University of California Transportation Center

This dissertation focuses on the integration of the Household Activity Pattern Problem (HAPP) with various locational decisions considering both supply and demand sides. We present several methods to merge these two distinct areas—transportation infrastructure and travel demand procedures—into an integrated framework that has been previously exogenously linked by feedback or equilibrium processes. From the demand side, travel demand for non-primary activities is derived from the destination choices that a traveler makes that minimizes travel disutility within the context of considerations of daily scheduling and routing. From the supply side, the network decisions are determined as an integral function of travel demand rather than a given fixed OD matrix.

First, the Location Selection Problem for the Household Activity Pattern Problem (LSP-HAPP) is developed. LSP-HAPP extends the HAPP by adding the capability to make destination choices simultaneously with other travel decisions of household activity allocation, activity sequence, and departure time. Instead of giving a set of pre-fixed activity locations to visit, LSPxviii HAPP chooses the location for certain activity types given a set of candidate locations. A dynamic programming algorithm is adopted and further developed for LSP-HAPP in order to deal with the choices among a sizable number of candidate locations within the HAPP modeling structure. Potential applications of synthetic pattern generation based on LSP-HAPP formulation are also presented.

Second, the Location – Household Activity Pattern Problem (Location-HAPP), a facility location problem with full-day scheduling and routing considerations is developed. This is in the category of Location-Routing Problems (LRPs), where the decisions of facility location models are influenced by possible vehicle routings. Location-HAPP takes the set covering model as a location strategy, and HAPP as the scheduling and routing tool. The proposed formulation isolates each vehicle’s routing problem from those of other vehicles and from the master set covering problem. A modified column generation that uses a search method to find a column with a negative reduced price is proposed.

Third, the Network Design Problem is integrated with the Household Activity Pattern Problem (NDP-HAPP) as a bilevel optimization problem. The bilevel structure includes an upper level network design while the lower level includes a set of disaggregate household itinerary optimization problems, posed as HAPP or LSP-HAPP. The output of upper level NDP (level-ofservice of the transportation network) becomes input data for the lower level HAPP that generates travel demand which becomes the input for the NDP. This is advantageous over the conventional NDP that outputs the best set of links to invest in, given an assumed OD matrix. Because the proposed NDP-HAPP can output the same best set of links, a new OD matrix and a detailed temporal distribution of activity participation and travel are created. A decomposed xix heuristic solution algorithm that represents each decision makers’ rationale shows optimality gaps of as much as 5% compared to exact solutions when tested with small examples.

Utilizing the aforementioned models, two transportation sustainability studies are then conducted for the adoption of Alternative Fuel Vehicles (AFVs). The challenges in adopting AFVs are directly related to the transportation infrastructure problems since the initial AFV refueling locations will need to provide comparable convenient travel experience for the early adopters when compared to the already matured gasoline fuel based transportation infrastructure. This work demonstrates the significance of the integration between travel demand model and infrastructure problems, but also draws insightful policy measurements regarding AFV adoption.

The first application study attempts to measure the household inconvenience level of operating AFVs. Two different scenarios are examined from two behavioral assumptions – keeping currently reported pattern and minimizing the inconvenience cost through HAPPR or HAPPC. From these patterns, the personal or household inconvenience level is derived as compared to the original pattern, providing quantified data on how the public sector would compensate for the increases in travel disutility to ultimately encourage the attractiveness of AFVs.

From the supply side of the AFV infrastructure, Location-HAPP is applied to the incubation of the minimum refueling infrastructure required to support early adoption of Hydrogen Fuel Cell Vehicles (HFCVs). One of the early adoption communities targeted by auto manufacturers is chosen as the study area, and then three different values of accessibility are tested and measured in terms of tolerances to added travel time. Under optimal conditions, refueling trips are found to be toured with other activities. More importantly, there is evidence xx that excluding such vehicle-infrastructure interactions as well as routing and scheduling interactions can result in over-estimation of minimum facility requirement.

Transportation planning research addresses accessibility from diverse approaches, focusing varyingly on the usability of the transportation system as a whole, a particular mode, the pattern of land uses, or the wherewithal of individuals and communities to make use of those systems. One aspect of accessibility that has received relatively little attention from planners is its cognitive, experiential aspect. Individuals’ activity and travel choices require not just money and time but also information about opportunities in the city. This component of an individual’s accessibility is highly personal but also dependent on the terrain of land uses and transportation options shaped by planners and policymakers. I seek to extend current accessibility research, addressing shortcomings in how the literature deals with individual experience of the city and knowledge. Through a series of empirical analyses of activity patterns and cognitive maps of theLos Angeles region, I explore the factors that shape individual accessibility. The first analysis investigates the spatial nature of personal cities, using the activity spaces of respondents to explore the types of opportunities that different populations within a city can access. The second demonstrates the differences – depending on mode of travel – among individuals’ perceptions of the city, even when location is held constant. The third analysis continues an exploration of the personal city by considering its fundamental components.

Overall, the analyses support the relevance of the personal city framework to accessibility research, highlighting in particular that planning interventions are filtered through experiential and cognitive processes. The findings highlight that the accessibility impacts of transportation and land use patterns are felt not just in the instantaneous calculations of a microeconomic choice framework, but also in the long-term, developmental processes of cognition and experience. For urban planners, the implications of this research include evidence of how the built environment can effectively reduce travel while maintaining accessibility and how different transportation modes afford varying levels of functional accessibility. Overall, I find that experience, information, and learning are elements of urban daily life traditionally neglected by planners but with potential to increase opportunity and accessibility for diverse urban populations.

Latent modal preferences, or modality styles, are defined as behavioral predispositions towards a certain travel mode or set of travel modes that an individual habitually uses. They are reflective of higher-level orientations, or lifestyles, that are hypothesized to influence all dimensions of an individual’s travel and activity behavior. For example, in the context of travel mode choice different modality styles may be characterized by the set of travel modes that an individual might consider when deciding how to travel, her sensitivity, or lack thereof, to different level-of-service attributes of the transportation (and land use) system when making that decision, and the socioeconomic characteristics that predispose her one way or another. Travel demand models currently in practice assume that individuals are aware of the full range of alternatives at their disposal, and that a conscious choice is made based on a tradeoff between perceived costs and benefits associated with alternative attributes. Heterogeneity in the choice process is typically represented as systematic taste variation or random taste variation to incorporate both observable and unobservable differences in sensitivity to alternative attributes. Though such a representation is convenient from the standpoint of model estimation, it overlooks the effects of inertia, incomplete information and indifference that are reflective of more profound individual variations in lifestyles built around the use of different travel modes and their concurrent influence on all dimensions of individual and household travel and activity behavior. 

The objectives of this dissertation are three-fold: (1) to develop a travel demand model framework that captures the influence of modality styles on multiple dimensions of individual and household travel and activity behavior; (2) to test that the framework is both methodologically flexible and empirically robust; and (3) to demonstrate the value of the framework to transportation policy and practice.

This dissertation investigates the connection between perceived and actual bicycling risk, andhow they both affect and are affected by one’s attitudes, knowledge, behavior, and experiences. Understanding bicycling risk has gained importance as efforts by the U.S. Department of Transportation, the Environmental Protection Agency, the Centers for Disease Control & Prevention, and others have urged communities to increase cycling for its health, environmental, and social equity benefits. Research has identified numerous barriers to increased bicycling in the U.S., including topography, weather, and trip distance, but the barrier that appears most consistently between studies is the perceived hazard associated with cycling near motorists. Yet, little research has fully explored the concept of risk to understand its component parts, including how 1) various driver actions affect perceived and actual cycling risk, 2) reported crash statistics reflect perceived and actual risk, 3) roadway design preferences are affected by perceived risk, and 4) attitudes toward cycling and cycling risk—especially among drivers—influence support for bicycling in one’s community. A deeper understanding of perceived and actual risk is critical for knowing how to address it, and, ultimately, to encourage more people to bicycle. To begin to answer these questions and demystify bicycling risk, this dissertation employs three main methods: focus groups, an online survey (n=463), and an analysis of reported crash data from the San Francisco Bay Area, one of the regions at the forefront of cycling efforts in the U.S. 

My findings confirm that perceived and actual cycling risk influence the decision to bicycle, but indicate that the causal pathways are more nuanced than previously understood. First, my data suggest that cyclists experience two types of roadway risk: pervasive risk in the form of near misses that occur frequently, and acute risk that occurs when a cyclist is struck—a less frequent, but more injurious incident. Both types—but particularly near misses— significantly affect perceived risk for cyclists and their family and friends, yet we lack systematic data on near misses and are therefore almost completely ignorant about the extent and effect of their occurrence. Routinely-collected reported crash data provide only limited insight into the type and extent of risk cyclists experience. 

Second, roadway design preferences are significantly related to perceived risk, and particularly important for attracting new cyclists. Surprisingly, drivers and cyclists both prefer roadway designs with separated space for bicyclists, particularly if barrier-separated, regardless of cycling frequency. Shared space designs are less popular among drivers and much less popular among cyclists, particularly for people who might consider cycling but do not currently do so: only a tiny fraction of potential cyclists feel comfortable sharing space with drivers on commercial streets. 

Third, perceived cycling risk extends beyond fear of danger for oneself, and is significantly related to support for cycling in one’s community. Structural equation models of perceived cycling risk, attitudes, and behavior revealed that respondents are affected by their perceived risk as cyclists, but also as drivers sharing the roadway with cyclists they view as “scofflaws”, and the risks they project onto other cyclists—particularly those cycling with children. This multi-pronged belief in cycling risk significantly negatively affects bicycling support, including support for new bicycle facilities and public funding to encourage cycling. 

Based on these findings, I propose a revised theoretical framework for conceptualizing cycling risk and its influences. I conclude the dissertation with policy recommendations for addressing perceived risk.

Mexico City is a suburban metropolis, yet most of its suburbs would be unfamiliar to urbanists accustomed to thinking about US metropolitan regions. Mexico City’s suburbs are densely populated—not thinly settled—and its residents rely primarily on informal transit rather than privately-owned automobiles for their daily transportation. These types of dense and transit-dependent suburbs have emerged as the fastest-growing form of human settlement in cities throughout Latin America, Asia, and Africa. Wealthier and at a later stage in its economic development than other developing-world metropolises, Mexico City is a compelling place to investigate the effects of rising incomes, increased car ownership, and transit investments in the dense, peripheral areas that have grown rapidly around informal transit in the past decades, and is a bellwether for cities like Dakar, Cairo, Lima, and Jakarta.

I begin this dissertation with a historical overview of the demographic, economic, and political trends that have helped shape existing urban form, transportation infrastructure, and travel behavior in Mexico City. Despite an uptick in car ownership and use, most households—both urban and suburban—continue to rely on public transportation. Furthermore, suburban Mexico City has lower rates of car ownership and use than its central areas. In subsequent chapters, I frame, pose, and investigate three interrelated questions about Mexico City’s evolving suburban landscape, the nature of households’ travel decisions, and the relationship between the built environment and travel behavior. Together, these inquiries tell a story that differs significantly from narratives about US suburbs, and provide insight into the future transportation needs and likely effects of land and transportation policy in these communities and others like them in Mexico and throughout the developing world.

First, how has the influence of the built environment on travel behavior changed as more households have moved into the suburbs and aggregate car use has increased? Using two large metropolitan household travel surveys from 1994 and 2007, I model two related-but-distinct household travel decisions: whether to drive on an average weekday, and if so, how far to drive. After controlling for income and other household attributes, I find that the influence of population and job density on whether a household undertakes any daily car trips is strong and has increased marginally over time. By contrast, high job and population densities have a much smaller influence on the total distance of weekday car travel that a household generates. For the subset of households whose members drive on a given weekday, job and population densities have no statistical effect at all. Contrary to expectations, a household’s distance from the urban center is strongly correlated with a lower probability of driving, even after controlling for income. This effect, however, appears to be diminishing over time, and when members of a household drive, they drive significantly more if they live farther from the urban center. The combination of informal transit, public buses, and the Metro has provided sufficient transit service to constrain car use in the densely populated suburban environments of Mexico City. Once suburban residents drive, however, they tend to drive a lot regardless of transit or the features of the built environment.

Second, how much are the recent trends of increased suburbanization, rising car-ownership, and the proliferation of massive commercially-built peripheral housing developments interrelated? To investigate this question, I first disentangle urban growth and car ownership trends by geographic area. The fastest-growing areas tend to be poorer and have had a much smaller impact on the size of the metropolitan car fleet than wealthier, more established neighborhoods in the center and western half of the metropolis. I then zoom in to examine several recent commercial housing developments. These developments, supported by publicly-subsidized mortgages, contain thousands of densely-packed, small, and modestly-priced housing units. Their residents remain highly reliant on public transportation, particularly informal transit, and the neighborhoods become less homogenous over time as homeowners convert units and parking spaces to shops and offices. Finally, I use the 2007 household travel survey to model households’ intertwined decisions of where to live and whether to own a car. As expected, wealthier and smaller households are more likely to purchase vehicles. However, they prefer to live in more central areas where households with cars tend to drive shorter distances. If housing policy and production cannot adapt to provide more centrally-located housing, growing incomes will tend to increase car ownership but concentrate more of it in areas where car-owning households drive much farther.

Third, how has the Metro’s Line B, one of the first and only suburban high-capacity transit investments, influenced local and regional travel behavior and land use? To explore this question, I compare travel behavior and land use measures at six geographic scales, including the investment’s immediate catchment area, across two time periods: six years before and seven years after the investment opened. Line B, which opened in stages in 1999 and 2000, significantly expanded Metro coverage into the densely populated and fast-growing suburban municipality of Ecatepec. While the investment sparked a significant increase in local Metro use, most of this increase came from people relying on informal transit, rather than cars. While this shift reduced transit fares and increased transit speeds for local residents, it also increased government subsidies for the Metro and had no apparent effect on road speeds. Furthermore, the Metro remains highly dependent on informal transit to provide feeder service even within Ecatepec. In terms of land use, the investment increased density around the stations but appears to have had little to no effect on downtown commercial development, where it might have been expected to have a significant influence. In short, the effects of Line B demonstrate much of the promise and problem with expanding high capacity transit service into the suburbs. Ridership is likely to be high, but so too will be the costs and subsidies, while the effects on car ownership and urban form are likely to be modest.

Individually, each chapter contributes to a specific body of transportation and planning literature drawn from the US as well as developing countries. Collectively, they point to connection between land use and transportation in Mexico City that is different from the 3 connection in US and other rich-world cities. In particular, there is a physical disconnect between the generally suburban homes of transit users and the generally central location of high-capacity public transit. Addressing this disconnect by shifting housing production from the periphery to the center or by expanding high-capacity transit to the periphery would require significant amounts of time and public subsidy. Thus, contemporary policies to reduce car use or increase accessibility for the poor in the short and medium term would do well to focus on improving the flexible, medium-capacity informal transit around which the city’s dense and transit-dependent suburbs have grown and continue to grow.

Mexico City is a suburban metropolis, yet most of its suburbs would be unfamiliar to urbanists accustomed to thinking about US metropolitan regions. Mexico City’s suburbs are densely populated—not thinly settled—and its residents rely primarily on informal transit rather than privately-owned automobiles for their daily transportation. These types of dense and transitdependent suburbs have emerged as the fastest-growing form of human settlement in cities throughout Latin America, Asia, and Africa. Wealthier and at a later stage in its economic development than other developing-world metropolises, Mexico City is a compelling place to investigate the effects of rising incomes, increased car ownership, and transit investments in the dense, peripheral areas that have grown rapidly around informal transit in the past decades, and is a bellwether for cities like Dakar, Cairo, Lima, and Jakarta.

I begin this dissertation with a historical overview of the demographic, economic, and political trends that have helped shape existing urban form, transportation infrastructure, and travel behavior in Mexico City. Despite an uptick in car ownership and use, most households—both urban and suburban—continue to rely on public transportation. Furthermore, suburban Mexico City has lower rates of car ownership and use than its central areas. In subsequent chapters, I frame, pose, and investigate three interrelated questions about Mexico City’s evolving suburban landscape, the nature of households’ travel decisions, and the relationship between the built environment and travel behavior. Together, these inquiries tell a story that differs significantly from narratives about US suburbs, and provide insight into the future transportation needs and likely effects of land and transportation policy in these communities and others like them in Mexico and throughout the developing world.

First, how has the influence of the built environment on travel behavior changed as more households have moved into the suburbs and aggregate car use has increased? Using two large metropolitan household travel surveys from 1994 and 2007, I model two related-but-distinct household travel decisions: whether to drive on an average weekday, and if so, how far to drive. After controlling for income and other household attributes, I find that the influence of population and job density on whether a household undertakes any daily car trips is strong and has increased marginally over time. By contrast, high job and population densities have a much smaller influence on the total distance of weekday car travel that a household generates. For the subset of households whose members drive on a given weekday, job and population densities have no statistical effect at all. Contrary to expectations, a household’s distance from the urban center is strongly correlated with a lower probability of driving, even after controlling for income. This effect, however, appears to be diminishing over time, and when members of a household drive, they drive significantly more if they live farther from the urban center. The combination of informal transit, public buses, and the Metro has provided sufficient transit service to constrain car use in the densely populated suburban environments of Mexico City. Once suburban residents drive, however, they tend to drive a lot regardless of transit or the features of the built environment.

Second, how much are the recent trends of increased suburbanization, rising carownership, and the proliferation of massive commercially-built peripheral housing developments interrelated? To investigate this question, I first disentangle urban growth and car ownership trends by geographic area. The fastest-growing areas tend to be poorer and have had a much smaller impact on the size of the metropolitan car fleet than wealthier, more established neighborhoods in the center and western half of the metropolis. I then zoom in to examine several recent commercial housing developments. These developments, supported by publiclysubsidized mortgages, contain thousands of densely-packed, small, and modestly-priced housing units. Their residents remain highly reliant on public transportation, particularly informal transit, and the neighborhoods become less homogenous over time as homeowners convert units and parking spaces to shops and offices. Finally, I use the 2007 household travel survey to model households’ intertwined decisions of where to live and whether to own a car. As expected, wealthier and smaller households are more likely to purchase vehicles. However, they prefer to live in more central areas where households with cars tend to drive shorter distances. If housing policy and production cannot adapt to provide more centrally-located housing, growing incomes will tend to increase car ownership but concentrate more of it in areas where car-owning households drive much farther.

Third, how has the Metro’s Line B, one of the first and only suburban high-capacity transit investments, influenced local and regional travel behavior and land use? To explore this question, I compare travel behavior and land use measures at six geographic scales, including the investment’s immediate catchment area, across two time periods: six years before and seven years after the investment opened. Line B, which opened in stages in 1999 and 2000, significantly expanded Metro coverage into the densely populated and fast-growing suburban municipality of Ecatepec. While the investment sparked a significant increase in local Metro use, most of this increase came from people relying on informal transit, rather than cars. While this shift reduced transit fares and increased transit speeds for local residents, it also increased government subsidies for the Metro and had no apparent effect on road speeds. Furthermore, the Metro remains highly dependent on informal transit to provide feeder service even within Ecatepec. In terms of land use, the investment increased density around the stations but appears to have had little to no effect on downtown commercial development, where it might have been expected to have a significant influence. In short, the effects of Line B demonstrate much of the promise and problem with expanding high capacity transit service into the suburbs. Ridership is likely to be high, but so too will be the costs and subsidies, while the effects on car ownership and urban form are likely to be modest.

Individually, each chapter contributes to a specific body of transportation and planning literature drawn from the US as well as developing countries. Collectively, they point to connection between land use and transportation in Mexico City that is different from the connection in US and other rich-world cities. In particular, there is a physical disconnect between the generally suburban homes of transit users and the generally central location of high-capacity public transit. Addressing this disconnect by shifting housing production from the periphery to the center or by expanding high-capacity transit to the periphery would require significant amounts of time and public subsidy. Thus, contemporary policies to reduce car use or increase accessibility for the poor in the short and medium term would do well to focus on improving the flexible, medium-capacity informal transit around which the city’s dense and transit-dependent suburbs have grown and continue to grow.

In India, demand for urban mobility is increasing rapidly because of growth in urban

populations, establishment of multiple employment sub-centers, suburbanization of households,better education, higher workforce participation rates, and rising incomes. An increase in discretionary spending is leading to higher household transportation budgets. Middle-income households in particular are investing in private vehicles such as motorized two-wheelers (TWs)

and cars. At the same time, policies to reduce vehicle ownership through regulations and user

costs remain underdeveloped and weakly enforced. This further increases households’

willingness to use vehicles, especially for non-discretionary work trips. Higher private vehicle

use is affecting other quality of life issues such as time spent commuting, accident rates, noise

pollution, and particulate and greenhouse gas emissions.

In part, this higher vehicle ownership and use is driven by land use dynamics in Indian

cities, where growth within city municipal boundaries is constrained by regulations limiting

floor-area ratios. As a result, much of the new growth has taken place in urban peripheries where

land is cheap and building costs are low. In these peripheral areas, existing small and medium

towns have become anchors for agglomeration, transforming into bedroom communities for

emergent middle-class groups. Urban peripheral areas are usually undersupplied with

transportation infrastructure such as roads or bus transit.

This dissertation unpacks the question of why the middle-class in India is driven to

owning and using TWs and cars by asking the following: (1) How does work location influence

travel by public and private modes? (2) What factors encourage vehicle ownership in middleclass

households? (3) What factors drive up vehicle use in middle-class households? The

research was conducted using a travel survey dataset from the Greater Mumbai Region (GMR)

that represents 1.5% of the households there. The GMR is among the most populated megacity

regions in the world, housing over 22 million people. Its growth illustrates the transformation

from a monocentric to a polycentric city which is seen in many rapidly growing Indian cities.

In seeking to develop an understanding of how work location affected travel, this

research identified employment sub-centers using work destination data. Of all middle-class

2

home-based work trips, 67 percent ended in a sub-center, while 33 percent did not. Mean travel

times and mean travel distances by train, TW and intermediate public transportation (IPT) modes

such as rickshaws were longer for work destinations in sub-centers than for work destinations in

the urban periphery, but trips made by buses were shorter in sub-centers. Car users traveled

longer and farther compared to TW users for home-based work trips in the GMR. Trains were

the speediest mode of travel in the GMR, but traveling by a TW or car was speedier than bus or

IPT travel—confirming that having a private vehicle has advantages.

This research used a multinomial logit model to analyze households’ choice of having no

vehicles, only TWs, or at least one car. Results indicated that household utility from both TWs

and cars increased with household characteristics such as per capita annual income, living in an

independent house or an apartment, number of rooms in the housing unit, housing location

farther from a railway station, the presence of children under 5 years, and larger household size.

Moreover, vehicle utility for households increased with the primary wage earner’s characteristics

including college education, employment, being married, making more trips across all modes,

traveling during the morning peak, and working in the urban periphery. Household utility from

both TWs and cars decreased when the primary wage earner had longer work trips and higher

employment density at the work location.

Regression models for vehicle kilometers traveled (VKT) and person kilometers traveled

(PKT) for cars and TWs showed that vehicle use increased with number of employed persons in

the household, and if the primary wage earner worked in the urban core. Vehicle use decreased if

density of housing and jobs went up at either the home or work location. TW use went down

with per capita annual household income.

Overall findings indicate that demand for private vehicles is rising due to the following

factors: better education, employment, higher incomes, suburbanization, peripheral employment

node formation, and lack of public travel options. However, higher density decreases vehicle use.

Without changes in policies encouraging higher well-managed densities, jobs-housing balance,

and supply of adequate transit and IPT travel options, vehicle ownership and use will likely

continue to grow rapidly in India.