Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6879933 | Computer Communications | 2018 | 19 Pages |
Abstract
Vehicle-to-barrier (V2B) communication is expected to facilitate wireless interactions between vehicles and roadside barriers in next-generation intelligent transportation systems. V2B systems will help mitigate single-vehicle, run-off-road crashes, which account for more than 50% of roadside crash fatalities. In this work, the characteristics of the wireless channel prior to and during a crash are analyzed using orthogonal frequency division multiplexing (OFDM) techniques, which has been used in existing vehicular communication systems. More specifically, the performance of OFDM-based V2B links are measured in real-world crash tests for the first time. Three crash tests conducted at the Midwest Roadside Safety Facility, Lincoln, Nebraska, are reported: a bogie vehicle crashing into a soil-embedded post at 27 mph, a sedan crashing to a concrete curb at 15 mph, and a pickup crashing to a steel barrier at 62 mph. Metrics including signal to interference plus noise ratio received signal strength, error vector magnitude, phase error, channel coherence, and bit error rate, are used to illustrate the impacts of antenna type, antenna deployment, speed, and mobility during the crash tests. The empirical evidence shows that barrier-height (0.7-0.9 m) antennas at the barrier can improve V2B signal quality compared to higher deployments (â¥1.5 m) due to the stronger reflection of electromagnetic waves at a larger angle of incidence. Moreover, compared to omni-directional barrier antennas, directional barrier antennas can increase signal quality, connectivity, and coherence time of V2B channel because of reduced multi-path effects, however, the antenna orientation needs to be carefully determined to maintain connectivity.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Networks and Communications
Authors
Samil Temel, Mehmet C. Vuran, Mohammad M.R. Lunar, Zhongyuan Zhao, Abdul Salam, Ronald K. Faller, Cody Stolle,