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UBC Theses and Dissertations

Analyzing the impacts of common and emerging transit service improvement strategies using traffic and emission microsimulation models Munia, Sadia Nowroz


This thesis develops traffic and emission microsimulation models to evaluate the impacts of transit preferential treatments on transport network and the environment. Common preferential treatments such as transit signal priority (TSP), queue jump lane (QJL), transit lane (TrLane), and combination of TSP and QJL (TSP+QJL), as well as emerging strategies such as automated vehicles (AV) are investigated. In the case of assessing network performance, indicators such as delay, number of stops and reliability are used. In the case of emission impacts, emissions from greenhouse gases (GHG) and criteria air contaminants (CAC) for different types of fuels are analyzed. The benefits of AVs are evaluated for alternative driving behaviors, penetration rates, congestion-level and fuel types. The traffic microsimulation model was developed using PTV’s VISSIM platform, and the emission simulation was performed using USEPA’s MOVES3. The study area for this thesis is a mixed traffic congested urban corridor running along the midtown area of Kelowna, BC. The traffic simulation model was calibrated and validated with a reasonably satisfactory accuracy for different peak periods. Among the common preferential treatments, TSP+QJL is found to be a comparatively effective option to reduce congestion delay (i.e., up to 16% than base delay) and runtime deviation (i.e., up to 19% than base deviation). A regression analysis further suggests the effectiveness of TSP+QJL, since it shows a higher likelihood to reduce deviation and does not reveal any variations over a specific period. The environmental impact assessment results show the TSP+QJL scenario reduces total corridor level GHG by 10% for CNG transit vehicles, whereas for Diesel engines, the reduction becomes 9%. Although TSP+QJL reduces significant delay or idle time at intersection, it reduces lower GHG than TrLane. Furthermore, while comparing these common transit improvement scenarios with of the emerging AV scenario, aggressive AVs yield a significant higher reduction in average delay (i.e., 40%) compared to the TSP+QJL scenario (i.e., up to 16%) for congested condition. The aggressive AV scenario also shows higher reduction in total emission for congested condition (i.e., 35%) than the uncongested condition (i.e., 3.9%).

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Attribution-NonCommercial-NoDerivatives 4.0 International