Abstract Description: The paper will focus on quantifying the impacts of traffic crashes on roadway emissions. Crashes contribute to approximately 25 percent of non-recurring congestion. Respectively, congestion on roadways tends to increase carbon dioxide emissions which ultimately have a negative effect on public health. The objective of this study is to determine how crashes by severity affect delay on different roadway types which will then be associated to emissions. Austin, the capital city of Texas will be as a case study for the analysis. Crashes and roadway characteristics for the most recent year will be matched and overlapped with traffic flows during the same period. Traffic flow data in terms of speed and occupancy can be obtained from sensors deployed on the transportation system or from INRIX platform which will be used to capture the spatio-temporal congested regions caused by crashes. INRIX provides real-time location-based data collected anonymously from vehicles. GPS-enabled smartphones, cameras and sensors on roadways. The increase in emissions associated with the congestion are estimated using emission factors from latest EPA Moves model. Subsequently, survival statistical analysis is adopted to identify the relationships between crashes and their emissions impacts on different roadway types. Outcomes from the analysis performed can assist decision makers to apply effective low-cost strategies to improve safety on roadways, therefore, reducing emissions due to congestion.
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