research report

Evaluating the Impacts of Start-Up and Clearance Behaviors in a Signalized Network: A Network Fundamental Diagram Approach

policy brief

Evaluating the Impacts of Start-Up and Clearance Behaviors in a Signalized Network: A Network Fundamental Diagram Approach

MS Thesis

The Effects of VMT on Travel Demand and Implied Equity Issues

Abstract

The purpose of this thesis was to analyze the California Household Travel Survey to examine any differences in travel behavior and demographics between two of California’s multi-county Metropolitan Planning Organization (MPO) areas, the Southern California Association of Governments (SCAG) and the Metropolitan Transportation Commission (MTC). As these regions continue to grow, they have witnessed significant gentrification affecting marginalized communities that are already struggling against increasing costs of living. There were significant differences in both travel times and distance traveled with the SCAG region having values slightly higher than MTC. However, within each region there were significant differences in income and racial demographics at the county level. In SCAG, Orange County had the highest Average HH level incomes and San Bernardino and Imperial Counties having the lowest average HH level incomes. Within the MTC area African Americans and Native Americans were found to more likely walk and use public transit more than other group due to these groups having the lowest incomes out of other groups. Also, these groups tend to reside in Contra Costa and Alameda Counties which have the lowest housing costs in the MTC region.

published journal article

How do they get by without cars? An analysis of travel characteristics of carless households in California

Abstract

In spite of their substantial number in the U.S., our understanding of the travel behavior of households who do not own motor vehicles (labeled “carless” herein) is sketchy. The goal of this paper is to start filling this gap for California. We perform parametric and non-parametric tests to analyze trip data from the 2012 California Household Travel Survey (CHTS) after classifying carless households as voluntarily carless, involuntarily carless, or unclassifiable based on a CHTS question that inquires why a carless household does not own any motor vehicle. We find substantial differences between our different categories of carless households. Compared to their voluntarily carless peers, involuntarily carless households travel less frequently, their trips are longer and they take more time, partly because their environment is not as well adapted to their needs. They also walk/bike less, depend more on transit, and when they travel by motor vehicle, occupancy is typically higher. Their median travel time is longer, but remarkably, it is similar for voluntarily carless and motorized households. Overall, involuntarily carless households are less mobile, which may contribute to a more isolated lifestyle with a lower degree of well-being. Compared to motorized households, carless households rely a lot less on motor vehicles and much more on transit, walking, and biking. They also take less than half as many trips and their median trip distance is less than half as short. This study is a first step toward better understanding the transportation patterns of carless households.

published journal article

Use of Ride-Hailing Services among Older Adults in the United States

Abstract

This paper presents an analysis of data from the 2017 National Household Travel Survey to examine the factors influencing the adoption and the frequency of use of on-demand ride-hailing services such as Uber and Lyft among older adults. Using a zero-inflated negative binomial model (ZINB), the results indicate that the determinants of adoption of on-demand ride-hailing services (users versus non-users) are different from the determinants of the frequency of use of these services among older adult users. Seniors who are younger, living alone, in urban dwellings, more highly educated, more affluent, or male with a medical condition that results in asking others for rides are more likely to be adopters of ride-hailing services. However, seniors who are middle elderly, less educated, or are carless older adults, are more likely to be frequent users of on-demand ride-hailing services as long as they adopt these services. In addition, smartphone possession plays an important role in the adoption behavior of on-demand ride-hailing services among older adults. Results of bivariate analysis showed that older adult ride-hailing users make more transit trips than their non-user counterparts, suggesting that ride-hailing services have the potential to serve as a complementary form of public transportation for older adults. The findings of this research will help ride-hailing operators in identifying potential market segments of their services and in developing campaign strategies for potential adopters.

Phd Dissertation

Deployment of Fuel Cell Electric Buses in Transit Agencies : Hydrogen Demand Allocation and Preferable Hydrogen Infrastructure Rollout Scenarios

Abstract

Aiming to reduce criteria air pollutant and greenhouse gas emissions, several initiatives have been announced throughout the world to incorporate zero emission buses into public transit agencies within the next 15 years. One example is the California Air Resources Board “Innovative Clean Transit Regulation” with the goal to transform the statewide transit bus fleet by 2040 with zero emission buses. In response, transit authorities face decisions between multiple bus technologies, each with different strengths and weaknesses as well as infrastructure requirements. Furthermore, because the performance of new bus technologies depends on the operating conditions of each transit agency, the results from demonstration projects are not typically applicable to another district.

This dissertation addresses the use of Life Cycle Assessment (LCA) to compare different zero-emission bus (ZEB) technologies for transit districts in the State of California. For LCAs conducted to date, the focus has been on one-on-one bus technology comparisons rather than a combination of bus technologies integrated into bus fleets (mixed fleet). This dissertation extends the traditional LCA approach by using Multi-Objective Linear Programming (MOLP) to identify the optimal ZEB technology mix.

The novelty of this extended LCA is the use of a consistent framework across multiple powertrain types with the same operating conditions. The fleet optimization incorporates essential aspects of a fleet operation such as operational constraints, route length, required infrastructure, and cost. Additionally, a Multi-Criteria Decision Analysis (MCDA) is incorporated to evaluate parameter weighting in the optimization problem, thereby creating an optimization solution that considers real constraints and priorities from stakeholders, users, and regulatory agencies.

The combination of these capabilities (LCA, MOLP, and MCDA) provides a comprehensive tool, including a variety of energy supply chains, which can inform transit agencies in the design of an electric bus fleet comprised by a mix of available and emerging ZEB technologies.

research report

Transportation Plans: Their Informational Content and Use Patterns in Southern California

Abstract

While a large amount of effort has been devoted to making and updating local transportation plans, little is known about the informational contents of these plans and their use patterns.  This project attempted to identify key informational contents of Californian cities’ transportation plans and to investigate how various stakeholders can use the plan contents through (i) a plan content analysis of a sample of general plans (recently adopted by eight municipalities in Orange County, California) and (ii) a plan use survey and follow-up analysis of survey responses. All plans that were analyzed were found to convey a variety of information about their visions, goals, policies, and implementation strategies, but the plan content analysis revealed substantial variation in the way cities composed their general plans and integrated them with other plans/players. Compared to land use elements, circulation elements tended to focus more on their connections with other agencies (external consistency) than on internal consistency. The plan use survey yielded a low response rate which may indicate limited use of plans in the field. However, a majority of the survey responses were positive about the usefulness and usability of general plans. In particular, the survey participants reported that they found the plans comprehensive, visionary, and well-organized, while relatively lower scores were obtained for two evaluation criteria: ‘[the plan] clearly explains what actions will be taken and when’ and ‘[the plan] is relevant to my everyday life and/or work’. Furthermore, some respondents reported that they used general plans not for their professional duties but for other (non-conventional) purposes, suggesting that plan contents could be used for a variety of decision-making processes.

Phd Dissertation

Electrification, Connectivity, & Active Demand Management: Addressing the traffic, health, and EJ impacts of drayage trucks in Southern California

Abstract

Trucking electrification combined with connected and automated technologies promises to cut the cost of freight transportation, reduce its environmental footprint, and make roads safer. If electric trucks are powerful enough to cease behaving as moving bottlenecks, they could also increase road capacity and reduce the demand for new infrastructure, a consequence that has so far been overlooked by the literature. In this dissertation, I study the traffic and infrastructure demand impacts of electrifying and connecting (via cooperative adaptive cruise control, CACC) heavy-duty drayage trucks (HDDTs) that serve the San Pedro Bay Ports (SPBP; the ports of Los Angeles and Long Beach, which is the largest port complex in the U.S), quantify the resulting health, environmental, and Environmental Justice impacts, and explore how to maximize the benefits of connected vehicles with active demand management.In Chapter 2, I explore the potential traffic and infrastructure implications of replacing conventional HDDTs that serve the SPBP with electric and/or connected HDDTs. I rely on microscopic simulation on a freeway and arterial network centered on I-710, the country’s most important economic artery. My results show that 1,000-hp electric/hydrogen trucks can be a substitute for additional road capacity. Accounting for the traffic impacts of new vehicle technologies is critical in infrastructure planning, and my results suggest shifting funding from building new capacity to financing zero-emission (ZE) 1,000 hp HDDTs until the market for these vehicles has matured. In Chapter 3, I quantify the health and GHG reduction benefits of replacing the HDDTs serving the SPBP with ZE-HDDTs. I simulate ZE-HDDTs on a regional freeway network to analyze their PM2.5 and CO2 emissions in 2012 and 2035 using MOVES3 emission factors. I then estimate their contribution to PM2.5 concentrations with InMAP and health impacts with BenMAP. I find that despite technology improvements and air quality regulations, SPBP HDDTs would still cause 106 premature deaths (valued at $1.3 billion in $2022) and 2,142 asthma attacks (over two thirds of which would accrue to disadvantaged communities) in 2035 due to population and drayage traffic growth, not to mention at least $220 million in climate costs. With ZE-HDDTs becoming attractive in the next few years from a total cost of ownership point-of-view, the main cost of achieving ZE road drayage is a scrappage program for non-ZE-HDDTs. My results justify implementing this program by 2035.In Chapter 4, I study the performance impacts of lane management strategies implemented on I-710 to support the deployment of CACC-enabled vehicles and their potential to absorb the 2035 projected growth in cargo demand at the SPBP. I find that a designated lane for CACC-enabled vehicles can decrease congestion by creating more platooning opportunities, thus maximizing CACC benefits.

Phd Dissertation

Automated Identification of Near-Stationary Traffic States and Calibration of Unifiable Multi-Lane Multi-Class Fundamental Diagrams

Abstract

Experience of daily commuters shows that stationary traffic patterns can be observed during peak periods in urban freeway networks. Such stationary states play an important role in various traffic flow studies. Conceptually, studies on the impact of capacity drop and design of traffic control strategies have been built on the assumption of stationarity. Mathematically, the existence and stability of stationary states in general road networks have been proved. Empirically, near-stationary states have been utilized for calibration of fundamental diagrams and investigation of traffic features at freeway bottlenecks. Therefore, an imperative need for real-world near-stationary data has been realized to better understand, investigate, and explore such above studies. However, there lacks an efficient method to identify near-stationary states.

To fill the gap, in this research, an automated method has been developed to efficiently identify near-stationary states from large amounts of inductive loop-detector data. The method consists of four steps: first, a data pre-processing technique is performed to select healthy datasets, fill in missing values, and normalize vehicle counts and occupancies; second, a PELT changepoint detection method is adopted to detect changes in means and partition time series into candidate intervals; third, informative characteristics of each candidate, including duration and gap, are defined and calculated; finally, near-stationary states are selected from candidates through duration and gap criteria.

A game theory approach is further designed to directly calibrate parameters of the above method. First, a multi-objective optimization problem is formulated to consider the quantity and quality of near-stationary states as the objective functions. Then the problem is converted into a non-cooperative game with at least one Nash equilibrium. To solve the game and obtain a unique solution, an alternated hill-climbing search algorithm is developed.

Furthermore, two calibration schemes for multi-lane and multi-class fundamental diagrams are respectively designed by utilizing near-stationary states. Such multi-commodity fundamental diagrams possess unifiable and non-FIFO properties and can capture interaction among different commodities. Calibration and validation results show that both the calibrated unifiable multi-lane and multi-class fundamental diagrams are well-fitted, physically meaningful, and have robust performance on the estimation of commodity flow-rates.

MS Thesis

A Direct Demand Model for Commuter Rail Ridership in the San Francisco Bay Area

Abstract

This thesis documents the development of a direct travel demand model for commuter rail in the San Francisco Bay Area. A direct demand model simultaneously estimates trip generation and attraction, which for this thesis would be trips between an origin-destination pair of stations. In the model, the number of trips assigned to an origin-destination pair of stations is dependent on land use characteristics at the origin and destination stations in combination with travel time on the network during congested peak periods and via transit. The model uses a multiplicative direct demand model to estimate ordinary least square regression parameters for the origin-destination trips. From the model form, the resultant estimated regression parameters are elasticities, and as such, can be used to postulate the effects of the selected land use characteristics and network travel times upon the number of trips made. At both the origin and destination, the location of the station within the central business districts of the San Francisco Bay region had the largest effect on trip generation and attraction. Higher employment density at the destination and a larger number of workers per household at the origin had a positive effect on trips, while the total number of industrial workers at the destination and an increased number of two car households had a negative effect on trips. Longer travel times on transit appeared to have a positive effect on trips, yet longer travel times in congested peak periods appeared to have a negative effect on trips.