A cloud-assisted design for autonomous driving
Author(s)Suresh Kumar, Swarun; Gollakota, Shyamnath; Katabi, Dina
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This paper presents Carcel, a cloud-assisted system for autonomous driving. Carcel enables the cloud to have access to sensor data from autonomous vehicles as well as the roadside infrastructure. The cloud assists autonomous vehicles that use this system to avoid obstacles such as pedestrians and other vehicles that may not be directly detected by sensors on the vehicle. Further, Carcel enables vehicles to plan efficient paths that account for unexpected events such as road-work or accidents. We evaluate a preliminary prototype of Carcel on a state-of-the-art autonomous driving system in an outdoor testbed including an autonomous golf car and six iRobot Create robots. Results show that Carcel reduces the average time vehicles need to detect obstacles such as pedestrians by 4.6x compared to today's systems that do not have access to the cloud.
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Proceedings of the first edition of the MCC workshop on Mobile cloud computing - MCC '12
Association for Computing Machinery
Kumar, Swarun, Shyamnath Gollakota, and Dina Katabi. “A Cloud-Assisted Design for Autonomous Driving.” Proceedings of the First Edition of the MCC Workshop on Mobile Cloud Computing - MCC ’12 (2012). August 17, 2012, Helsinki, Finland. ACM (2012).
Author's final manuscript