Browsing by Author "Tao, Tao"
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Item After Study of The Bus Rapid Transit A Line Impacts(Center for Transportation Studies, University of Minnesota, 2018-12) Tomhave, Benjamin; Zhang, Yufeng; Khani, Alireza; Hourdos, John; Dirks, Peter; Olsson, Jack; Tao, Tao; Wu, Xinyi; Cao, JasonIn response to the limited awareness surrounding Bus Rapid Transit (BRT) and the A Line, this study provides answers to questions regarding the operation and public perception of the A Line in the Twin Cities region, Minnesota. Two traffic scenarios were studied, one for high-volume oversaturated traffic during the Minnesota State Fair, and a second for normal operating conditions. For both scenarios, intersection queue length and traffic flow rate were compared before and after an A Line bus. It was found that in both time periods (Fair and non- Fair), the dwelling of an A Line bus during a green traffic signal did not have a statistically significant impact on intersection queue length or traffic-flow rate at either of the two researched stations. From an analysis of the 2016 On-Board Survey, it was determined that passengers are more satisfied by the overall service of the A Line than local buses while there is not a significant difference in overall satisfaction compared to express buses, light rail and commuter rail. The top three important service attributes to overall satisfaction are “paying my fare is easy,” “hours of operation,” and “handling of concerns/complaints.” It is recommended that the transit agency improve the attributes that have higher relative influences and lower mean performances. Based on this criterion, the attributes that should be given priority are “shelter/station conditions and cleanliness” and “behaviors of other passengers and atmosphere on board.”Item The effects of pedestrian and bicycle exposure on crash risk in Minneapolis(Journal of Transport and Land Use, 2021) Tao, Tao; Lindsey, Greg; Cao, Jason; Wang, JueyuExposure to risk is a theoretically important correlate of crash risk, but many safety performance functions (SPFs) for pedestrian and bicycle traffic have yet to include the mode-specific measures of exposure. When SPFs are used in the systematic approach to assess network-wide crash risk, the omission of the exposure potentially could affect the identification of high-risk locations. Using crash data from Minneapolis, this study constructs and compares two sets of SPFs, one with pedestrian and bicycle exposure variables and the other without, for network-wide intersection and mid-block crash models. Inclusion of mode-specific exposure variables improves model validity and measures of goodness-of-fit and increases accuracy of predictions of pedestrian and bicycle crash risk. Including these exposure variables in the SPFs changes the distribution of high-risk locations, including the proportion of high-risk locations in low-income and racially concentrated areas. These results confirm the importance of incorporating exposure measures within SPFs and the need for pedestrian and bicycle monitoring programs to generate exposure data.Item Exploring the interaction effect of poverty concentration and transit service on highway traffic during the COVID-19 lockdown(Journal of Transport and Land Use, 2021) Tao, Tao; Cao, JasonDuring COVID-19 lockdowns, transit agencies need to respond to the decline in travel but also maintain the essential mobility of transit-dependent people. However, there are a few lessons that scholars and practitioners can learn from. Using highway traffic data in the Twin Cities, this study applies a generalized additive model to explore the relationships among the share of low-income population, transit service, and highway traffic during the week that occurred right after the 2020 stay-at-home order. Our results substantiate that transportation impacts are spread unevenly across different income groups and low-income people are less able to reduce travel, leading to equity concerns. Moreover, transit supply influences highway traffic differently in areas with different shares of low-income people. Our study suggests that transportation agencies should provide more affordable travel options for areas with concentrated poverty during lockdowns. In addition, transit agencies should manage transit supply strategically depending on the share of low-income people to better meet people’s mobility needs.Item Impact of Transitways on Travel on Parallel and Adjacent Roads and Park-and-ride Facilities(Minnesota Department of Transportation, 2021-01) Webb, Alex; Tao, Tao; Khani, Alireza; Cao, Jason; Wu, XinyiTransitways such as light rail transit (LRT) and bus rapid transit (BRT) provide fast, reliable, and high-capacity transit service. Transitways have the potential to attract more riders and take a portion of the auto mode share, reducing the growth of auto traffic. Park-and-ride (PNR) facilities can complement transit service by providing a viable choice for residents who are without walking access to transit or those who prefer better transit service such as LRT or BRT. In this study, we conducted two research tasks on Transitways services in the Twin Cities region in Minnesota; 1) to examine the impact of the operation of the Green Line LRT on the annual average daily traffic (AADT) of its adjacent roads, and 2) to estimate a PNR location choice model in the Twin Cities metropolitan area.Item Nonlinear and threshold relationships between built environment attributes and travel behavior(2022-09) Tao, TaoSince the 1990s, a growing number of studies have examined the relationships between built environment attributes and travel behavior and offered supportive evidence for planning policies that discourage driving and/or encourage transit and active travel modes. Due to the lack of efficient methods, most studies assume that the relationships between built environment attributes and travel behavior are (generalized) linear. The rise of machine learning approaches allows scholars to relax the assumption. Built on the recent literature, my dissertation aims to further advance the field on the nonlinear and threshold relationships between built environment attributes and travel behavior through studying three distinct but interrelated research topics. Most studies focus on only one travel mode and fall short of comparing nonlinear and threshold relationships of the built environment with different travel modes. Identifying the common thresholds for different modes enables the optimization of built environment attributes. Using regional travel survey data in the Twin Cities, the US, the study in Chapter 2 applies gradient boosting decision trees (GBDT) to examine and compare the nonlinear associations between built environment attributes and travel distances by driving, transit, and active travel. It also compares the contributions of regional and local built environment attributes. The results show that there are prevalent nonlinear associations between built environment characteristics and travel distances, informing planners of the effective ranges, within which the characteristics influence travel distances efficiently. Moreover, regional characteristics collectively have a stronger influence on all three travel distances than local characteristics. This result suggests that planners should pay more attention to metropolitan-scale planning and deploy programs that enhance regional accessibility. Few studies emphasize the nonlinear relationship between the built environment and auto use in suburban areas. However, their association in suburban areas may differ from that in urban areas, implying context-specific planning policies. The study in Chapter 3 uses GBDT to explore the nonlinear relationships between built environment attributes and driving distance in suburban areas and how the relationships differ from those in urban areas of the Twin Cities. The result shows that enhancing job accessibility and intersection density are promising for reducing driving in suburban areas. Transit supply plays a moderate role in reducing diving distance in suburban areas. However, density and land use diversity, although important in urban areas, have trivial influences in suburban areas. Previous studies using cross-sectional data to examine the nonlinear relationships usually reveal the nonlinear associations between built environment attributes and travel behavior. The study in Chapter 4 applies transport rationales, extracted by Dr. Petter Næss and his research team from a comprehensive analysis of qualitative interview data, and the GBDT approach to data from Stavanger, Norway to explore causal mechanisms for the nonlinear relationships. The results show that transport rationales for choosing activity locations and travel modes, along with configurations of the jobs and other facilities, provide causal explanations for the nonlinear and threshold effects of built environment attributes on people’s driving-related behavior. Distance to city center plays the most important role and its nonlinear relationship reflects the influence of the polycentric city structure of Stavanger on driving. For Stavanger and similar cities, compact development around the city center helps to rein auto dependence. Furthermore, the threshold relationships provide planning guidelines to support compact development policies.Item Pedestrian and Bicycle Crash Risk and Equity: Implications for Street Improvement Projects(2019-06) Lindsey, Greg; Tao, Tao; Wang, Jueyu; Cao, JasonTransportation managers need information about crash risk and equity to prioritize investments in street networks. This case study uses data from Minneapolis, Minnesota, to illustrate how estimates of pedestrian and bicycle crash risk and assessments of inequities in the distribution of that risk can inform prioritization of street improvement projects. Crash numbers and frequencies for pedestrian and bicycle crashes at intersections and mid-blocks in Minneapolis are determined for the 2005-2017 period. New models of pedestrian and bicycle crash risk at both intersections and mid-blocks that control for exposure are introduced and used to predict crashes at all intersections and mid-blocks in the city. Statistical tests are used to assess the equity of distribution of estimated crash risk between areas of concentrated poverty with majority-minority populations and other areas in the city. Crash indexes based on predicted crashes are used to illustrate how increased emphases can be placed on pedestrian and bicycle safety in street improvement rankings. Results show that pedestrian and bicycle crash risk is correlated with exposure, that different factors affect crash risk at intersections and mid-blocks, and that these factors differ for pedestrian and bicycle crashes. Results also show that mean crash risk is higher in neighborhoods with lower incomes and majority-minority populations. For street improvement projects in the city, different rankings result when segments are ranked according to modeled pedestrian and bicycle crash risk in addition to total crash rates based on historical numbers of crashes at particular locations. Results generally affirm efforts by the Minneapolis Department of Public Works to increase emphases on pedestrian and bicycle safety and equity in its prioritization of street improvements.Item The Value of Dedicated Right of Way (ROW) to Transit Ridership and Carbon Emissions(Center for Transportation Studies, University of Minnesota, 2023-12) Cao, Jason; Tao, Tao; Johnson, Isak; Huang, HannahTransit agencies have adopted various types of right of way (ROW) for transit routes, including mixed traffic, semi-exclusive ROW, exclusive ROW, and grade separation, but few empirical studies have quantified their impacts on ridership and carbon emissions. Using data collected from transit agencies in the US, this research aimed to examine the impacts of dedicated ROW. We applied the gradient boosting decision tree method to estimate the nonlinear relationships between yearly route-level transit ridership and five types of independent variables, with a focus on ROW. The results showed that ROW contributes 18% of the power to predicting transit ridership, which is the largest among all the independent variables. Upgrading from mixed traffic to semi-exclusive ROW could boost ridership by 70,000, on average. A further upgrade to an exclusive ROW could add 3.68 million passengers. Moreover, the number of stops, transit route commence year, population density, signal priority, number of park-and-ride facilities, headway, network density, and route length all have non-trivial contributions to predicting ridership. Upgrading the operating environment could substantially reduce carbon emissions, up to 6.37 million pounds of CO2e. Overall, elevating ROW levels could notably enhance transit ridership and reduce carbon emissions, locating transit routes in the areas with adequate population density and network density could improve their performance, deploying signal priority and improving transit frequency also help, and increasing the share of electric buses could further decrease carbon emissions.