@inproceedings{819,
  author = {Tam Nguyen and Thanh Tran and Viet-Tham Huynh and Bao Truong and Minh-Quan Le and Mohit Kumavat and Vatsa Patel and Mai-Khiem Tran and Minh-Triet Tran},
  title = {Data-Driven City Traffic Planning Simulation},
  abstract = {Big cities are well-known for their traffic congestion and high density of vehicles such as cars, buses, trucks, and even a swarm of motorbikes that overwhelm city streets. Large-scale development projects have exacerbated urban conditions, making traffic congestion more severe. In this paper, we proposed a data-driven city traffic planning simulator. In particular, we make use of the city camera system for traffic analysis. It seeks to recognize the traffic vehicles and traffic flows, with reduced intervention from monitoring staff. Then, we develop a city traffic planning simulator upon the analyzed traffic data. The simulator is used to support metropolitan transportation planning. Our experimental findings address traffic planning challenges and the innovative technical solutions needed to solve them in big cities.},
  year = {2022},
  journal = {ISMAR 2022},
  chapter = {859},
  pages = {6},
  month = {10},
  url = {https://par.nsf.gov/biblio/10428271},
  doi = {10.1109/ISMAR-Adjunct57072.2022.00185},
}