Ram M. Pendyala

• PhD
• Professor at Arizona State University

The notion that people’s activity-travel patterns influence wellbeing and overall quality of life is well recognized. Nonetheless, activity-travel demand model outputs do not provide explicit measures of wellbeing that can be used to assess the impacts of alternative policies, investments, and technologies. This study presents a model of wellbeing...

As transportation systems grow in complexity, analysts need sophisticated tools to understand travelers’ decision-making and effectively quantify the benefits of the proposed strategies. The transportation community has developed integrated demand–supply models to capture the emerging interactive nature of transportation systems, serve diverse plan...

The growing behaviors of work-from-home (WFH) and online shopping hold significant potential for reducing traffic congestion and emissions. Understanding the frequency and the interplay between these two behaviors is important for successful implementation. This study investigates the recent trends of WFH and online shopping and the underlying fact...

The COVID-19 pandemic was an unprecedented global crisis that has impacted virtually everyone. We conducted a nationwide online longitudinal survey in the United States to collect information about the shifts in travel-related behavior and attitudes before, during, and after the pandemic. The survey asked questions about commuting, long distance tr...

The growing behaviors of work-from-home (WFH) and online shopping hold significant potential for reducing traffic congestion and emissions. Understanding the frequency and the interplay between these two behaviors is important for successful implementation. This study investigates the recent trends of WFH and online shopping and the underlying fact...

With work arrangements experiencing dramatic changes over the past three years due to the COVID-19 pandemic, and the possibility that altered work arrangements may persist well into the future, the implications of teleworking on activity-travel behavior are potentially profound. This paper aims to substantially add to the body of knowledge about th...

A sustainable transportation future is one in which people eschew personal car ownership in favor of using autonomous vehicle (AV)-based ridehailing services in a shared mode. However, the traveling public has historically shown a disinclination toward sharing rides and carpooling with strangers. In a future of AV-based ridehailing services, it wil...

This paper presents an examination of the interrelationship between household vehicle ownership and ridehailing use frequency. Both variables constitute important mobility choices with significant implications for the future of transport. Although it is generally known that these two behavioral phenomena are inversely related to one another, the di...

The COVID-19 pandemic has brought about transformative changes in human activity-travel patterns. These lifestyle changes were naturally accompanied by and associated with changes in transportation mode use and work modalities. In the United States, most transit agencies are still grappling with lower ridership levels, thus signifying the onset of...

This research aims to investigate the well-being implications of changes in activity-travel and time-use patterns brought about by the COVID-19 pandemic. The study uses American Time Use Survey (ATUS) data from 2019 and 2020 to assess changes in activity-travel and time-use patterns. It applies two methods—a well-being scoring method and a time-pov...

This study presents an integrated model to shed light on the factors influencing individuals’ likelihood and frequency of usage of bus transit in Bengaluru, India, with a focus on the role of individuals’ subjective perceptions of service quality. Typically, subjective perceptions of transit service characteristics such as comfort, cleanliness, rel...

This study focuses on an important transport-related long-term effect of the COVID-19 pandemic in the United States: an increase in telecommuting. Analyzing a nationally representative panel survey of adults, we find that 40-50% of workers expect to telecommute at least a few times per month post-pandemic, up from 24% pre-COVID. If given the option...

This study focuses on an important transport-related long-term effect of the COVID-19 pandemic in the United States: an increase in telecommuting. Analyzing a nationally representative panel survey of adults, we find that 40-50% of workers expect to telecommute at least a few times per month post-pandemic, up from 24% pre-COVID. If given the option...

A critical challenge facing transportation planners is to identify the type and the extent of changes in people’s activity-travel behavior in the post-Covid-19 pandemic world. In this study, we investigate the travel behavior evolution by analyzing a longitudinal two-wave panel survey data conducted in the United States from April 2020 to May 2021....

The COVID-19 pandemic is an unprecedented global crisis that has impacted virtually everyone. We conducted a nationwide online longitudinal survey in the United States to collect information about the shifts in travel-related behavior and attitudes before, during, and after the pandemic. The survey asked questions about commuting, long distance tra...

How does the extent of automobile use affect the level of satisfaction that people derive from their daily travel routine, after controlling for many other attributes including socio-economic and demographic characteristics, attitudinal factors, and lifestyle proclivities and preferences? This is the research question addressed by this paper. In th...

This study focuses on the long-term impacts of COVID-19 on telecommuting behavior. We seek to study the future of telecommuting, in the post-pandemic era, by capturing the evolution of observed behavior during the COVID-19 pandemic. To do so, we implemented a comprehensive multi-wave nationwide panel survey (the Future Survey) in the U.S. throughou...

As an active performance evaluation method, the fluid-based queueing model plays an important role in traffic flow modeling and traffic state estimation problems. A critical challenge in the application of traffic state estimation is how to utilize heterogeneous data sources in identifying key interpretable model parameters of freeway bottlenecks,...

Many rapidly developing countries around the world are at a crossroads when it comes to transportation, air quality, and sustainability. Indeed, the challenges presented by vehicular growth in India have motivated the search for sustainable transportation solutions. One solution constitutes ridehailing services, which are expected to reduce car own...

A variant of the traditional multiple discrete-continuous extreme value (MDCEV) model that obviates the need to have budget information, labeled as the Lγ-profile MDCEV model, has been proposed recently. This new model structure breaks the strong linkage between the discrete and continuous choice dimensions of decision-making. But recent studies sh...

The COVID-19 pandemic has impacted billions of people around the world. To capture some of these impacts in the United States, we are conducting a nationwide longitudinal survey collecting information about activity and travel-related behaviors and attitudes before, during, and after the COVID-19 pandemic. The survey questions cover a wide range of...

The explosive nature of Covid-19 transmission drastically altered the rhythm of daily life by forcing billions of people to stay at their homes. A critical challenge facing transportation planners is to identify the type and the extent of changes in people's activity-travel behavior in the post-pandemic world. In this study, we investigated the tra...

Human behavior is notoriously difficult to change, but a disruption of the magnitude of the COVID-19 pandemic has the potential to bring about long-term behavioral changes. During the pandemic, people have been forced to experience new ways of interacting, working, learning, shopping, traveling, and eating meals. A critical question going forward i...

In a world of ever-changing travel behavior and ever-increasing modal options, is vital to have integrated models that could capture the interactions between supply and demand layers of travel. Addressing this need, we propose three different versions of network representation and mathematical models for the activity-based vehicle routing problem t...

The utility of attitudes in travel demand forecasting requires predictability. Any attempt to simulate future attitudes, as is done in such models, would be impractical if they were subject to substantial unpredictable variation over time. We investigate the stability of attitudes using waves of the COVID Future survey answered 3.5–11 months apart....

This study identifies differences in COVID-19 related attitudes and risk perceptions among urban, rural, and suburban populations in the US using data from an online, nationwide survey collected during April-October 2020. In general, rural respondents were found to be less concerned by the pandemic and a lower proportion of rural respondents suppor...

This article uses data from the first wave of the COVID Future Panel study to evaluate attitudes towards COVID-19 and their influence on traveler behaviors. An exploratory factor analysis identified two underlying constructs based on the measured attitudes, namely “Concern about Pandemic Response” and “COVID Health Concern.” A cluster analysis base...

In an era of big data and emergence of new technologies such as app-based ride services, there are growing opportunities for better understanding human mobility patterns from newly available data sources. Statistical models have been mainly utilized to uncover and rigorously calibrate the influence of significant factors; and machine learning algor...

Human behavior is notoriously difficult to change, but a disruption of the magnitude of the COVID-19 pandemic has the potential to bring about long-term behavioral changes. During the pandemic, people have been forced to experience new ways of interacting, working, learning, shopping, traveling, and eating meals. A critical question going forward i...

The COVID-19 pandemic has impacted billions of people around the world. To capture some of these impacts in the United States, we are conducting a nationwide longitudinal survey collecting information about travel-related behaviors and attitudes before, during, and after the COVID-19 pandemic. The survey questions cover a wide range of topics inclu...

Ride-hailing services have grown in cities around the world. There are, however, few studies and even fewer publicly available data sources that provide a basis to understand and quantify changes in ride-hailing usage over time. Ride-hailing use may change over time because of socio-demographic shifts, economic and technological changes, and servic...

As app-based ride-hailing services have been widely adopted within existing traditional taxi markets, researchers have been devoted to understand the important factors that influence the demand of the new mobility. Econometric models (EMs) are mainly utilized to interpret the significant factors of the demand, and deep neural networks (DNNs) have b...

The virtual (online) and physical (in-person) worlds are increasingly inter-connected. Although there is considerable research into the effects of information and communication technologies (ICT) on activity-travel choices, there is little understanding of the inter-relationships between online and in-person activity participation and the extent to...

The mode share of app-based ride-hailing services has been growing steadily in recent years and this trend is expected to continue. Ride-hailing services generate two types of trips – passenger hauling trips and deadheading trips. Passenger hauling trips are the trips made while transporting passengers between places. Virtually all other trips made...

Walking is a mode of transport that offers many benefits. This study aims to provide insights on the emotions associated with different types of walking episodes – namely, utilitarian walking episodes that are undertaken with the purpose of fulfilling an activity at a destination and recreational walking episodes that are undertaken with no specifi...

The introduction of mobile application-based ride hailing services represents a convergence between technologies, supply of vehicles, and demand in near real time. There is growing interest in quantifying the demand for such services from regulatory, operational, and system evaluation perspectives. Several studies model the decision to adopt ride h...

Understanding the dynamic relationship between demand and supply and the resulting congestion across different scales is theoretically challenging and practically important for managing transportation systems. This paper aims to describe oversaturated system dynamics with parsimonious analytical formulations based on polynomial functional approxima...

Travel model systems often adopt a single decision structure that links several activity-travel choices together. The single decision structure is then used to predict activity-travel choices, with those downstream in the decision-making chain influenced by those upstream in the sequence. The adoption of a singular sequential causal structure to de...

The rise of ride-hailing services has presented a number of challenges and opportunities in the urban mobility sphere. On the one hand, they allow travelers to summon and pay for a ride through their smartphones while tracking the vehicle’s location. This helps provide mobility for many who are traditionally transportation disadvantaged and not wel...

To what extent do experiences in childhood and parental influences shape mobility choices and behaviors in adulthood? This is the central question that this research seeks to answer through an analysis of a unique survey data set that includes variables describing a number of contextual factors from the individual’s childhood. The study presents a...

In consumer surveys, more information per response regarding preferences of alternatives may be obtained if individuals are asked to rank alternatives instead of being asked to select only the most-preferred alternative. However, the latter method continues to be the common method of preference elicitation. This is because of the belief that rankin...

This chapter provides a discussion of the important research topics for understanding behavioral responses to highly automated vehicles (AVs) as discussed at a breakout session at the Automated Vehicle Symposium (AVS) 2018. The session, and thus this chapter, highlights the need for valid behavioral data on which to base assumptions, models, foreca...

Surveys of behavior could benefit from information about people’s relative ranking of choice alternatives. Rank ordered data are often collected in stated preference surveys where respondents are asked to rank hypothetical alternatives (rather than choose a single alternative) to better understand their relative preferences. Despite the widespread...

This paper is motivated by the increasing recognition that modeling activity-travel demand for a single day of the week, as is done in virtually all travel forecasting models, may be inadequate in capturing underlying processes that govern activity-travel scheduling behavior. The considerable variability in daily travel suggests that there are impo...

Activity-travel choices of individuals are influenced by spatial dependency effects. As individuals interact and exchange information with, or observe the behaviors of, those in close proximity of themselves, they are likely to shape their behavioral choices accordingly. For this reason, econometric choice models that account for spatial dependency...

Household vehicle miles of travel (VMT) has been exhibiting a steady growth in post-recession years in the United States and has reached record levels in 2017. With transportation accounting for 27 percent of greenhouse gas emissions, planning professionals are increasingly seeking ways to curb vehicular travel to advance sustainable, vibrant, and...

Prior research has shown that land use patterns and the spatial configurations of cities have a significant impact on residential energy demand. Given the pressing issues surrounding energy security and climate change, there is renewed interest in developing and retrofitting cities to make them more energy efficient. Yet deriving micro-scale reside...

One approach to assessing the quality of life associated with a person’s daily travel is to obtain a summary judgment of that individual’s satisfaction with travel. Such a judgment could be considered a measure of the transportation-domain-specific subjective well-being (SWB). A number of such summary measures have been developed, including happine...

The recently emerging trend of self-driving vehicles and information sharing technologies, made available by private technology vendors, starts creating a revolutionary paradigm shift in the coming years for traveler mobility applications. By considering a deterministic traveler decision making framework at the household level in congested transpor...

There is mounting evidence to suggest that the urban built form plays a crucial role in household energy consumption, hence planning energy efficient cities requires thoughtful design at multiple scales - from buildings, to neighborhoods, to urban regions. While data on household energy use are essential for examining the energy implications of dif...

There are a number of disruptive mobility services that are increasingly finding their way into the marketplace. Two key examples of such services are car-sharing services and ride-sourcing services. In an effort to better understand the influence of various exogenous socio-economic and demographic variables on the frequency of use of ride-sourcing...

Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a...

A semi-nonparametric generalized multinomial logit model, formulated using orthonormal Legendre polynomials to extend the standard Gumbel distribution, is presented in this paper. The resulting semi-nonparametric function can represent a probability density function for a large family of multimodal distributions. The model has a closed-form log-lik...

Model estimation results of MNL, SGMNL-11, SGMNL-21 and SGMNL-22. (TIF)

Probability density distributions of random components in the “SGMNL-22” model. (TIF)

Transit choice probability for a specific commuter in response to an improvement in service frequency. (TIF)

Comparisons of semi-nonparametric probability densities when K = 1. (TIF)

Comparisons of semi-nonparametric probability densities when K = 2. (TIF)

Comparisons of disaggregate marginal effects and elasticities. (TIF)

An example of “c” matrix. (TIF)

Comparisons of aggregate marginal effects (AME) and elasticities (AE). (TIF)

Comparisons of market shares and individual choice probabilities. (TIF)

Building energy consumption makes up 40% of the total energy consumption in the United States. Given that energy consumption in buildings is influenced by aspects of urban form such as density and floor-area-ratios (FAR), understanding the distribution of energy intensities is critical for city planners. This paper presents a novel technique for es...

The recently emerging trend of self-driving vehicles and information sharing technologies, made available by private technology vendors, starts creating a revolutionary paradigm shift in the coming years for traveler mobility applications. By considering a deterministic traveler decision making framework at the household level in congested transpor...

This paper presents a methodology for the calculation of household travel energy consumption at the level of the traffic analysis zone in conjunction with information that is readily available from a standard four-step travel demand model system. The methodology presented in this paper embeds two algorithms. The first algorithm provides a means of...

There is considerable interest in modeling and forecasting the impacts of autonomous vehicles on travel behavior and transportation network performance. In an autonomous vehicle future, individuals may privately own such vehicles, or use mobility-on-demand services provided by transportation network companies that operate shared autonomous vehicle...

Smartphone ownership and use are becoming increasingly prevalent around the world. However, little is known about the impacts of this technology on activity travel choices. The objective of this study was to determine the extent to which smartphone ownership and use influence activity travel demand, after controlling for other lifestyle and demogra...

This paper explores differences in activity-travel behavior within the millennial generation with a view to better understand how their choices might shape transportation systems of the future. Through the estimation of a Generalized Heterogeneous Data Model on a special millennial mobility attitudes survey data set, this study investigates heterog...

Millennials, defined in this study as those born between 1979 and 2000, became the largest population segment in the United States in 2015. Compared to recent previous generations, they have been found to travel less, own fewer cars, have lower driver’s licensure rates, and use alternative modes more. But to what extent will these differences in be...

This research is motivated by the need to improve transportation policy analysis through the development of a holistic framework to evaluate transportation externalities. Traditionally, transportation planning has been focused primarily on the improvement of transportation infrastructure and network performance and little attention has been paid to...

We propose a stochastic frontier approach to estimate budgets for the multiple discrete-continuous extreme value (MDCEV) model. The approach is useful when the underlying time and/or money budgets driving a choice situation are unobserved, but the expenditures on the choice alternatives of interest are observed. Several MDCEV applications hitherto...

Microsimulation models that simulate travel demand at the level of individual travelers have been gaining increasing interest among practitioners. Transportation planning agencies across the country are steadily migrating to activity-based microsimulation models, which provide considerable flexibility when testing policy scenarios. Generating a syn...

Universities with large student enrollments often constitute special generators and contribute substantially to a region's travel demand. Universities are not only large in size but also unique in nature because the travel patterns of university students are substantially different from those of the general population. Student travel patterns are d...

This paper presents a comprehensive model of injury severity that accounts for unmeasured driver behavior attributes. The results of the model have important implications for the design of safety interventions and advanced vehicular features and technologies. Engineering designs that accommodate the diminished capabilities of older drivers, that in...

Incentive-based travel demand management strategies are gaining increasing attention because they are generally considered more acceptable by the traveling public and policy makers. This study presented a detailed analysis and modeling effort aimed at understanding how incentives affected traveler choices by using data collected from a reward-based...

Activity-based models (ABMs) adopt the notion of tours to model activity travel patterns, because the concept of a tour closely mimics how individuals chain their activities in the real world. Each tour may be defined by a primary destination that corresponds to a primary purpose and may include a multitude of secondary stops on the way to the prim...

The automotive industry is witnessing a revolution with the advent of advanced vehicular technologies, smart vehicle options, and fuel alternatives. However, there is very limited research on consumer preferences for such advanced vehicular technologies. The deployment and penetration of advanced vehicular technologies in the marketplace, and plann...

Problem, research strategy, and findings: Many cities have adopted minimum parking requirements, but there is relatively poor information about how parking infrastructure has grown. We estimate how parking has grown in Los Angeles County (CA) from 1900 to 2010 and how parking infrastructure evolves, affects urban form, and relates to changes in aut...

Spatial transferability of travel demand models has been an issue of considerable interest, particularly for small- and medium-sized planning areas that often do not have the resources and staff time to collect large-scale travel survey data and estimate model components native to the region. Traditional approaches to identifying geographic context...

This paper presents an empirical comparison of the following approaches to estimate annual mileage budgets for multiple discrete-continuous extreme value (MDCEV) models of household vehicle ownership and utilization: (a) a log-linear regression approach to model observed total annual household vehicle miles traveled (AH-VMT), (b) a stochastic front...

Research on travel demand modeling has primarily focused on weekday activity-travel patterns. However, weekend activities and travel constitute a major component of individuals' overall weekly activity-travel participation. This paper describes a modeling effort that focuses on weekend activity-travel demand for discretionary events. This study bri...

Most of the recent advances in activity-based models (ABMs) have been on the demand side, that is, description of the individual needs for certain types of activities and travel as a function of person, household, and accessibility variables. The supply side of activities that describes characteristics of the locations where a certain activity can...