TY - Generic T1 - Real-Time Distance Estimation and Filtering of Vehicle Headways for Smoothing of Traffic Waves T2 - International Conference on Cyber-Physical Systems 2019 Y1 - 2019 A1 - Rahul Bhadani A1 - Matthew Bunting A1 - Benjamin Seibold A1 - Raphael E Stern A1 - Shumo Cui A1 - Jonathan Sprinkle A1 - Benedetto Piccoli A1 - Daniel B. Work KW - autonomous vehicles KW - Digital Filter KW - simulation KW - Traffic AB -

In this paper, we describe an experience report and field deployment of real-time filtering algorithms used with a robotic vehicle to smooth emergent traffic waves. When smoothing these waves in simulation, a common approach is to implement controllers that utilize headway, relative velocity and even acceleration from smooth ground truth information, rather than from realistic data. As a result, many results may be limited in their impact when considering the dynamics of the vehicle under control and the discretized nature of the laser data as well as its periodic arrival. Our approach discusses trade-offs in estimation accuracy to provide both distance and velocity estimates, with ground-truth hardware-in-the-loop tests with a robotic car. The contribution of the work enabled an experiment with 21 vehicles, including the robotic car closing the loop at up to 8.0 m/s with this filtered estimate, stressing the importance of an algorithm that can deliver real-time results with acceptable accuracy for the safety of the drivers in the experiment.

 

JF - International Conference on Cyber-Physical Systems 2019 CY - Montreal, Canada UR - https://dl.acm.org/citation.cfm?doid=3302509.3314026 ER -