Economical Acquisition of Intersection Data to Facilitate CAV Operations

Economical Acquisition of Intersection Data to Facilitate CAV Operations

Headshot of Samuel Labi. The link directs to their bio page.
Samuel Labi
Headshot of James Krogmeier. The link directs to their bio page.
James Krogmeier
Montasir Abbas Headshot. The link directs to their bio page.
Montasir Abbas
Purdue University Logo. The link directs to the funded research led by this institution.

Principal Investigator(s):

Samuel Labi, Professor of Civil Engineering – Purdue University
Director – NEXTRANS
James Krogmeier, Professor of Electrical and Computer Engineering – Purdue University
Montasir Abbas, Professor of Civil Engineering – Virginia Polytechnic Institute & State University

Project Abstract:
Connected and automated vehicles (CAVs) provide an opportunity for improving safety and reducing pollution, energy consumption, and travel delay. Past and ongoing studies are investigating the operations of CAVs at various subsystems of the transportation system, including freeway weaving sections and urban intersections. In order to make operations decisions, however, more cost-effective ways of obtaining and distributing infrastructure data are needed. Unfortunately, existing deployment methods of data collection and delivery are time-consuming and costly. This research is investigating alternative cost-effective ways of collecting intersection data to facilitate traffic operations in the prospective era of CAVs. The research is determining the cost to deploy equipment that will make SPaT and MAP data more likely useful to mobile devices.

Institution(s): Purdue University

Award Year: 2022

Research Thrust(s): Enabling Technology, Infrastructure Design & Management, Modeling & Implementation

Project Form(s):