02015nas a2200253 4500008004100000245009900041210006900140250000700209260003000216520122200246653002401468653001901492653001501511653001201526100001901538700002101557700002201578700002201600700001501622700002301637700002301660700002101683856005701704 2019 eng d00aReal-Time Distance Estimation and Filtering of Vehicle Headways for Smoothing of Traffic Waves0 aRealTime Distance Estimation and Filtering of Vehicle Headways f a10 aMontreal, Canadac04/20193 a
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.
10aautonomous vehicles10aDigital Filter10asimulation10aTraffic1 aBhadani, Rahul1 aBunting, Matthew1 aSeibold, Benjamin1 aStern, Raphael, E1 aCui, Shumo1 aSprinkle, Jonathan1 aPiccoli, Benedetto1 aWork, Daniel, B. uhttps://dl.acm.org/citation.cfm?doid=3302509.331402602161nas a2200205 4500008004100000245009600041210006900137260004100206490000700247520150000254653002401754653000801778653001201786100001901798700002301817700002201840700002301862700002101885856004901906 2018 eng d00aDissipation of Emergent Traffic Waves in Stop-and-Go Traffic Using a Supervisory Controller0 aDissipation of Emergent Traffic Waves in StopandGo Traffic Using aFontainbleau, Miami Beach, USAbIEEE0 v573 a
This paper presents the use of a quadratic band controller in an autonomous vehicle (AV) to regulate emergent traffic waves resulting from traffic congestion. The controller dampens the emergent traffic waves through modulating its velocity according to the relative distance and velocity of the immediately preceding vehicle in the flow. At the same time, it prevents any collision within the range specified by the design parameters. The approach is based on a configurable quadratic band that allows smooth transitions between (i) no modification to the desired velocity; (ii) braking to match the speed of the preceding vehicle; and (iii) braking to avoid collision with the lead vehicle. By assuming that the lead vehicle's velocity will be oscillatory, the controller's smooth transition between modes permits any vehicle following the AV to have a smoother reference velocity. The configurable quadratic band allows design parameters, such as actuator and computation delays as well as the dynamics of vehicle deceleration, to be taken into account when constructing the controller. Experimental data, software-in-the-loop distributed simulation, and results from physical platform performance in an experiment with 21 human-driven vehicles are presented. Analysis shows that the design parameters used in constructing the quadratic band controller are met, and assumptions regarding the oscillatory nature of emergent traffic waves are valid.
10aautonomous vehicles10aCPS10aTraffic1 aBhadani, Rahul1 aPiccoli, Benedetto1 aSeibold, Benjamin1 aSprinkle, Jonathan1 aWork, Daniel, B. uhttps://ieeexplore.ieee.org/document/861970000954nas a2200301 4500008004100000020002200041245010200063210006900165260002700234300001000261653002400271653001700295100002100312700002200333700001500355700002100370700001500391700002100406700002200427700002300449700001900472700002100491700002300512700003100535700002400566700001500590856004700605 2017 eng d a978-1-4503-4976-500aControlling for Unsafe Events in Dense Traffic Through Autonomous Vehicles: Invited Talk Abstract0 aControlling for Unsafe Events in Dense Traffic Through Autonomou aNew York, NY, USAbACM a7–710aSugiyama experiment10aTraffic flow1 aWork, Daniel, B.1 aStern, Raphael, E1 aWu, Fangyu1 aChurchill, Miles1 aCui, Shumo1 aPohlmann, Hannah1 aSeibold, Benjamin1 aPiccoli, Benedetto1 aBhadani, Rahul1 aBunting, Matthew1 aSprinkle, Jonathan1 aMonache, Maria, Laura Dell1 aHamilton, Nathaniel1 aHaulcy, R. uhttp://doi.acm.org/10.1145/3055378.3055380