Singapore has over 2,200 traffic lights and nearly 30,000 registered taxis. If the top 10% of traffic lights would be addressed this requires a multi-million infrastructure investment, that would increase traffic flow (20-40%), fuel efficiency (up to 15%) and safety, while decreasing traffic bound emissions (up to 30%%) and noise.
We developed a technology concept for optimisation of large traffic networks through in-car or road-side green light optimised speed advice (GLOSA) based on interaction with next generation Traffic Controllers. Current adaptive traffic controllers will become predictive connected controllers, potentially improving throughput by 20-40%, while lowering emissions (CO2, NOx, PM) and noise. Individual cars (especially commercial vehicles such as taxis and trucks) benefit, as well as overall system performance for urban traffic
Technology Features, Specifications and Advantages
Solution components (Proof of Concept):
1. Model predictive traffic light controller that optimises traffic based on (in-car or roadside) sensor enabled) predictions for improved overall network performance, or target group preferential treatment (pedestrians, public transport, ambulance).
2. On Board Unit and/or smartphone application indicating time-to-green/red
3. Simulation environment capable of simulating effects of Smart Intersections on traffic speed, travel time, climate (CO2), noise and air quality
Industry: Traffic authorities, Traffic engineering firms, traffic (management) technology firms, traffic service providers, logistics & transport companies, taxi/hail riding companies
Products & services marketed:
- Simulation of network effects of smart Intersections
- Software algorithms for In-car speed advice for Green and Red light
- JUNO model predictive based connected traffic controller
Increased fuel efficiency (up to 15%), optimised traffic flow (20-40%), lower emissions (up to 30%)