Methodology for Vehicle Emission Impacts Analysis from Signal Timing Optimization of an Urban Street Networ

The pace of urban street capacity expansion is much slower than the growth of vehicle travel, leading to several traffic congestions. To mitigate traffic congestion expanding capacity is not feasible for many cases due to the high cost and space restriction. Improving the efficient use of the available capacity becomes the solution. Traffic signal optimization is one of the most widely used ways of efficient capacity utilization. Concurrent to traffic signal optimization, more smooth traffic operations in term of reasonably higher speed and a reduced traffic delay will in turn change vehicle emissions. This research aims to quantify changes in vehicle emissions resulted from traffic signal optimization by introducing a new methodology for quantifying network wide vehicle emissions and real world application in of the Chicago urban network for validation. The proposed methodology considers undersaturation and oversaturation of traffic conditions and urban street segments with varying speeds for different types of vehicles and pollutants by hour of the day and location within the network. It begins with information collection and research through a review of existing methods for urban street network vehicle emission estimation, intersection vehicle emission evaluation, and the running vehicle emission modeling. The proposed methodology focuses on three elements: estimation of emissions from vehicles stopped at intersections and for vehicles cruising along segments, as well as analysis of network wide vehicle emissions and changes in overall network vehicle emissions by time of the day and by areas. Major steps of methodology application included the use of Chicago TRANSIMS model implementing optimized signal timing plans to obtain refined traffic volumes at intersections and on segments, increased vehicle operating speeds, changed green splits, and vehicle compositions for all intersections and segments in the urban street network, the application of an intersection vehicle emission model for stopped vehicles and a segment vehicle emission model for vehicles cruising on segments, and the network wide analysis of vehicle emission changes by vehicle type and pollutant type in a 24-hour period within an urban street network, respectively. The proposed methodology for intersection vehicle emission estimation was successfully applied to a dense urban street network in Chicago for each approach per cycle and then extended for intersections in hours of the day to analyze the impacts of traffic changes at intersections on exhaust changes. In order to develop the network vehicle emission analysis method, it is essential to evaluate the segment vehicle emissions. This is achieved by using the concept of vehicle specific power which is used to estimate emissions of cruising vehicles considered along with vehicle speeds and speed changes and hence analyzing changes in segment vehicle emissions affected by traffic volume changes derived from signal timing optimization. The decreased number of vehicles stopped at intersections by applying signal timing optimization will reduce intersection emissions, hence reducing overall network vehicle emissions. In addition to have vehicle emissions got reduced at intersections, the increasing vehicle speed for vehicles on segments could further reduce vehicle emissions on segments.