MS Thesis

Off-Street Parking Cost Forecasting Models for Southern California

Publication Date

June 29, 2014

Author(s)

Biling Liu

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

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Abstract

Parking cost is an important and sensitive factor in understanding travel behavior and is typically utilized in the mode choice model of regional demand forecasting models. There are various socio-economics variables that can affect the value of parking cost by employment type, time periods, and trip purposes. In this study, a set of parking cost forecasting models are developed using survey data and local socio-economic data with the objective of identifying parking cost patterns and forecasting future parking costs. This study first summarizes methods applied in previous parking cost forecasting models. Two categories of models were estimated. The first category does not consider parking space supply as a factor in forecasting TAZ parking; the second category considers both parking space supply and parking demand as explanatory variables. For each category, using current off-street parking cost survey data, linear regression models are built for hourly, daily and monthly pricing for SCAG Tier 2 Transportation Analysis Zones (TAZ) using R and Matlab. Daily parking rates are set as the base rates to generate the hourly and monthly parking cost models. The consideration of parking demand is a major contribution of this study, with demand generated based on home-based-work trip attractions for commuters by income groups in all models. This study found that daily parking rates can be explained by total employment, the proportion of office to total jobs, and the proportion of multiple to total households. Hourly parking cost can be explained based on daily parking rates and travel behavior associated with education, hospital, finance, entertainment and other employment types. The monthly parking cost model is built base on both daily and hourly parking rates as independent variables. Future work includes, integration of on-street parking costs with the current models for off-street parking.

Phd Dissertation

Estimating Emissions by Modeling Freeway Vehicle Speed Profiles Using Point Detector Data

Publication Date

June 14, 2014

Author(s)

Jin Choi

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience Intelligent Transportation Systems, Emerging Technologies, & Big Data Zero-Emission Vehicles & Low-Carbon Fuels

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Abstract

A method for accurate emissions estimation that will contribute to promoting public health has been increasingly important. The purpose of this study is to develop a novel method that is designed to make accurate real-time emissions estimation from individual vehicles on freeways possible. The benefit of this method is that it can overcome the weakness of macroscopic emissions estimation methods, which underestimated emissions. The most distinguishing feature of the Speed Profile Estimation (SPE) method is that it uses a speed profile (SP) that is generated by the sum of a basic SP (BSP), which is calculated by the basic travel information of an individual vehicle obtained from vehicle reidentification (REID), and a residual SP (RSP), which is estimated by categorized traffic information. In order to estimate RSP this research employs Autoregressive (AR) model and Fourier series (FS). And to find the parameters of RSP, the total absolute difference between actual SP emissions and estimated SP emissions was optimized by genetic algorithm. For this, parameters are calculated for all possible combinations of three categorizations and clusters by K-mean clustering. Individual vehicle trajectories from two freeways, US101 and I-80, were provided by the Next Generation Simulation (NGSIM) dataset. US101 was examined for calibration, and I-80 for validation. And then, transferability tests were conducted for various section distances to verify model transferability. Finally, REID is simulated with low vehicle signatures match rates to test its applicability to real situations. Unlike previous methods, the SPE is notable for its real-time, transferable, reliable, and cost efficient emissions estimation. The calibration and validation account only 4.0 % and 4.1 % MAPEs, respectively. Moreover, transferability tests showed that MAPEs are lower than 4.4 % in both longer and shorter section distances. Furthermore, REID simulation increases only 0.2 % MAPE even in low vehicle signatures match rates, which is lower than 5 % MAPE in emissions estimation. Any signal-like formulation other than AR or FS can perform better emissions estimation when it replaces the RSP. Also, in this research the SPE method was calibrated only for LOS F, when it is arguably of greatest value, but further research should be coordinated to extend the models in other possible traffic conditions such as LOS ÃE.

Phd Dissertation

Assessing costs and benefits of the kaohsiung rail system

Publication Date

June 14, 2014

Author(s)

Chung Yeh

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

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Abstract

This dissertation assesses costs and benefits of two recent public rail transit systems in Kaohsiung, Taiwan’s second largest city: Kaohsiung’s mass rapid transit (MRT) system, which was completed and inaugurated in 2008 and Kaohsiung light rail transit (LRT) loop line, which is now under construction. I first focus on the benefits of the opening of Kaohsiung’s MRT system as reflected in the price of apartments with elevators. I combine two stage least squares with geographically weighted regression to analyze transactions of apartments with elevators in 2007 and 2009. This approach allows accounting for the joint determination of time-on-market information (TOM) and price while allowing hedonic parameters to vary spatially. Results show that the opening of the MRT had a statistically significant and positive impact on the value of apartments with elevators. However, accounting for TOM has a negligible impact on my results. Second, I apply the theory of real options to capture uncertainty in operating revenues and costs in the context of build-operate-transfer (BOT) and operate-transfer (OT) contracts for Kaohsiung’s LRT loop line project. Unlike the traditional net present value (NPV) approach, real options analysis includes option values embedded in a project. Here, I rely on the binomial pricing approach to explore the value of the options to abandon and to expand the project. My findings show that the options to abandon or expand the LRT system are not sufficient to make a BOT contract attractive to a private firm, even under the best case scenario; however, accounting for the value of these options makes an OT contract at least 10% more attractive. These results show that accounting for uncertainty in large urban transportation projects can be important although the value of flexibility may not be sufficient to offset large construction costs.

MS Thesis

Comparison of alternate feedback methods for the four-step model

Publication Date

March 29, 2014

Author(s)

Chenying Qin

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

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Abstract

The purpose of this thesis is to study the feasibility and effectiveness of different feedback methods as applied to Miasma Beach Project. There are two methods of feedback, direct and averaging link volumes via MSA, each with and without averaging of OD volumes, totally is four methods, are introduced to the Four-Step Model based on Miasma Beach Project. Also, the RMSE of link flow and OD matrix, and VHT value are in use to measure the result of each feedback solution. After compared the result and confirmed the “true solution” of the model, a short conclusion of is drawn. It’s very clear that any approach to feedback makes significant corrections to the FSM result, the model consistency is much improved

Phd Dissertation

Simulation Study of Day-Night Variations in Emissions Impacts and Network Augmentation Schemes: An Application to PierPASS Policy for Port Trucks in California

Publication Date

June 1, 2014

Author(s)

Ankoor Bhagat

Areas of Expertise

Freight, Logistics, & Supply Chain Safety, Public Health, & Mobility Justice

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Abstract

Freight operations are critical to our prosperity, but they also generate substantial external costs in the form of additional congestion, air pollution, and health impacts. Unfortunately these external costs are not well understood. In this dissertation, I focus on the drayage trucks that serve the San Pedro Bay Ports (or SPBP, i.e. the Ports of Los Angeles and Long Beach in Southern California), which is the largest port complex in the country. This research focuses on the PierPASS program, which shifts drayage trucks traffic from mid-day and peak hours to the evening and night hours. External costs from drayage trucks remain a major concern for communities adjacent to the ports because they bear a disproportionate fraction of the health impacts (respiratory and cardiovascular illnesses, cancers, and premature deaths) associated with the pollution generated by ports operations. In this context, the purpose of my dissertation is analyze the impacts of shifting freight traffic to off-peak periods with an emphasis on congestion, air pollution (NOx, and PM) and related health impacts. This impact analysis was conducted using a framework that integrates microscopic traffic simulation with emission estimation, air dispersion, and a health impact assessment. The research also developed a new approach for origin-destination demand estimation on large microscopic simulation network that is made by augmenting an existing simulation network. Thus the research makes both policy analysis and methodological contributions, and is expected to help enable policy makers to craft cleaner logistics policies. I found that PierPASS had little impact on traffic congestion and on overall emissions of various pollutants. However, PierPASS had a significant impact on the distribution of these emissions between day and night. During night-time, total port truck emissions increased by 71% for NOx and 72% for PM, while day-time emissions decreased by 9% for both NOx and PM. My dispersion analysis shows that PierPASS increased air pollutant concentrations during both day time and night time because of boundary layer effects. Finally, my health impact analyses using EPA’s BenMAP model show that the annual social costs due to PierPASS are $438 million.

Phd Dissertation

ReMuLAA - A new algorithm for the route choice problem

Publication Date

March 14, 2014

Author(s)

Pedro Camargo

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

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Abstract

A new framework for analyzing the choice set formation for route choice models in transportation networks is presented and an algorithm is proposed. The algorithm is tested against a sample of GPS data for heavy trucks for the State of California. The results are presented in detail along with an analysis of both their qualitative and quantitative merits. A new algorithm for the route choice problem is also presented and its results analyzed against the state of the practice and state of the art. This new algorithm, ReMuLAA, is also the first known closed solution algorithm for the route choice problem using the Multinomial Logit Model (MNL) for an entire class of networks (Directed Acyclic Networks) without explicit route enumeration. A correction for the MNL model to account for route overlapping is also presented and the results are compared with other state-of-the-art route choice algorithms. The results of the application of ReMuLAA in a real world model are also presented and its advantages discussed.

MS Thesis

Feedback with Alternate Trip Assignment Approaches in the Four-Step Model

Publication Date

March 29, 2014

Author(s)

Zhen Li

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

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Abstract

The traditional Four-Step Model is widely used in the Transportation Planning and Forecasting Process. However, the model itself has a structural defect: it is only equilibrium in terms of Trip Assignment. Thus it is often viewed as an inadequate, partial equilibrium model. To achieve an overall equilibrium in the Transportation Planning and Forecasting Process, a feedback process can be introduced into the Four-Step Model. The objective of this research is to incorporate different feedback methods into the traditional Four-Step Modeling process to improve model performance. The specific approach herein is to examine the relative performance of direct and averaging feedback methods, and then to investigate the convergence of this two approaches by replacing User Equilibrium trip assignment with All-or-Nothing trip assignment during each feedback loop, but not in the original four step model application. An evaluation and comparison of these methods is presented. Two measures of effectiveness, the Root-Mean-Square Error (RMSE) and Total Vehicle Hours Traveled (VHT), are employed to test the convergence and evaluate the methods.

research report

Quantifying the Effect of Local Government Actions on VMT

Publication Date

February 13, 2014

Associated Project

Quantifying Effect of Local Government Actions on Vehicle Miles Traveled (VMT)

Author(s)

Deborah Salon, Marlon Boarnet, Patricia (Pat) Mokhtarian

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

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Abstract

This research uses empirical analysis of travel survey data to quantify how much Californians will change the amount that they drive in response to changes in land use and transport system variables. The study improves upon past research in three key ways. First, a dataset comprising merged information from five California-based household travel surveys was assembled. Second, a novel approach to control for residential self-selection was developed. Third, understanding heterogeneity in effects of variables on vehicle miles of travel (VMT) across two important dimensions – neighborhood type and trip type — was a focus. The effects of some land use and transport system characteristics do depend on neighborhood type, in ways that are intuitive but had not previously been empirically verified. Results of this research are embedded in the VMT Impact spreadsheet tool, which allows users to easily see the implications of this work for any census tract, city, or region in California.

MS Thesis

Left-turn elimination network analysis

Publication Date

December 30, 2013

Associated Project

Improving Transport Performance: The Case of Left Turns

Author(s)

Cunxiang (Nicole) Mi

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience

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Abstract

Left-turn movement volume takes small percentage of approach volume, however case delay to the majority of traffic flow at an intersection. Left-turn movement has longest averaged delay at an intersection itself. The idea of eliminating left-turn movement is to force a small number of left-turn trips to re-routing, as a results, all other trips would have less delay at an intersection. Elimination of some left-turn movements at a defined network may help improving network performance in term of network travel time, thus, a higher level of system optimization can be achieved. A network analysis is performed to compare network performance before and after left-turn elimination applied. Traffic assignment result is expected to be different because of trips re-routing after left-turn elimination.. Intersection control delay is expected to decrease at the intersection that where left-turn elimination is applied. As a result, network travel time is expected to drop because of the saving at intersection control delay. Signalized intersection control delay is a key of this study. Trips re-routing may happen because of prohibited left-turn movement, as well as the difference in turn penalty per movement if it is assigned, which would affect shortest path calculation. Trip re-routing may cause increase in total turn movement volume in network.

Phd Dissertation

Interregional Commodity Flow Model Using Structural Equation Modeling: Application to the California Statewide Freight Forecasting Model

Publication Date

December 14, 2013

Associated Project

California Statewide Freight Forecasting Model

Author(s)

Fatemeh Ranaiefar

Areas of Expertise

Freight, Logistics, & Supply Chain

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Abstract

Freight forecasting models are data intensive and may require many explanatory variables to achieve prediction accuracy. One problem, particularly in the United States, is that public data sources are usually available only at highly aggregate geographic levels, while models with more disaggregate geographic levels are required for regional freight transportation planning. A second problem is that supply chain effects are often ignored or modeled with economic input-output models which lack explanatory power. This study addresses these challenges by considering a Structural Equation Modeling approach, that is not confined to a specific spatial structure as spatial regression models would be, and allows for correlations between industries. The goal of the proposed methodology is to design a reliable and policy sensitive modeling framework for long term commodity flow forecasting that makes the best use of public available data sources. Practicality and improvement over previously available freight generation and distribution models are the highlights of this approach. There are two primary developed in this study. The first one is a structural commodity generation model. The second model is the Structural Equations for Multi-Commodity OD Distribution (SEMCOD) model. The proposed framework is implemented as a primary module in California Statewide Freight Forecasting Model (CSFFM) and will be used to update the California Transportation Plan (CTP 2015). The models are specified and estimated based on FAF3 data. It is shown that the proposed modeling framework provides a better fit to the data than independent regression models for each commodity. The three components of the models are: direct and indirect effects, supply chain elasticities at zone level and at origin-destination level, and intra-zonal supply-demand interactions. A validation of the geographic scalability of the model is conducted using a zoning system consisting of 97 county or sub-county zones in California.