Resources for Automated vehicle data, modelling and control

-- Results from NSF project #1826162 "Understanding the Impacts of Automated Vehicles on Traffic Flow Using Empirical Data" (PIs: Danjue Chen, Jorge Laval)

Introduction

Adaptive Cruise Control (ACC) technology, as a precursor of automated vehicle technology, has been available for over two decades and is now adopted in the car models from more than 20 manufacturers (WIKI). It can be expected that the penetration of ACC vehicles will continue to grow and become very significant, and thus will have profound impacts on the traffic flow. The literature has reported that ACC has the potential to improve traffic flow such as increasing the throughput and improving traffic stability. Notably, most studies that claimed the benefits of ACC on traffic flow were based on simulation outcomes and lacked the empirical ground.

This webpage will serve as a repository for ACC field test data, research outcome, and webinar information, to facilitate research and application of ACC and ultimately automated vehicles.

If you are willing to share your data or to present your research, please contact Dr. Danjue Chen: danjue_chen@uml.edu.

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