| Title |
Movement Recommendation System Based on Multi-Spot Congestion Analytics |
| ID_Doc |
42983 |
| Authors |
Nakayama, K; Onoue, A; Hori, M; Shimada, A; Taniguchi, R |
| Title |
Movement Recommendation System Based on Multi-Spot Congestion Analytics |
| Year |
2020 |
| Published |
Sustainability, 12, 6 |
| DOI |
10.3390/su12062417 |
| Abstract |
A method is proposed for resolving human congestion at a specific time at key spots in an area. Sensing data on real-world human flows are analyzed, and important information for changing movement behavior is accordingly provided. By using conventional approaches, this was a difficult task, whereas in the proposed approach, the targets and timing of providing information for congestion mitigation are determined based on spot importance. A congestion transition model is constructed from actual data and the results of a questionnaire survey. Finally, congestion mitigation in key spots is simulated after movement recommendation has been provided. |
| Author Keywords |
data visualization; predictive analytics; smart city |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI) |
| EID |
WOS:000523751400264 |
| WoS Category |
Green & Sustainable Science & Technology; Environmental Sciences; Environmental Studies |
| Research Area |
Science & Technology - Other Topics; Environmental Sciences & Ecology |
| PDF |
https://www.mdpi.com/2071-1050/12/6/2417/pdf?version=1584707661
|