AI Analysis on Traffic Data for Traffic Prediction and Management

I&T Solution AI Analysis on Traffic Data for Traffic Prediction and Management
(REF: S-1381)
Trial Project
Solution Feature
  • Data collection on vehicle count and speed in real-time through LiDAR & Video camera
  • Traffic prediction model development through temporal and spatial analysis, integrated external data
  • Prediction of traffic congestion up to 30 minutes ahead
  • Categorization of congestion into low, medium, and high
  • Feedback loop for continuous model improvement
Trial Application and Expected Outcome
  • Install LiDAR sensors and cameras on a selected highway segment in Hong Kong. Collect real-time LiDAR and video data for congestion prediction. Evaluate the system's accuracy in predicting congestion levels based on combined LiDAR and video analytics.
  • Collect data during a major event or a public holiday to analyse congestion patterns before, during, and after the event.
  • Conduct real-time predictions and compare them with actual congestion levels. Measure the system's accuracy, precision, and recall in predicting congestion within the 30-minute timeframe.
  • Deploy the system in an area affected by a temporary road closure. Predict congestion levels during the closure period and compare them with observed congestion.
  • Refine the model with improved congestion judgement criteria.
Additional Solution Information AI Analysis on traffic data for traffic prediction.pdf
Info on I&T Solution Provider
Solution Provider:Kodifly Limited
Address:Unit 661, 6/F, Building 19W, No. 19 Science Park West Avenue, Hong Kong Science Park, Pak Shek Kok, N.T., Hong Kong
Contact Person:Mr Henry WONG
Position:CEO
Tel:6159 3979
Email: henry@kodifly.com
Webpage: https://www.kodifly.com

For details of the above I&T solution, please contact the I&T solution provider.