Intervehicle Range Estimation From Periodic Broadcasts

Dedicated short-range communications enables vehicular communication using periodic broadcast messages. We propose to use these periodic broadcasts to perform intervehicle ranging. Motivated by this scenario, we study the general problem of range estimation between pairs of moving vehicles using per...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology 2017-12, Vol.66 (12), p.10637-10646
Main Authors: Niesen, Urs, Ekambaram, Venkatesan N., Jose, Jubin, Xinzhou Wu
Format: Article
Language:English
Subjects:
Algorithms
Broadcast
Broadcasting
Delays
Distance measurement
DSRC
Messages
Offsets
Polynomials
ranging
Receivers
Short-range communications
Transmissions (automotive)
Trip estimation
Unicast
Vehicles
vehicular communication
Wireless fidelity
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Summary:Dedicated short-range communications enables vehicular communication using periodic broadcast messages. We propose to use these periodic broadcasts to perform intervehicle ranging. Motivated by this scenario, we study the general problem of range estimation between pairs of moving vehicles using periodic broadcasts. Each vehicle has its own independent and unsynchronized clock, which can exhibit significant drift between consecutive periodic broadcast transmissions. Consequently, both the clock offsets and drifts need to be taken into account in addition to the vehicle motion to accurately estimate the vehicle ranges. We develop a range estimation algorithm using local polynomial smoothing of the vehicle motion. The proposed algorithm can be applied to networks with arbitrary number of vehicles and requires no additional message exchanges apart from the periodic broadcasts. We experimentally validate our algorithm and show that its performance is close to that of unicast round-trip time ranging. In particular, we are able to achieve submeter ranging accuracies in vehicular scenarios. Our scheme requires additional timestamp information to be transmitted as part of the broadcast messages, and we develop a novel timestamp compression algorithm to minimize the resulting overhead.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2017.2762242