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- Title
- METHODOLOGY FOR VEHICLE EMISSION IMPACTS ANALYSIS FROM SIGNAL TIMING OPTIMIZATION OF AN URBAN STREET NETWORK
- Creator
- Lu, Pu
- Date
- 2017, 2017-05
- Description
-
The pace of urban street capacity expansion is much slower than the growth of vehicle travel, leading to several traffic congestions. To...
Show moreThe 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.
Ph.D. in Civil Engineering, May 2017
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- Title
- SAFETY IMPACTS OF SIGNAL TIMING OPTIMIZATION ON URBAN INTERSECTIONS WITH RED LIGHT RUNNING PHOTO ENFORCEMENT
- Creator
- Feng, Siyang
- Date
- 2015, 2015-12
- Description
-
The traffic safety issue especially in urban areas is getting increasingly severe due to the ever-growing travel demand which closely related...
Show moreThe traffic safety issue especially in urban areas is getting increasingly severe due to the ever-growing travel demand which closely related to people’s basic necessities. As a part of the urban traffic network, the safety of the intersections in the urban area also reflects the efficiency and quality of the integrated urbanization level. Red light running at intersections has been a major safety concern in the United States. Because the red light running at intersection often results in a disproportionally higher percentage of injuries. From this point of view, the safety improvement of the urban intersections is imperative. The red light running photo enforcement has been designed to increase safety on streets by reducing the head-on, rear-end, and sideswipe crashes at intersections. Meanwhile, methods for intersection signal timing optimization in urban areas have been developed to reduce intersection delays. As a result of delay reductions, it is also important to analyze changes in vehicle crashes in order to gain a holistic understanding of traffic mobility and safety impacts. This study introduces an Empirical Bayesian (EB) before and after analysis method to evaluate the safety impacts of signal timing optimization on urban intersections with some intersections involved with red light running photo enforcement. Data on 842 signalized intersections are collected to calibrate the safety performance functions and to quantify the crash reduction effects before and after the signal timing optimization. Base on the EB method application, it is reviewed that a certain extent of safety enhancements is achieved as measured by crash type and severity level after intersection signal timing optimization and red light photo enforcement treatments.
M.S. in Civil Engineering, December 2015
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