Traffic responsive intersection control algorithm using GPS data

Abstract

This paper reports on the performance of signalised intersection control using vehicle GPS information compared to fixed-time and inductive loop based control. Traffic congestion forecasts estimate an increase of about 60% in 2030. At present, poor choice of signal timings by isolated intersection controllers cause traffic delays that have enormous negative impacts on the economy and environment. Signal timings can be improved by using vehicles' GPS information to overcome the control action deficit at isolated intersections. This new signal control algorithm is beneficial for traffic engineers and governmental agencies, as traffic flow can be optimised and, hence, fuel consumption and emissions decreased. Under the open European Telecommunication Standards Institute (ETSI) Cooperative Awareness Message (CAM) framework, a traffic responsive GPS based vehicle actuation algorithm (GPS-VA) is proposed. GPS-VA uses position and heading data from vehicle status broadcasts, and inferred velocity information to determine vehicle queue lengths and detect vehicles passing through the intersection. The gathered information is then used to actuate intersection signal timings. Microscopic simulations comparing GPS-VA to fixed-time control and inductive loop based vehicle actuation (Loop-VA) on four urban road networks were performed to see how the proposed GPS-VA algorithm performs compared to existing control strategies. The results show that the GPS-VA is an effective alternative to traditional intersection control strategies, offering delay reductions of up to 50% for connected vehicle fleet penetrations above 30%.

More information

Identifiers

ORCID for Craig, Benjamin Rafter: orcid.org/0000-0003-3411-114X

ORCID for Bani Anvari: orcid.org/0000-0001-7916-7636

Catalogue record

Export record

Altmetrics