Date of Award
Controller Area Network (CAN), GPS, Intelligent Transport System (ITS), On Board Unit (OBU), Vehicle to Vehicle communications (V2V)
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In this thesis we investigate an alternate source of vehicular information for collision avoidance systems and driver assistance applications, which is more accurate, reliable in all conditions and has minimum time lag. We have designed and developed an architecture, which enables us to read, analyze, decode and store the real-time vehicular data from the vehicle’s electric sensors. We have designed two algorithms for decoding the raw data read from the vehicle’s Controller Area Network (CAN) bus, to which various electric components of the vehicle are connected to communicate the real-time data. We have shown that the vehicular speed which is a very important parameter in the calculation of ‘Time to Collision (TTC)’ by collision avoidance algorithms is more accurate, reliable and has higher polling rate, when calculated from the vehicle’s CAN bus as compare to the other source of information i.e. GPS.
Sood, Gaurav, "Architecture for Extracting Data from Vehicular Sensors" (2015). Electronic Theses and Dissertations. 5514.