Name
Title | ||
|---|---|---|
LiDAR-Enhanced Connected Infrastructures Sensing and Broadcasting High-Resolution Traffic Information Serving Smart Cities. |
Abstract | ||
|---|---|---|
Connected-vehicle system is an important component of smart cities. The complete benefits of connected-vehicle technologies need the real-time information of all vehicles and other road users. However, the existing connected-vehicle deployments obtain the real-time status of connected vehicles, but without knowing the unconnected traffic since there are still many unconnected vehicles and pedestrians on the roads. Therefore, it is urgent to find an approach to collect the high-resolution real-time status of unconnected road users. When it is difficult for all vehicles, pedestrians, and bicyclists to broadcast their real-time status in the near future, enhancing the traffic infrastructures to actively sense and broadcast each road user's status is an intuitive solution to fill the data gap. This paper introduces a new-generation LiDAR-enhanced connected infrastructures that can actively sense the high-resolution status of surrounding traffic participants with roadside LiDAR sensors and broadcast connected-vehicle messages through DSRC roadside units. The system architecture, the LiDAR data processing procedure, the data communication, and the first pilot implementation at an intersection in Reno, Nevada are included in this paper. This research is the start of the new-generation connected infrastructures serving connected/autonomous vehicles with the roadside LiDAR sensors. It will accelerate the deployment of the connected network for the smart cities to improve traffic safety, mobility, and fuel efficiency. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ACCESS.2019.2923421 | IEEE ACCESS |
Keywords | Field | DocType |
Connected-vehicle,LiDAR data,communication platform,smart cities | Broadcasting,Software deployment,Computer science,Computer network,Lidar,Systems architecture,Lidar data,Fuel efficiency,Dedicated short-range communications | Journal |
Volume | ISSN | Citations |
7 | 2169-3536 | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bin Lv | 1 | 15 | 3.03 |
| Hao Xu | 2 | 12 | 12.74 |
| Jianqing Wu | 3 | 4 | 2.46 |
| Yuan Tian | 4 | 6 | 8.99 |
| Yongsheng Zhang | 5 | 204 | 43.58 |
| Yichen Zheng | 6 | 0 | 0.34 |
| Changwei Yuan | 7 | 0 | 1.35 |
| Sheng Tian | 8 | 0 | 1.01 |