Matching Items (1,855)
Filtering by
- Creators: Debussy, Claude, 1862-1918
- Status: Published
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
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
ContributorsDebussy, Claude, 1862-1918 (Composer)
ContributorsDebussy, Claude, 1862-1918 (Composer)
ContributorsDebussy, Claude, 1862-1918 (Composer)
ContributorsDebussy, Claude, 1862-1918 (Composer)
ContributorsDebussy, Claude, 1862-1918 (Composer)
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