Litcius/Paper detail

Oops! It's Too Late. Your Autonomous Driving System Needs a <i>Faster</i> Middleware

Tianze Wu, Baofu Wu, Sa Wang, Liangkai Liu, Shaoshan Liu, Yungang Bao, Weisong Shi

2021IEEE Robotics and Automation Letters20 citationsDOI

Abstract

Autonomous Driving (AD) has entered a period of rapid development in recent years. With the amount of sensors and control logics installed increasing tremendously to guarantee robustness, a big challenge is posed for AD middleware. Both the academia and the industry are eager for an investigation of the performance of middlewares in Autonomous Driving Vehicles (AVs). To fill this gap, we summarize typical communication scenarios of AVs and evaluate different communication mechanisms of three popular open-source middlewares comprehensively. Besides, we construct a benchmark pack named ComP which consists of a perception communication scenario and a group of real AD applications for researchers to assess middleware performance. Our findings provide useful guidelines for researchers and insightful optimization advice for designing middlewares.

Topics & Concepts

Middleware (distributed applications)Computer scienceRobustness (evolution)Benchmark (surveying)Construct (python library)PerceptionDistributed computingComputer networkBiochemistryGeodesyChemistryGeographyNeuroscienceGeneBiologyAutonomous Vehicle Technology and SafetyVehicular Ad Hoc Networks (VANETs)Context-Aware Activity Recognition Systems