Phd Dissertation

Freeway Traffic Parameter and State Estimation with Eulerian and Lagrangian Data

Publication Date

March 1, 2016

Author(s)

Zhe (Jared) Sun

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience Intelligent Transportation Systems, Emerging Technologies, & Big Data

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Abstract

The purpose of this study is to develop a traffic estimation framework which combines different data sources to better reconstruct the traffic states on the freeways. The framework combines both traffic parameter and state estimation in the same work flow, which resolves the inconsistency issue of most existing traffic state estimation methods.

To examine the quality of the traffic sensor data, the study starts with proposing the network sensor health problem (NSHP). The optimal set of sensors is selected from all sensors such that the violation of flow conservation is minimized. The health index for individual detector is then calculated based on the solutions. We also developed a tailored greedy search algorithm to find the solutions effectively. The proposed method is tested using the loop detector data from PeMS on a stretch of the SR-91 freeway. We compared the results with PeMS health status and found considerable level of consistency.

Two different traffic state estimation methods are proposed based on the data availability and traffic states. The LoopReid method is derived from the Newell’s simplified kinematic wave model by assuming the whole road segment is fully congested. We formulate a least square optimization problem to find the initial states and traffic parameters based on the first-in-first-out principle and the congested part of the Newell’s model. While developing the LoopCT method, we derived a counterpart of the Newell’s kinematic wave model in the Lagrangian coordinates under Eulerian boundary conditions. This model also leads to a new method to estimate vehicle trajectories within a road segment. We formulate a least square optimization problem in initial states and traffic parameters which works for mixed traffic states. The two estimation methods turned out to be highly related and the LoopCT method degenerates to the LoopReid method when the traffic is fully congested. The two methods are validated using two datasets from the NGSIM project. Both methods achieved considerable level of accuracy at reconstructing the traffic states and parameters.

research report

Promoting Peer-to-Peer Ridesharing Services as Transit System Feeders

Publication Date

May 1, 2016

Associated Project

Promoting Peer-to-Peer Ridesharing Services as Transit System Feeders

Author(s)

R. (Jay) Jayakrishnan, Neda Masoud, Jiangbo (Gabe) Yu, Daisik (Danny) Nam

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

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Abstract

Peer-to-peer ridesharing is a recently emerging travel alternative that can help accomodate the growth in urban travel demand, and alleviate some of the current problems such as excessive vehicular emissions. Prior ridesharing projects suggest that the demand for ridesharing is usually shifted from transit, while its true benefits are obtained only if the demand shifts from private autos. This project studies the potential of efficient real-time ride-matching algorithms to augment demand for transit by reducing private auto use. The Los Angeles Metro red line is considered for a case study, since it has recently shown declining ridership. A mobile application with an innovative ride-matching algorithm is developed as a decision support tool that suggests transit-ridership and rideshare routes. The app also facilitates peer-to-peer communication of users via smart phones. For successful ride-sharing, strategically selecting locations for individuals to get on/off rideshare vehicles is crucial, along with the pricing structure for rides. These can be adjusted dynamically based on the feedback from the app-users. A parametric study of the application of real-time ride-matching algorithms using simulated demand in conjunction with the SCAG model for the selected study are is conducted.

published journal article

California Vehicle Inventory and Use Survey: Pilot Study Insights

Publication Date

January 1, 2016

Associated Project

California Vehicle Inventory and Use Survey

Author(s)

Kyungsoo Jeong, Andre (Yeow Chern) Tok, Stephen Ritchie, Jun Park

Areas of Expertise

Freight, Logistics, & Supply Chain Travel Behavior, Land Use, & the Built Environment

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Abstract

With the discontinuation of the national Vehicle Inventory and Use Survey (VIUS) in the United States in 2002, insufficient data have been available for well more than a decade on commercial vehicle activity. The goal of this pilot survey effort was to develop a preliminary design for a proposed California Vehicle Inventory and Use Survey (Cal-VIUS) and to test it with a scaled-down sample to provide guidance on the full-scale survey design. The sample was drawn from vehicle records obtained from the California Department of Motor Vehicles and International Registration Plan data sets by using a stratified sampling technique to capture intrastate and Interstate commercial vehicle activity in California. Limitations identified in the 2002 VIUS were addressed in the Cal-VIUS pilot survey questionnaire, which was administered on an online survey platform (http://surveyanalytics.com). The questionnaire was designed to collect annual and trip-based activity data through two complementary surveys: a web-based fleet manager survey and a smartphone app-based driver survey (with web-based option). These surveys were conducted between December 29, 2014, and February 28, 2015, and between February 24 and February 26, 2015, respectively. Results from the web-based fleet manager survey showed that the stratification design was adequate to describe the heterogeneous characteristics of vehicle activities between strata with respect to vehicle miles traveled within California. The driver survey was not fully tested because of limited response. Results from the pilot survey are expected to provide valuable insights to those who are developing future truck-related survey studies.

research report

Development of a New Methodology to Characterize Truck Body Types along California Freeways

Publication Date

January 1, 2016

Associated Project

Development of a New Methodology to Characterize Truck body Types Along California Freeways

Author(s)

Stephen Ritchie, Andre (Yeow Chern) Tok

Areas of Expertise

Freight, Logistics, & Supply Chain Intelligent Transportation Systems, Emerging Technologies, & Big Data

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Abstract

The purpose of this project was to develop a new methodology to characterize truck body types along California Freeways. With new information on truck activity by body types, results from this study are expected to improve heavy duty vehicle classification in the Emission Factors (EMFAC) model and the California Vehicle Activity Database (CalVAD), and provide critical data that is required for the analysis of freight movement that will benefit the California Statewide Freight Forecasting Model (CSFFM) and other freight- or truck-related studies.
This study sought to develop two types of classification models: the first from the combination of inductive loop signature and weigh-in-motion (WIM) data, and the second from standalone inductive loop signature data. The key benefit of these models is their readiness for implementation at existing traffic detector infrastructure such as inductive loop detector (ILD) and WIM sites. It was demonstrated through this study that the modifications to existing inductive loop detector and WIM sites were minimal, and did not compromise existing operations. The standalone inductive signature classification model (designed for implementation an existing ILD sites) demonstrated the ability to distinguish over 40 truck configurations, while the combined inductive loop signature and WIM classification model was able to identify over 60 truck types. These models were subsequently deployed at sixteen selected sites in the California San Joaquin Valley. A prototype web interface called the Truck Activity Monitoring System (TAMS, http://freight.its.uci.edu/tams) was designed to generate dynamic reports of the results via an interactive web-based user interface.
Other models developed in this study include a method for estimating truck volumes by a reduced number of body types from standalone WIM data, an optimal site selection model for determining the optimal sites for deployment of the advanced classification system developed in this study, and a method for estimating gross vehicle weight distributions at inductive loop detector sites instrumented with inductive signature technology by using data obtained from affiliated WIM sites.
The project was separated into three phases: proof-of-concept truck body classification models were developed in Phase 1; model enhancement was performed in Phase 2; and system deployment took place as Phase 3.

MS Thesis

Analysis of the 2000 SCAG Post-Census Regional Travel Survey and the 2012 California Household Travel Survey

Publication Date

December 31, 2015

Author(s)

Andrew Timothy

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

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Abstract

Results from the 2000 SCAG Post-Census Regional Travel Survey and the 2010-2012 California Household Travel Survey are used to study the demographics and characteristics of Imperial, Los Angeles, Orange, Riverside, San Bernardino, and Ventura counties. Graphs for each county are created to show pertinent data to transportation applications, such as the average number of vehicles a household owns or how many trips certain individuals make in one day. Studying both sets of data gives perspective on how the SCAG region has evolved over 12 years. The overwhelming majority of trips are still traveled by personal vehicle, despite walking trips seeing an increase over 2000, and trips are more frequent overall.

MS Thesis

Changes in Travel Patterns of Two-person Households in California between 2001 and 2012

Publication Date

December 31, 2015

Author(s)

Dhanya Pranab Kumar

Areas of Expertise

Travel Behavior, Land Use, & the Built Environment

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Abstract

The main objective of this thesis is to highlight the travel patterns of two-person households in California as captured in the 2000-2001 and 2010-2012 California Household Travel Surveys (CHTS). The intent is to present basic travel characteristics of households with two peoples who are couples, are employed and do not have kids at home (denoted as DINK – Dual Income No Kids at home) along with comparisons with two-person households who does not belong to the aforementioned category (NON-DINK) using the CHTS 2000-2001 and 2010-2012 datasets. The results highlight significant differences in travel patterns between the two categories, DINKs and NON-DINKs during the eleven years from 2001 to 2012. The average number of daily trips is higher for DINKs compared to NON-DINKs and the trip rate has reduced in 2012 compared to 2001 for both categories. Auto (driver of auto/truck/van) trips is the primary mode of travel for DINKs and NON_DINKs in CHTS 2001 and 2012. During the eleven years, there has been a decrease in auto trips and an increase in the percentages of passenger, bike, walk and transit trips. The primary trip purpose for DINKs are work or work-related, whereas the primary trip purpose for NON-DINKs are shopping/maintenance trips according to both survey results.

MS Thesis

Assessing the Impact of SB743 on Transportation Planning, Traffic Impact Analysis, and Level-of-Service

Publication Date

December 31, 2015

Author(s)

Oluseyi Ojuri

Areas of Expertise

Infrastructure Delivery, Operations, & Resilience Travel Behavior, Land Use, & the Built Environment

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Abstract

Since the implementation of CEQA in 1970, traffic impact analyses have been a key component in California’s land development. A current paradigm shift towards building and living sustainably has caused policy makers, engineers and planners to reexamine the policies that have been instituted. It has also influenced exploration of solutions that can change future developments. We must first analyze the established system of traffic impact analysis to determine the viability and potential benefits of measuring transportation network efficiency through factors highlighted in Senate Bill (SB) 743. These factors include vehicle miles travelled (VMT), fuel use or automobile trips generated. For the purpose of this paper, the focus will be on the VMT. When VMT analysis is applied on a project level, a list of key questions arise that are related to SB 743’s goals of reducing greenhouse gases, increasing multimodal transportation and developing appropriate metrics to conduct transportation analysis. A review of Senate Bill 743 text along with the Governor’s Office of Planning and Research report on the Bill paints a picture of what California’s future development will look like. Furthermore, an examination of travel trends and literature about current transportation analysis helps to evaluate the potential success of Senate Bill 743. In summary, Senate Bill 743 symbolizes a huge step towards carbon emission reduction and an excellent opportunity to start a conversation about making land development more sustainable in California. However, the bill leaves out the essential components of existing traffic impact analyses and employs a measure of environmental impact that does not reflect accessibility or multi-modal transportation.

Phd Dissertation

Modeling Shared-use Urban Mobility Systems to Increase System Performance

Publication Date

September 15, 2015

Author(s)

Robert Regue Grino

Areas of Expertise

Public Transit, Shared Mobility, & Active Transportation

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Abstract

Shared-use mobility systems, which enable users to have short-term access to transportation modes on an on-demand basis, have experienced tremendous growth over the last decade. However, most of the existing systems suffer from two confounding issues: the lack of modeling tools to understand, simulate and predict their behavior and the lack of integration with the existing transit network. To address those issues, this dissertation focuses on investigating the operational challenges of bikesharing systems, with an emphasis on the rebalancing operations and the modeling of a new mobility concept, Car2work, which builds upon existing carsharing ideas and successfully integrates with existing transit networks. A methodological framework to solve the bikesharing rebalancing problem is proposed. The novelties of the approach are that it is proactive instead of reactive, as the bike redistribution occurs before inefficiencies are observed, and uses the outputs of a demand-forecasting technique to decompose the inventory and the routing problem. The decomposition makes the problem scalable, responsive to operator inputs, and able to accommodate user-specific models. Simulation results based on data from the Hubway bikesharing system show that system performance improvements of 7% in the afternoon peak could be achieved.

Car2work main goal is to connect commuters with workplaces while leveraging the line-haul capabilities of existing public transit systems and guaranteeing a trip back home, efficiently tackling the “last mile” problem that is a limiting characteristic of public transit. It differs from the traditional dynamic-ridesharing approaches because it is designed for recurrent commuting trips where commuters announce their (multiple) trips in advanced and an automated all-or-nothing matching strategy is performed, guaranteeing a ride home. The problem is formulated as a pure binary problem that is solved using an aggregation/disaggregation algorithm that renders optimal solutions. The solution approach is based on decomposing the problem into a master problem and a sub-problem, reducing the number of decision variables and constraints. As a result, various instances of the problem can be solved in reasonable amount of time, even when considering the transit network. The model can be used to simulate a widespread implementation of the concept.

Phd Dissertation

Inequality in Accessibility to Amenities and Exposure to Hazards

Publication Date

September 15, 2015

Author(s)

Dongwoo Yang

Areas of Expertise

Safety, Public Health, & Mobility Justice Travel Behavior, Land Use, & the Built Environment

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Abstract

This dissertation proposes a heuristic theoretical framework for understanding dynamics that impact environmental health including social/built environmental settings, individual residents’ behavioral patterns, location activity spaces (LAS), environmental quality, exposure, and health outcomes. I examined the relationships between factors included in the framework based on individuals’ LASs, and represent a hypothetical geographic boundary in which an individual is expected to spend his/her time in daily life. In addition to the individual level exposure, I characterized built environmental quality for subsidized housing neighborhoods in Los Angeles and Orange Counties, which have not been the focus of previous affordable housing studies. In Chapter 2 and Chapter 4, I empirically demonstrated the framework for residents in neighborhoods near the Expo Right Rail Transit line and the Boyle Heights community in Los Angeles. With OLS regression analysis, I found that bigger LAS were associated with lower walkability, more non-residential land use, higher transit stop density, shorter length of residency, working out of home, and higher income. I examined the relationship between the probability of a census block group (BG) having at least one subsidized unit and associated BG built environmental qualities. Based on logistic regression models, I found that subsidized housing units tended to be located in BGs with better transit access, lower walkability, more mixed-use, and lower air pollution concentrations.

Phd Dissertation

Technology, Trade and the Environment

Publication Date

August 20, 2015

Author(s)

Paul Stroik

Areas of Expertise

Transportation Economics, Funding, & Finance

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Abstract

The three chapters in this dissertation use firm-level data from Vietnam, Chile, and a set of Eastern-European countries to understand the importance of foreign direct investment in technology diffusion and subsequent environmental implications of changes in the production process. Chapter 1 investigates whether increased within-firm or within-industry foreign exposure, or foreign exposure from domestic downstream industry increases technology adoption. Chapters 2 and 3 look beyond technology spillovers of foreign investment, considering whether increased foreign investment affects domestic firm energy intensities. Chapter 2 studies whether domestic Vietnamese firms that become suppliers of domestic foreign-owned firms experience differential technology adoption and changes in energy intensity. Chapter 3 studies whether increased within-firm or within-industry foreign exposure, or foreign exposure from domestic downstream industry in Chile affects firm-level energy intensities.

Studying manufacturing and service firms in Eastern-European countries, Chapter 1 finds that technology gains from domestic foreign exposure differ between lower-income and higher-income countries. In higher-income countries, increased within-industry foreign exposure and increased foreign exposure from downstream industries on average increases technology adoption.

Studying Vietnamese manufacturing firms, Chapter 2 finds that firms that become suppliers of domestic foreign firms are on average more likely to have innovated than their non-supplier peers. These technology gains are found not to translate into short-run changes in energy intensity.

Studying Chilean manufacturing firms, Chapter 3 finds as firms experience increased within-firm foreign investment, they on average increase their electricity intensity. Moreover, increased within-industry foreign exposure on average increases electricity intensity for all firms, and fuel intensity for firms in “dirty” industries.