Optimising a vehicle´s approach towards an adaptively controlled intersection

Traffic emissions at controlled intersections can be reduced when the possibilities of infrastructure-to-vehicle communication are put to good use. In this study the authors present two applications: one infrastructure-based and one vehicle-based that in concert are able to significantly reduce the overall emissions at a controlled intersection. The infrastructure-based application employs a model-predictive control approach, an advanced form of traffic-adaptive control. The vehicle-based application uses information gained from the infrastructure-based application (i.e. the estimated time that the vehicle approaching the intersection will be allowed to enter the intersection and cross the stop line) to improve a vehicle´s approach towards an intersection. Both applications have the same aim: to avoid unnecessary accelerations, decelerations and delay. For both peak and off-peak hours, the results show that the application of a model-predictive controller as opposed to the more traditional traffic-actuated controller is beneficial both in terms of travel time reduction (~15.5% in both cases) and carbon-di-oxide (CO₂) reduction (2.9 and 9.3%, respectively). Together with an approach advice the amount of CO₂ emitted in both cases can be further reduced with an additional 7%, assuming a 100% equipment ratio.