The technology predicts future traffic conditions of large scale road networks in real-time and provide predictive route guidance to users. In this way, the technology promises to reduce the driver’s travel time, fuel consumption and discomfort, and improve the overall productivity.
Traffic states of the large-scale networks can be predicted in real-time by deploying the compressed prediction method (a proprietary method developed earlier and applied for patent). Compressed prediction is a fast and scalable algorithm that enables real-time traffic prediction across multiple time horizons for large road networks. Route Guidance is implemented on top of the traffic prediction, giving optimal route based on future traffic conditions. The deliverable solution for individual users is in the form of smartphone application giving users real-time traffic information in GIS context. Users will also be able to share traffic information with others using social networking apps. Crowdsourcing is also done to further improve the predictions accuracy route reliability.
The technology is targeted to three types of users: Individual car owners/commuters Taxi companies/Delivery vans Public sector companies managing road infrastructure
Traffic congestion introduces delay, impacts the driver comfort and satisfaction, increases pollution and noise at congestion sites and significantly reduces the productivity of the city. It has been shown that through efficient routing offer reduction in travel time (up to 14%), fuel consumption (up to 7.8%) and variability of travel times (up to 50%). Hence real-time network estimation and multi-horizon predictions are necessary for efficient utilization of network infrastructure.
Avoid traffic congestion and potential traffic jams Reliable commuting times Providing alternate routes to avoid congestion Better management of roads and infrastructure