Date of Award
College of Science, Engineering, and Technology (COSET)
MS in Transportation Planning & Management
Professor Lei Yu
The issues regarding Greenhouse Gas (GHG) emissions have attracted worldwide attention. In the transportation sector, the emissions from on-road vehicles are known as a major source of GHG emissions. As we know, the implementation of different traffic management strategies will result in changes in emission levels for different emission species, therefore, these strategies can potentially be very effective approaches to reduce mobile source GHG emissions, especially a vehicle's CO2 emissions. However, due to real-world data constrain and the limitations associated with current mobile source emission models, there has not been a systematic effort to study the impact of a specific traffic management strategy on mobile source GHG emission control. This research is intended to develop an emission estimation methodology to quantify a vehicle's CO2 emissions in a real-world traffic network, in which a Portable Emission Measurement System (PEMS) is used to collect the vehicle's real-world emission and activity data, and a Vehicle Specific Power (VSP) based modeling approach is used as the basis for emission estimation. Three traffic management strategies are selected in this study, including High Occupancy Vehicle (HOV) lane, traffic signal 2 coordination plan, and Electronic Toll Collection (ETC). In the HOV lane scenario, CO2 emission factors produced by the testing vehicle using HOV lane and the corresponding mixed flow lane are compared. In the evaluation of traffic signal coordination, total CO2 emissions produced under the existing coordinated signal timing and the emulated non coordinated signal timing along the same designed testing route are compared. In the ETC scenario, total CO2 emissions produced by the testing vehicle around an ETC station and a .Manual Toll Collection (MTC) station located on the same toll road segment are estimated and compared. The results from this study indicate that the proposed emission estimation methodology is accurate. It is a combination of the advantages of field testing approach and the latest modeling approach practice. The evaluation study on the three selected traffic management strategies demonstrated that HOV lane, well-coordinated signal timing, and ETC are all effective measures to reduce mobile source GHG emissions. However, their level of effectiveness is different.
Shi, Qinyi, "Evaluation of mobile Source Greenhouse Gas Emissions for assessment of Traffic Management Strategies" (2011). Theses (Pre-2016). 196.