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Description
The environmental and economic assessment of neighborhood-scale transit-oriented urban form changes should include initial construction impacts through long-term use to fully understand the benefits and costs of smart growth policies. The long-term impacts of moving people closer to transit require the coupling of behavioral forecasting with environmental assessment. Using new light rail and bus rapid transit in Los Angeles, California as a case study, a life-cycle environmental and economic assessment is developed to assess the potential range of impacts resulting from mixed-use infill development. An integrated transportation and land use life-cycle assessment framework is developed to estimate energy consumption, air emissions, and economic (public, developer, and user) costs. Residential and commercial buildings, automobile travel, and transit operation changes are included and a 60-year forecast is developed that compares transit-oriented growth against growth in areas without close access to high-capacity transit service. The results show that commercial developments create the greatest potential for impact reductions followed by residential commute shifts to transit, both of which may be effected by access to high-capacity transit, reduced parking requirements, and developer incentives. Greenhouse gas emission reductions up to 470 Gg CO2-equivalents per year can be achieved with potential costs savings for TOD users. The potential for respiratory impacts (PM10-equivalents) and smog formation can be reduced by 28-35%. The shift from business-as-usual growth to transit-oriented development can decrease user costs by $3,100 per household per year over the building lifetime, despite higher rental costs within the mixed-use development.
ContributorsNahlik, Matthew (Author) / Chester, Mikhail V (Thesis advisor) / Pendyala, Ram (Committee member) / Fraser, Matthew (Committee member) / Arizona State University (Publisher)
Created2014
Description
Traffic congestion is a major externality in modern transportation systems with negative economic, environmental and social impacts. Freeway bottlenecks are one of the key elements besides the demand for travel by automobiles that determine the extent of congestion. The primary objective of this research is to provide a better understanding of factors for variations in bottleneck discharge rates. Specifically this research seeks to (i) develop a methodology comparable to the rigorous methods to identify bottlenecks and measure capacity drop and its temporal (day to day) variations in a region, (ii) understand the variations in discharge rate of a freeway weaving bottleneck with a HOV lane and (iii) understand the relationship between lane flow distribution and discharge rate on a weaving bottleneck resulted from a lane drop and a busy off-ramp. In this research, a methodology has been developed to de-noise raw data using Discrete Wavelet Transforms (DWT). The de-noised data is then used to precisely identify bottleneck activation and deactivation times, and measure pre-congestion and congestion flows using Continuous Wavelet Transforms (CWT). To this end a methodology which could be used efficiently to identify and analyze freeway bottlenecks in a region in a consistent, reproducible manner was developed. Using this methodology, 23 bottlenecks have been identified in the Phoenix metropolitan region, some of which result in long queues and large delays during rush-hour periods. A study of variations in discharge rate of a freeway weaving bottleneck with a HOV lane showed that the bottleneck discharge rate diminished by 3-25% upon queue formations, however, the discharge rate recovered shortly thereafter upon high-occupancy-vehicle (HOV) lane activation and HOV lane flow distribution (LFD) has a significant effect on the bottleneck discharge rate: the higher the HOV LFD, the lower the bottleneck discharge rate. The effect of lane flow distribution and its relationship with bottleneck discharge rate on a weaving bottleneck formed by a lane drop and a busy off-ramp was studied. The results showed that the bottleneck discharge rate and lane flow distribution are linearly related and higher utilization of the median lane results in higher bottleneck discharge rate.
ContributorsKandala, Srinivasa Srivatsav (Author) / Ahn, Soyoung (Thesis advisor) / Pendyala, Ram (Committee member) / Kaloush, Kamil (Committee member) / Arizona State University (Publisher)
Created2014
Description
This dissertation research contributes to the advancement of activity-based travel forecasting models along two lines of inquiry. First, the dissertation aims to introduce a continuous-time representation of activity participation in tour-based model systems in practice. Activity-based travel demand forecasting model systems in practice today are largely tour-based model systems that simulate individual daily activity-travel patterns through the prediction of day-level and tour-level activity agendas. These tour level activity-based models adopt a discrete time representation of activities and sequence the activities within tours using rule-based heuristics. An alternate stream of activity-based model systems mostly confined to the research arena are activity scheduling systems that adopt an evolutionary continuous-time approach to model activity participation subject to time-space prism constraints. In this research, a tour characterization framework capable of simulating and sequencing activities in tours along the continuous time dimension is developed and implemented using readily available travel survey data. The proposed framework includes components for modeling the multitude of secondary activities (stops) undertaken as part of the tour, the time allocated to various activities in a tour, and the sequence in which the activities are pursued.
Second, the dissertation focuses on the implementation of a vehicle fleet composition model component that can be used not only to simulate the mix of vehicle types owned by households but also to identify the specific vehicle that will be used for a specific tour. Virtually all of the activity-based models in practice only model the choice of mode without due consideration of the type of vehicle used on a tour. In this research effort, a comprehensive vehicle fleet composition model system is developed and implemented. In addition, a primary driver allocation model and a tour-level vehicle type choice model are developed and estimated with a view to advancing the ability to track household vehicle usage through the course of a day within activity-based travel model systems. It is envisioned that these advances will enhance the fidelity of activity-based travel model systems in practice.
Second, the dissertation focuses on the implementation of a vehicle fleet composition model component that can be used not only to simulate the mix of vehicle types owned by households but also to identify the specific vehicle that will be used for a specific tour. Virtually all of the activity-based models in practice only model the choice of mode without due consideration of the type of vehicle used on a tour. In this research effort, a comprehensive vehicle fleet composition model system is developed and implemented. In addition, a primary driver allocation model and a tour-level vehicle type choice model are developed and estimated with a view to advancing the ability to track household vehicle usage through the course of a day within activity-based travel model systems. It is envisioned that these advances will enhance the fidelity of activity-based travel model systems in practice.
ContributorsGarikapati, Venu Madhav (Author) / Pendyala, Ram M. (Thesis advisor) / Zhou, Xuesong (Committee member) / Lou, Yingyan (Committee member) / Arizona State University (Publisher)
Created2014
Description
Public-Private Partnerships (P3) in North America have become a trend in the past two decades and are gaining attention in the transportation industry with some large scale projects being delivered by this approach. This is due to the need for alternative funding sources for public projects and for improved efficiency of these projects in order to save time and money. Several research studies have been done, including mature markets in Europe and Australia, on the cost and schedule performance of transportation projects but no similar study has been conducted in North America. This study focuses on cost and schedule performance of twelve P3 transportation projects during their construction phase, costing over $100 million each, consisting of roads and bridges only with no signature tunnels. The P3 approach applied in this study is the Design-Build-Finance-Operate-Maintain (DBFOM) model and the results obtained are compared with similar research studies on North American Design-Build (DB) and Design-Bid-Build (DBB) projects. The schedule performance for P3 projects in this study was found to be -0.23 percent versus estimated as compared to the 4.34 percent for the DBB projects and 11.04 percent for the DB projects in the Shrestha study, indicating P3 projects are completed in less time than other methods. The cost performance in this study was 0.81 percent for the P3 projects while in the Shrestha study the average cost increase for the four DB projects was found to be 1.49 percent while for the DBB projects it was 12.71 percent, again indicating P3 projects reduce cost compared to other delivery approaches. The limited number of projects available for this study does not allow us to draw an explicit conclusion on the performance of P3s in North America but paves the way for future studies to explore more data as it becomes available. However, the results in this study show that P3 projects have good cost and schedule adherence to the contract requirements. This study gives us an initial comparison of P3 performance with the more traditional approach and shows us the empirical benefits and limitations of the P3 approach in the highway construction industry.
ContributorsBansal, Ankita (Author) / Chasey, Allan (Thesis advisor) / Gibson, Edd (Committee member) / Pendyala, Ram (Committee member) / Arizona State University (Publisher)
Created2012
Description
Recently, automation, shared use, and electrification are proposed and viewed as the “three revolutions” in the future transportation sector to significantly relieve traffic congestion, reduce pollutant emissions, and increase transportation system sustainability. Motivated by the three revolutions, this research targets on the passenger-focused scheduled transportation systems, where (1) the public transit systems provide high-quality ridesharing schedules/services and (2) the upcoming optimal activity planning systems offer the best vehicle routing and assignment for household daily scheduled activities.
The high quality of system observability is the fundamental guarantee for accurately predicting and controlling the system. The rich information from the emerging heterogeneous data sources is making it possible. This research proposes a modeling framework to systemically account for the multi-source sensor information in urban transit systems to quantify the estimated state uncertainty. A system of linear equations and inequalities is proposed to generate the information space. Also, the observation errors are further considered by a least square model. Then, a number of projection functions are introduced to match the relation between the unique information space and different system states, and its corresponding state estimate uncertainties are further quantified by calculating its maximum state range.
In addition to optimizing daily operations, the continuing advances in information technology provide precious individual travel behavior data and trip information for operational planning in transit systems. This research also proposes a new alternative modeling framework to systemically account for boundedly rational decision rules of travelers in a dynamic transit service network with tight capacity constraints. An agent-based single-level integer linear formulation is proposed and can be effectively by the Lagrangian decomposition.
The recently emerging trend of self-driving vehicles and information sharing technologies starts creating a revolutionary paradigm shift for traveler mobility applications. By considering a deterministic traveler decision making framework, this research addresses the challenges of how to optimally schedule household members’ daily scheduled activities under the complex household-level activity constraints by proposing a set of integer linear programming models. Meanwhile, in the microscopic car-following level, the trajectory optimization of autonomous vehicles is also studied by proposing a binary integer programming model.
The high quality of system observability is the fundamental guarantee for accurately predicting and controlling the system. The rich information from the emerging heterogeneous data sources is making it possible. This research proposes a modeling framework to systemically account for the multi-source sensor information in urban transit systems to quantify the estimated state uncertainty. A system of linear equations and inequalities is proposed to generate the information space. Also, the observation errors are further considered by a least square model. Then, a number of projection functions are introduced to match the relation between the unique information space and different system states, and its corresponding state estimate uncertainties are further quantified by calculating its maximum state range.
In addition to optimizing daily operations, the continuing advances in information technology provide precious individual travel behavior data and trip information for operational planning in transit systems. This research also proposes a new alternative modeling framework to systemically account for boundedly rational decision rules of travelers in a dynamic transit service network with tight capacity constraints. An agent-based single-level integer linear formulation is proposed and can be effectively by the Lagrangian decomposition.
The recently emerging trend of self-driving vehicles and information sharing technologies starts creating a revolutionary paradigm shift for traveler mobility applications. By considering a deterministic traveler decision making framework, this research addresses the challenges of how to optimally schedule household members’ daily scheduled activities under the complex household-level activity constraints by proposing a set of integer linear programming models. Meanwhile, in the microscopic car-following level, the trajectory optimization of autonomous vehicles is also studied by proposing a binary integer programming model.
ContributorsLiu, Jiangtao (Author) / Zhou, Xuesong (Thesis advisor) / Pendyala, Ram (Committee member) / Mirchandani, Pitu (Committee member) / Lou, Yingyan (Committee member) / Arizona State University (Publisher)
Created2018
Description
Priced Managed Lanes (MLs) have been increasingly advocated as one of the effective ways to mitigating congestion in recent years. This study explores a new and innovative pricing strategy for MLs called Travel Time Refund (TTR). The proposed TTR provides an additional option to paying drivers that insures their travel time by issuing a refund to the toll cost if they do not reach their destination within specified travel times due to accidents or other unforeseen circumstances. Perceived benefits of TTR include raised public acceptance towards priced MLs, utilization increase of HOV/HOT lanes, overall congestion mitigation, and additional funding for relevant transportation agencies. To gauge travelers’ interests of TTR and to analyse its possible impacts, a stated preference (SP) survey was performed. An exploratory and statistical analysis of the survey responses revealed negative interest towards HOT and TTR option in accordance with common wisdom and previous studies. However, it is found that travelers are less negative about TTR than HOT alone; supporting the idea, that TTR could make HOT facilities more appealing. The impact of travel time reliability and latent variables representing psychological constructs on travelers’ choices in response to this new pricing strategy was also analysed. The results indicate that along with travel time and reliability, the decision maker’s attitudes and the level of comprehension of the concept of HOT and TTR play a significant role in their choice making. While the refund option may be theoretically and analytically feasible, the practical implementation issues cannot be ignored. This study also provides a discussion of the potential implementation considerations that include information provision to connected and non-connected vehicles, distinction between toll-only and refund customers, measurement of actual travel time, refund calculation and processing and safety and human factors issues. As the market availability of Connected and Automated Vehicles (CAVs) is prognosticated by 2020, the potential impact of such technologies on effective demand management, especially on MLs is worth investigating. Simulation analysis was performed to evaluate the system performance of a hypothetical road network at varying market penetration of CAVs. The results indicate that Connected Vehicles (CVs) could potentially encourage and enhance the use of MLs.
ContributorsVadlamani, Sravani (Author) / Lou, Yingyan (Thesis advisor) / Pendyala, Ram (Committee member) / Zhou, Xuesong (Committee member) / Grimm, Kevin (Committee member) / Arizona State University (Publisher)
Created2018
Description
The purpose of this project was to design a new railroad crossing for pedestrians and bicyclists in mid-block or urban areas. In order to develop a successful design, the needs of the railroad, the end-users, and the city governments were researched and converted into measurable engineering requirements. For the railroad companies, the most important need was a crossing that presents an effective barrier to users while a train is in the area. For bicyclists and pedestrians (the end-users), the most important need was for the crossing to be both reliable and easily accessible. For the city governments, the most important need was a crossing that is inexpensive yet sturdy. The approach to this project was similar to the approach used in many engineering design processes. First is the Introduction, which provides an overview of the issue and presents the full problem statement. Next is the Research of Prior Art, which details the past solutions to railroad crossings as well as the 3 E's of railroad crossing safety. After this, the customer needs are discussed in the Needs to Requirements section and the process of converting these into measurable engineering requirements is shown. Next, various conceptual design options are shown in the Conceptual Design section and a final conceptual design is chosen based on adherence to the stated requirements. This final conceptual design is then taken into the preliminary design phase and refined until it becomes the final preliminary design. After the Final Preliminary Design Description, the Project Conclusions and Recommendations are presented. Due to time and monetary constraints, this project ends after the preliminary design stage. Despite this, the conclusion of this project is that the final design presented here will be successful if additional resources are obtained to move it forward into the detailed design phase. For now, this project has come to a halt due to UP's reluctance to allow any additional railroad crossings in the Phoenix and Tempe, Arizona areas. It is recommended that city officials and bicyclist/pedestrian action groups continue talks with UP until they agree to allow additional crossings to be built that are geared towards non-motorized users.
ContributorsJones, Mitchell Drexel (Author) / Kuby, Michael (Thesis director) / Lou, Yingyan (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2015-05
Description
Transit-oriented developments (TODs) are a promising strategy to increase public transit use and, as a result, reduce personal car travel. By using TOD infill to increase urban population density and encourage transportation mode-shifting, the potential exists to reduce life-cycle per capita energy use and environmental impacts of the interdependent infrastructure systems. This project specifically examined the Gold Line of light rail and Orange Line of bus rapid transit in Los Angeles, CA.
ContributorsNahlik, Matthew John (Author) / Chester, Mikhail (Thesis director) / Pendyala, Ram (Committee member) / Pincetl, Stephanie (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor)
Created2013-05
Description
Arizona's transportation infrastructure is in need of an update. The American Society of Civil Engineers (ASCE) State Infrastructure 2017 Report Card scores Arizona's roads at a D+ and Arizona's bridges at a B. These grades are indicative that the serviceability levels of the roads and bridges are less than adequate. These grades may seem tolerable in light of a national bridge C+ grade and a national road D grade, but the real problem lies in Arizona's existing funding gap that is in danger of exponentially increasing in the future. With an influx of vehicles on Arizona's roads and bridges, the cost of building, repairing, and maintaining them will grow and cause a problematic funding shortage. This report explores the current state of Arizona's roads and bridges as well as the policy and funding sources behind them, using statistics from the ASCE infrastructure report card and the Federal Highway Administration. Additionally, it discusses how regular, preventative maintenance for transportation infrastructure is the economically responsible choice for the state because it decreases delays and fuel expenses, prevents possible catastrophes, and increases human safety. To prioritize preventative transportation infrastructure maintenance, the common mentality that allows it to be sidelined for more newsworthy projects needs to be changed. Along with gaining preventative maintenance revenues through increasing vehicular taxes and fees, encouraging transportation policymakers and politicians to make economic decisions in favor of maintenance rather than waiting until failure is a reliable way to encourage regular, preventative maintenance.
ContributorsBurdett, Courtney (Author) / Hjelmstad, Keith (Thesis director) / Pendyala, Ram (Committee member) / Civil, Environmental and Sustainable Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Managed Lanes (MLs) have been increasingly advocated as a way to reduce congestion. This study provides an innovative new tolling strategy for MLs called the travel time refund (TTR). The TTR is an “insurance” that ensures the ML user will arrive to their destination within a specified travel time savings, at an additional fee to the toll. If the user fails to arrive to their destination, the user is refunded the toll amount.
To gauge interest in the TTR, a stated preference survey was developed and distributed throughout the Phoenix-metropolitan area. Over 2,200 responses were gathered with about 805 being completed. Exploratory data analysis of the data included a descriptive analysis regarding individual and household demographic variables, HOV usage and satisfaction levels, HOT usage and interests, and TTR interests. Cross-tabulation analysis is further conducted to examine trends and correlations between variables, if any.
Because most survey takers were in Arizona, the majority (53%) of respondents were unfamiliar with HOT lanes and their practices. This may have had an impact on the interest in the TTR, although it was not apparent when looking at the cross-tabulation between HOT knowledge and TTR interest. The concept of the HOT lane and “paying to travel” itself may have turned people away from the TTR option. Therefore, similar surveys implementing new HOT pricing strategies should be deployed where current HOT practices are already in existence. Moreover, introducing the TTR concept to current HOT users may also receive valuable feedback in its future deployment.
Further analysis will include the weighting of data to account for sample bias, an exploration of the stated preference scenarios to determine what factors were significant in peoples’ choices, and a predictive model of those choices based on demographic information.
To gauge interest in the TTR, a stated preference survey was developed and distributed throughout the Phoenix-metropolitan area. Over 2,200 responses were gathered with about 805 being completed. Exploratory data analysis of the data included a descriptive analysis regarding individual and household demographic variables, HOV usage and satisfaction levels, HOT usage and interests, and TTR interests. Cross-tabulation analysis is further conducted to examine trends and correlations between variables, if any.
Because most survey takers were in Arizona, the majority (53%) of respondents were unfamiliar with HOT lanes and their practices. This may have had an impact on the interest in the TTR, although it was not apparent when looking at the cross-tabulation between HOT knowledge and TTR interest. The concept of the HOT lane and “paying to travel” itself may have turned people away from the TTR option. Therefore, similar surveys implementing new HOT pricing strategies should be deployed where current HOT practices are already in existence. Moreover, introducing the TTR concept to current HOT users may also receive valuable feedback in its future deployment.
Further analysis will include the weighting of data to account for sample bias, an exploration of the stated preference scenarios to determine what factors were significant in peoples’ choices, and a predictive model of those choices based on demographic information.
ContributorsArcher, Melissa (Author) / Lou, Yingyan (Thesis advisor) / Chester, Mikhail (Committee member) / Zhou, Xuesong (Committee member) / Arizona State University (Publisher)
Created2015