CarMA: Towards Personalized Automotive Tuning
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Wireless sensing and actuation have been explored in many contexts, but the automotive setting has received relatively little attention. Automobiles have tens of onboard sensors and expose several hundred engine parameters which can be tuned (a form of actuation). The optimal tuning for a vehicle can depend upon terrain, traffic, and road conditions, but the ability to tune a vehicle has only been available to mechanics and enthusiasts.
CarMA (Car Mobile Assistant) is a system that provides high-level abstractions for sensing automobile parameters and tuning them. Using these abstractions, developers can easily write smartphone "apps" to achieve fuel efficiency, responsiveness, or safety goals. Users of CarMA can tune their vehicles at the granularity of individual trips, a capability we call personalized tuning.
By developing route and driver-specific customizations, applications can use CarMA to increase fuel efficiency as well as to improve user satisfaction by increasing responsiveness when necessary, and promoting vehicular safety by appropriately limiting the range of performance available to novice or unsafe drivers.
Further Reading
Tobias Flach, Nilesh Mishra, Luis Pedrosa, Christopher Riesz, and Ramesh Govindan; CarMA: Towards Personalized Automotive Tuning. In Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems. 2011
Tobias Flach, Nilesh Mishra, Luis Pedrosa, Christopher Riesz, and Ramesh Govindan; CarMA: Towards Personalized Automotive Tuning. Technical Report 11-921, University of Southern California, Computer Science Department. 2011
People
- Tobias Flach (USC)
- Nilesh Mishra (USC)
- Luis Pedrosa (USC)
- Yurong Jiang (USC)
- Hang Qiu (USC)
- Matthew McCartney (USC)
- Ramesh Govindan (USC)