CarSpeak: a content-centric network for autonomous driving

  • Authors:

  • Swarun Kumar;Lixin Shi;Nabeel Ahmed;Stephanie Gil;Dina Katabi;Daniela Rus

  • Affiliations:

  • Massachusetts Institute of Technology, Cambridge, MA, USA;Massachusetts Institute of Technology, Cambridge, MA, USA;Massachusetts Institute of Technology, Cambridge, MA, USA;Massachusetts Institute of Technology, Cambridge, MA, USA;Massachusetts Institute of Technology, Cambridge, MA, USA;Massachusetts Institute of Technology, Cambridge, MA, USA

  • Venue:
  • ACM SIGCOMM Computer Communication Review - Special october issue SIGCOMM '12
  • Year:
  • 2012

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Abstract

This paper introduces CarSpeak, a communication system for autonomous driving. CarSpeak enables a car to query and access sensory information captured by other cars in a manner similar to how it accesses information from its local sensors. CarSpeak adopts a content-centric approach where information objects -- i.e., regions along the road -- are first class citizens. It names and accesses road regions using a multi-resolution system, which allows it to scale the amount of transmitted data with the available bandwidth. CarSpeak also changes the MAC protocol so that, instead of having nodes contend for the medium, contention is between road regions, and the medium share assigned to any region depends on the number of cars interested in that region. CarSpeak is implemented in a state-of-the-art autonomous driving system and tested on indoor and outdoor hardware testbeds including an autonomous golf car and 10 iRobot Create robots. In comparison with a baseline that directly uses 802.11, CarSpeak reduces the time for navigating around obstacles by 2.4x, and reduces the probability of a collision due to limited visibility by 14x.