project team to interface with RSEs. A central software will also be developed and deployed in Mcity traffic management center to visualize dynamic map and related information of incidents, e.g. accident, game event or road work.

Project Outcome

To develop a system that can utilize connected vehicle (CV) data collected by the roadside equipment (RSE) to automatically and dynamically update geometric intersection description (GID) map at lane level, in order to support various CV applications and automated vehicle technology.


BUDGET YEAR: 2016-05-01
IMPACT: EFFICIENCY