Impact Assessing of Traffic Lights via GPS Vehicle Trajectories
Bibliographic Data
| ID | 22032002 |
|---|---|
| Authors | Zhuhua Liao (0000-0001-9720-7910, Hunan University of Science and Technology, corresponding author), Hao Xiao (0000-0002-9368-1495, Hunan University of Science and Technology), Silin Liu (0000-0001-6531-5511, Hunan University of Science and Technology), Yizhi Liu (0000-0001-8636-6895, Hunan University of Science and Technology), Aiping Yi (Hunan University of Science and Technology) |
| Year | 2021 |
| Volume | 10 |
| Issue | 11 |
| Pages | 769 |
| Publication date | 2021-11-12 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi10110769 |
| OpenAlex | W3211927032 |
| Language | EN |
| Citations received | 3 |
| References cited | 13 |
The adaptability of traffic lights in the control of vehicle traffic heavily affects the trafficability of vehicles and the travel efficiency of traffic participants in busy urban areas. Existing studies mainly have focused on the presence of traffic lights, but rarely evaluate the impact of traffic lights by analyzing traffic data, thus there is no solution for practicably and precisely self-regulating traffic lights. To address these issues, we propose a low-cost and fast traffic signal detection and impact assessment framework, which detects traffic lights from GPS trajectories and intersection features in a supervised way, and analyzes the impact range and time of traffic lights from intersection track data segments. The experimental results show that our approach gains the best AUC value of 0.95 under the ROC standard classification and indicates that the impact pattern of traffic lights at intersections is high related to the travel rule of traffic participants
Adaptability · Floating car data · Global Positioning System · Real-time computing · Telecommunications · Traffic congestion · Traffic signal · Transport engineering · Anomaly Detection Techniques and Applications · Automated Road and Building Extraction · Computer Science · Engineering · Traffic Prediction and Management Techniques
| Citations per year | 0.75 |
|---|---|
| Citation span | 2022 - 2023 (2) |
| Highly cited | No |