Name
Title | ||
|---|---|---|
An Internet-of-Vehicles Powered Defensive Driving Warning Approach for Traffic Safety |
Abstract | ||
|---|---|---|
As a major type of driver assistance technologies, automated warning systems provide drivers and vulnerable road users with safety. These systems, such as forward collision warnings, can detect potential risks nearby and alert the drivers. One shortcoming of such warning systems is that their effectiveness and capability depend on the information collected from sensors existing in a single vehicle, which can be highly limited in the presence of occlusion, leading to irreversible consequences. To overcome this shortcoming, in this paper, we benefit from the vehicular sensing and communication technologies to propose a novel Internet-of-vehicles (IoV) powered framework for defensive driving warning, in which a vehicle can take advantage of other vehicles sensing data through V2V communications. We further evaluate the introduced framework in cyclist protection system scenarios. Simulation results demonstrate how the proposed IoV-based framework can improve warning systems by providing increased situational awareness. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/GLOBECOM46510.2021.9685139 | 2021 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM) |
Keywords | DocType | ISSN |
Driving behavior analysis, vehicular network, risky driving, cyclist detection, intelligent vehicles | Conference | 2334-0983 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mozhgan Nasr Azadani | 1 | 0 | 2.37 |
| Boukerche, A. | 2 | 61 | 16.98 |