TIIS (한국인터넷정보학회)
Current Result Document : 4,120 / 4,121
| 한글제목(Korean Title) |
Traffic Flow Sensing Using Wireless Signals |
| 영문제목(English Title) |
Traffic Flow Sensing Using Wireless Signals |
| 저자(Author) |
Xuting Duan
Hang Jiang
Daxin Tian
Jianshan Zhou
Gang Zhou
Wenjuan E
Yafu Sun
Shudong Xia
Xuting Duan
Hang Jiang
Daxin Tian
Jianshan Zhou
Gang Zhou
Wenjuan E
Yafu Sun
Shudong Xia
|
| 원문수록처(Citation) |
VOL 15 NO. 10 PP. 3858 ~ 3874 (2021. 10) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatio-temporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles. |
| 키워드(Keyword) |
Internet of Vehicles
RSSI
Traffic Flow Sensing
Cooperative Vehicle Infrastructure System
Internet of Vehicles
RSSI
Traffic Flow Sensing
Cooperative Vehicle Infrastructure System
|
| 파일첨부 |
PDF 다운로드
|
