交通監視カメラを用いた市街地の車両モビリティ合成手法
A Method for Synthesizing Vehicle Mobility in Urban Areas Using Traffic Surveillance Cameras
We present a case study on synthesizing realistic vehicle mobility using link traffic information extracted from
surveillance videos. Our trial has been conducted in a town of Toyooka city, Japan, where many people visit using private vehicles in tourism seasons, which causes parking lot issues in the center of the town. We have developed an automatic vehicle tracking system that can measure the link traffic in the captured videos. Using the information and a set of potential routes between origin and destination in the town, we estimate, for each route, the volume of the traffic flow on the route. Finally, we generate micro-level vehicle mobility data using a traffic simulator, minimizing the Mean Absolute Percentage Error(MAPE) between the measured and generated link volumes. The synthesized mobility will be used for improving the traffic, for example, the adoption of new traffic regulations in the region.
The reproduced mobility data obtained in this study are available here.
Published Paper
- 林和輝, 廣森聡仁, 山口弘純, 鈴木理基, & 北原武. (2022). 交通映像からの車線交通量抽出とそれを用いた地域モビリティデータ生成. マルチメディア, 分散, 協調とモバイルシンポジウム 2022 論文集, 2022, 1458-1467.
- 林和輝, 廣森聡仁, 山口弘純, 鈴木理基, & 北原武. (2022). 交通監視カメラを用いた市街地の車両モビリティ合成手法. 研究報告コンピュータセキュリティ (CSEC), 2022(2), 1-8.
- Kazuki Hayashi, Akihito Hiromori and Hirozumi Yamaguchi (Osaka University, Japan); Masaki Suzuki and Takeshi Kitahara (KDDI Research, Inc., Japan, "Synthesizing Town-scale Vehicle Mobility from Traffic Surveillance Cameras: A Case Study", Proceedings of the 2022 IEEE International Workshop on Pervasive Computing for Vehicular Systems Co-located with IEEE PerCom 2022, pp. 593-598