AI Use Case
Predict likelihood of traffic accidents or queues and optimise traffic system to reduce the risk
Predict likelihood of traffic accidents or queues and optimise traffic system to reduce the risk. This will require the deployment of sensors and 'smart' traffic lights.
Operational - Customer wait times,Risk reduction - Reduce environmental physical risk,Risk reduction - Environmental impact
Milton Keynes~Milton Keynes will attempt to ease congestion and detect traffic conditions using AI-enabled traffic lights,Rapid Flow Technologies~Surtrac reduces intersection wait times by 40% and travel time by 25% on average by optimising traffic signals based on real-time data,New Delhi Police~New Delhi Police plans to manage traffic in the city using camera sensors and machine learning,Santa Clara University~Santa Clara University improves pedestrian safety by automatically detecting approaching people and triggering a crosswalk signal ,Didi Chuxing~Didi to tackle traffic congestion and optimise navigation routes with deep learning,Iowa Department of Transportation~Iowa Department of Transportation uses machine learning to monitor traffic flows during winter,Department for Transport~The Department for Transport aims to monitor UK roads for faster reaction to road incidents using deep learning
Public And Social Sector
ML Task - Action Selection - Reinforcement Learning ,Machine Learning (ML),Traditional AI,ML Task - Prediction - Binary Classification,ML Task - Prediction - Multi-class Classification,ML Task - Prediction - Annotation,ML Task - Prediction - Regression,Product - Data Capture - Sensor IoT,Product - Data Capture - Camera