Abstract
The increase in traffic volumes in urban areas makes network delay and capacity optimisation challenging. However, the introduction of connected vehicles in intelligent transport systems presents unique opportunities for improving traffic flow and reducing delays in urban areas. This paper proposes a novel traffic signal control algorithm called Multi-mode Adaptive Traffic Signals (MATS) which combines position information from connected vehicles with data obtained from existing inductive loops and signal timing plans in the network to perform decentralised traffic signal control at urban intersections. The MATS algorithm is capable of adapting to scenarios with low numbers of connected vehicles, an area where existing traffic signal control strategies for connected environments are limited. Additionally, a framework for testing connected traffic signal controllers based on a large urban road network in the city of Birmingham (UK) is presented. The MATS algorithm is compared with MOVA on a single intersection, and a calibrated TRANSYT plan on the proposed testing framework. The results show that the MATS algorithm offers reductions in mean delay up to 28% over MOVA, and reductions in mean delay and mean numbers of stops of up to 96% and 33% respectively over TRANSYT, for networks with 0-100% connected vehicle presence. The MATS algorithm is also shown to be robust under non-ideal communication channel conditions, and when heavy traffic demand prevails on the road network.
Highlights
I NCREASING traffic volumes in urban areas make network delay and capacity optimisation challenging
Under non-ideal communication conditions, the mode Adaptive Traffic Signals (MATS) algorithm reduces mean delay better than Microprocessor Optimised Vehicle Actuation (MOVA) above 40% Connected Vehicles (CV) penetration, with reductions in mean delay between 19%-29% above 40% CV penetration. When both inductive loop and CV data are used in the MATS-HA algorithm, the MATS-HA algorithm reduces mean delay between 12%-15% compared with MOVA for CV penetrations ≥10%
The results show that the MATS algorithm is better than the state-of-the-art vehicle actuation strategy MOVA, and that loop detector data is useful at low CV penetrations but can limit performance at high CV penetrations
Summary
I NCREASING traffic volumes in urban areas make network delay and capacity optimisation challenging. The current literature does not properly address the issue of imperfect communication channel conditions and testing traffic signal control algorithms at increasing penetrations of CVs, and in realistic scenarios. RAFTER et al.: AUGMENTING TRAFFIC SIGNAL CONTROL SYSTEMS FOR URBAN ROAD NETWORKS WITH CV demands of mixed-mode traffic, varying levels of CV penetration, and under imperfect communication channel conditions. The contributions of this paper are as follows: 1) A new traffic signal control algorithm, MATS, is proposed which combines information from existing fixed-time plans and loop detectors, and position data from CVs to perform decentralised control on signalised intersections.
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