Robust signal timing optimization with environmental concerns

This paper formulates a bi-objective optimization model to determine timing plans for coordinated traffic signals along arterials to minimize traffic delay and the risk associated with human exposure to traffic emissions. Based on a cell-transmission representation of traffic dynamics, a modal sensitive emission approach is used to estimate the tailpipe emission rate for each cell of a signalized arterial. A cell-based Gaussian plume air dispersion model is then employed to capture the dispersion of air pollutants and compute the roadside pollutant concentrations. A measure of mean excess exposure is further defined to represent the risk associated with human exposure to traffic pollutants under the wind uncertainty. A signal timing optimization model is formulated to optimize the cycle length, offsets, green splits and phase sequences to minimize the total system delay and the mean excess exposure simultaneously. The bi-objective optimization model is solved via a simulation-based genetic algorithm to find a set of Pareto optimal solutions. A numerical example is presented to demonstrate the model.

• This paper develops a signal timing optimization model. • The objective is to minimize both traffic delay and air pollutant concentrations. • The model is macroscopic and computationally tractable. • The model optimizes cycle length, green splits, phase sequences and offsets. • A numerical example based on a real arterial is presented to demonstrate the model.