The University of Nottingham | United Kingdom
Chonghan Chen | Wenzhe Pei | Minjie Lyu | Song Zhang
Our team proposes an intellectual traffic planning and controlling system, which utilises traffic data to optimize city traffic by controlling traffic light and provide route advice for drivers. By applying this system, we can: - Ease traffic congestion - Save traveling time - Reduce fuel consumption - Provide prioritized services for different vehicles. The data will mainly be obtained through pre-existing traffic monitoring devices, including sensors and surveillance cameras. We would expect this data to be provided by third parties or governments. Depending on the size of our user base, we would also consider obtaining data from users. Machine learning can be used to learn traffic patterns. It can also be used to search for the best traffic arrangement.