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.

CarSpeak: A Content-Centric Network for Autonomous Driving
Swarun Kumar, Lixin Shu, Stephanie Gil, Nabeel Ahmed, Dina Katabi, and Daniela Rus
ACM SIGCOMM, 2012.  PDF     SLIDES

A Cloud-Assisted Design for Autonomous Driving
Swarun Kumar, Shyamnath Gollakota, and Dina Katabi
MCC Workshop 2012 (SIGCOMM), 2012.  PDF     SLIDES

Swarun Kumar
Massachusetts Institute of Technology

Lixin Shi
Massachusetts Institute of Technology

Nabeel Ahmed
Massachusetts Institute of Technology

Stephanie Gil
Massachusetts Institute of Technology

Dina Katabi
Massachusetts Institute of Technology

Daniela Rus
Massachusetts Institute of Technology