Computing optimum traffic signal cycle length considering vehicle delay and fuel consumption

Abstract

Traffic signal cycle lengths are traditionally optimized to minimize vehicle delay at intersections using the Webster formulation. This study continues previous work by the authors to enhance the Webster model and develop new formulations to compute the optimum cycle length, considering vehicle delay, fuel consumption, and tailpipe emissions. The microscopic simulation software INTEGRATION is used to simulate two-phase and four-phase isolated intersections over a wide range of traffic demand levels, traffic demand distributions, cycle lengths, and signal timing lost times. Intersection delay, fuel consumption levels, and emissions of carbon dioxide (CO2), hydrocarbon (HC), carbon monoxide (CO), and oxides of nitrogen (NOx) are derived from the simulation software. The optimum cycle lengths for various measures of effectiveness are then used to develop the proposed formulations. The simulation results demonstrate that the Webster method overestimates the optimum cycle length and produces unrealistically long cycle length estimates when the traffic volume-to-capacity ratio exceeds 50%. A new logarithmic delay model is proposed herein to address the shortcomings of the Webster model. This model is then calibrated to compute the optimum cycle lengths considering vehicle fuel consumption and emission levels. The estimated optimum cycle lengths for emissions are shown to be longer than the optimum cycle lengths for vehicle delay for lower levels of congestion. The paper demonstrates how a multi-objective cycle length can be computed to simultaneously minimize vehicle delays and fuel consumption levels. After computing the optimum cycle length, the optimum phase split can then be computed using the traditional approach of equating the degree of saturation across all phases. It is anticipated that the proposed formulations will produce significant savings in vehicle delay and fuel consumption levels.