Development of Dynamic Network Traffic Simulator for Mixed Traffic Flow Under Connected and Autonomous Vehicles

Principal Investigator(s):

Srinivas Peeta, Hockema Professor of Civil Engineering – Purdue University

Project Abstract:
Phase 1: The advent of connected and autonomous vehicles (CAVs) will generate changes that have the potential to enhance network capacity, reduce congestion, and increase safety. While several studies have examined the potential impact of CAVs on the driving environment, there is the key need for modeling approaches that can characterize network-level evolution of traffic flow dynamics and the impacts on stability under mixed traffic streams of human-driven vehicles and CAVs. There is the need for a comprehensive traffic flow modeling framework that incorporates different levels of connectivity and automation as well as different market penetration rates. This study will develop a unified car-following modeling framework that models mixed traffic streams under different market penetration rates of CAVs. It will also perform stability analyses to explore implications for safety and mobility.

Phase 2: Connected and autonomous vehicles (CAVs) will generate a revolution in the transportation system, with great potential to improve traffic safety, efficiency, and environmental sustainability. However, the transition to CAVs will occur over time and, during it, CAVs will coexist with human- driven vehicles (HDVs), connected vehicles (CVs) and autonomous vehicles (AVs) in the traffic flow. While several studies have examined the potential impact of AVs, CVs and CAVs on the driving environment, there is a key need for modeling approaches that can characterize network level evolution of traffic flow dynamics and their impacts on stability under mixed traffic streams. There is the need for a comprehensive traffic flow modeling framework that incorporates different levels of connectivity and automation as well as different market penetration rates. This study will develop a unified traffic flow modeling framework that models mixed traffic streams under different market penetration rates of AVs, CVs and CAVs. It will also perform stability analyses to explore implications for safety and mobility.

Institution(s): Purdue University

Award Year: 2017

Research Thrust(s): Control & Operations

Project Form(s):