Konstadinos Goulias

• Ph.D., MS. Laurea
• Professor at University of California, Santa Barbara

Autonomous electric vehicles (AEVs) can potentially revolutionize the transportation landscape, offering a safer, contact-free, easily accessible, and more eco-friendly mode of travel. Prior to the market uptake of AEVs, it is critical to understand the consumer segments that are most likely to adopt these vehicles. Beyond market adoption, it is al...

The COVID-19 pandemic has significantly shifted travel behaviors, with major changes observed in online shopping and travel to work. Despite considerable research into pandemic-induced changes in travel behavior, it remains uncertain whether these new patterns have persisted or reverted to pre-pandemic norms. This study addresses this uncertainty b...

Accessibility, the ease or difficulty with which activity opportunities can be reached from a given location, can be measured using the cumulative number of opportunities from an origin within a given amount of travel time and/or distance. Estimating accessibility indicators is used to show the level of service quality offered by a transportation s...

Accessibility to opportunities is strongly correlated with travel behaviors. This research, in particular, centered on individual daily accessibility, which quantifies the total number of opportunities of each type that can be reached within a certain travel time from the destinations an individual visited in a day. Existing studies rarely focused...

In this study, the most recent American Time Use Surveys containing reported activity-based emotions and sensations information before (10,378 respondents in 2013) and during (6,902 respondents in 2021) the COVID-19 pandemic are used to assess if time use related individuals’ subjective wellbeing (SWB) decreased in the pandemic. Given that the coro...

Urban expansion is a form of land cover and land use change (LCLUC) that occurs globally, and population growth can be a driver of and be driven by LCLUC. Determining the cause–effect relationship is challenging because the temporal resolution of population data is limited by decadal censuses for most countries. The purpose of this study is to expl...

Social Media have increasingly provided data about the movement of people in cities making them useful in understanding the daily life of people in different geographies. Particularly useful for travel analysis is when Social Media users allow (voluntarily or not) tracing their movement using geotagged information of their communication with these...

Movement is manifested through a series of patterns at multiple spatial and temporal scales. Movement data today are becoming available at increasingly fine-grained temporal granularity. These observations often represent multiple behavioral modes and complex patterns along the movement path. However, the relationships between the observation scale...

Understanding the mental process of public acceptance of autonomous vehicles (AVs) is important to the prediction and change of adoption behavior. We present a conceptual model to incorporate background factors such as demographic variables and travel behaviors attributes to the understanding of AV perceived usefulness and intention to adopt AVs. U...

In this study using data from the 2017 National Household Travel Survey in California from 26,078 survey participants, sequence analysis is used to estimate a fragmentation indicator of people's daily schedules. Then, spatial clustering is used to find groups of observations with similarly high or low fragmentation using the longitude and latitude...

Interaction analysis for moving individuals in space and time can contribute to understanding urban dynamics and human social networks. Recent advancements in trajectory analytics have created methods to identify and extract spatiotemporal patterns of interaction using movement tracking data. However, existing definitions and classifications of int...

A growing number of research attempts have been made to enhance our knowledge about the characteristics of the potential early Autonomous Vehicle (AV) adopters. However, little is known about whether the public attitudes towards AVs change over time and how. With a multiyear cross-sectional travel survey data of the Puget Sound Region that encompas...

Car ownership is linked to higher car use, which leads to important environmental, social and health consequences. As car ownership keeps increasing in most countries, it remains relevant to examine what factors and policies can help contain this growth. This paper uses an advanced spatial econometric modeling framework to investigate spatial depen...

Advances of unmanned aircraft system (UAS) technology have spurred a rapid investment of commercial UAS use in broad public domains, such as cargo transport, agriculture support, emergency response, on-demand communication, and infrastructure health monitoring. Urban unmanned aerial transportation that can transport passengers over short distances...

This paper uses movement as a marker to study interactions in humans and animals to better understand their collective behaviors. Interaction is an important driving force in social and ecological systems. It can also play a significant role in the transmission of infectious diseases and viruses as witnessed during the ongoing COVID-19 pandemic. Al...

Population ageing has been a thorny issue in many countries. One of the challenges is how to improve and change transportation design and transport policy development to adapt to the dramatic changes in the composition of our population. In this paper, we apply a network-based approach of human mobility measurement called “motif” to investigate the...

In this chapter the inclusion of psycho-attitudinal metrics about places and perceptions of the environment in travel behavior is reviewed and illustrated with two examples at different geographic scales. First, specific destinations are used as case studies to demonstrate the use of attitudes as Sense of Place components and their correlation with...

This paper demonstrates the use of motif and sequence analysis in tandem to analyse differences and commonalities between telecommuters and usual commuters. In terms of substantive findings, telecommuters are by far more diverse in their allocation of time to places, activities, and travel. Approximately 20% of telecommuters stay at home all day du...

The extensive record of Landsat imagery is commonly used to map urban land-cover and land-use change. Random forest (RF) classification was applied for mapping more detailed urban land-use and change categories than is typically attempted with Landsat data. Two dates of Landsat imagery (1990 and 2015) were utilized with surface reflectance, Vegetat...

We investigate the evolution of the Chinese Spring Festival travel network during COVID-19 early outbreak (Jan 17 to Feb 23, 2020) in China and explore the impacts of COVID-19 on the evolution of the intercity travel network. We find that the connections of a China city with other 27.9 cities were cut off after the Wuhan lockdown (Jan 23). Correlat...

In this paper, we develop a new joint pattern recognition method that combines network motif-based analysis with activity sequence-based analysis. We use the advantages of both methods in creating groups of patterns that have within them distinct pattern homogeneity and across-pattern heterogeneity. The first portion of the analysis here applies a...

Sequence analysis is used in this paper to measure fragmentation in activity participation and travel. Fragmentation here is defined as the sequencing of many short and long activities and trips that happen in a personal daily schedule. Studying sequences of daily episodes (each activity at a place and each trip) is preferable over other techniques...

The key to Autonomous Vehicles (AVs) successful penetration of markets lies in identifying specific needs that AVs satisfy for daily activity-travel participation of individuals. In this paper we explore whether and to what extent people’s exhibited spatiotemporal activity-travel patterns correlate with their stated perceptions about self-driving c...

In this chapter the inclusion of psycho-attitudinal metrics about places and perceptions of the environment in travel behavior is reviewed and illustrated with two examples at different geographic scales. First, specific destinations are used as case studies to demonstrate the use of attitudes as Sense of Place components and their correlation with...

This research filled a gap in empirically supported knowledge linking the survival and economic success of business establishments to locational characteristics including access to transportation facilities. This relationship was studied for the entire State of California while controlling in a statistically robust way for a variety of factors infl...

A new method of sequence analysis to measure fragmentation in activity participation is presented in this paper. We applied this method to a sample of residents in the Central Coast of California that participated in the California Household Travel Survey in 2012–2013. This method explores sequences of daily activity and travel employing techniques...

In this paper, we analyze travel behavior data of daily summaries and time-of-day dynamics in two different cities from two different countries collected at about the same time. These are the records from diaries of 2890 and 2836 trip makers in Thessaloniki, Greece, and San Diego, California respectively. Using Latent Class Cluster analysis, we fin...

In this paper, a new land use classification method is explored for its utility in explaining travel behavior and as a new dimension in population synthesis for travel demand forecasting. This method is based on latent profile analysis applied to 17 business establishment indicators for each of the more than 20,000 block groups in California. The m...

This study analyzes 8-week long-distance travel records from the California Household Travel Survey for completeness and identifies general types of non-commute long-distance tours using Latent Class Analysis. Likely due to the difficulty of gathering data of this kind, there has been relatively limited study of non-commute long-distance travel, de...

Data of long-distance tours by each household from an 8-week California Household Travel Survey travel log are analyzed in this paper. Each tour record contains summary data from a single-day diary, household sociodemographic information, and place of residence characteristics. Each tour contains a main trip, selected tours with a main trip that is...

Using data of attitudes in the Puget Sound region we first identify predispositions in favor of car use (car loving persons and households) and distinguish them from other predispositions favoring other modes (transit and carsharing lovers). Then we explore if like-minded people (homophily) live together and examine heterogeneity within their house...

Using data of attitudes in the Puget Sound region we first identify predispositions in favor of car use (car loving persons and households) and distinguish them from other predispositions favoring other modes (transit and carsharing lovers). Then we explore if like-minded people (homophily) live together and examine heterogeneity within their house...

In this paper, we employ structural regression models to identify the differences and commonalities among life cycle stages in daily interpersonal contacts and their activity-travel time allocation. The daily contacts (with family, friends, schoolmates, co-workers, clubmates, and others), duration of activities by type, and travel time are the endo...

Longitudinal data have the potential to reveal the causal mechanism underlying changes in observed behavior, can protect us from finding spurious relationships, study time precedence, and offer strength in helping discover association among variables. In this paper, we expand our previous analysis of the only longitudinal travel behavior database i...

The role of time (as a constrained resource) in terms of budgets and expenditures is of great importance in travel behavior analysis within the context of daily activity engagement choices, emotional well-being, and quality of life. This research investigated the behavioral links between activity time budgets and episodic well-being measures in a t...

This paper describes a new method of population synthesis that includes land use information. The method is based on an initial identification of suitable land use summaries to build a spatial taxonomy at any spatial scale. This same taxonomy is then used to classify household travel survey records (persons and households) and in parallel geographi...

This study used activity-travel diary data to analyze the time-of-day dynamics of interpersonal contacts and examined their complex relationship with other activity-travel time allocation and personal accessibility dynamics. In total, 2,942 activity-travel diaries from 1,471 participants were used to identify five unique patterns of daily human int...

In this paper, we demonstrate the use of an inexpensive and easy-to-collect long-term dataset to address the problems caused by basing activity space studies off short-term data. In total, we use 63,114 geo-tagged tweets from 116 unique users to create individuals’ activity spaces based on minimum bounding geometry (convex hull). By using polygon d...

In this paper data from 230 households observed in ten different occasions (waves) from 1989 to 2002 in the Puget Sound region are used to explore relationships among number of cars owned, number of trips driving alone, and number of trips sharing cars with household members. Using a mixture latent class Markov model we identify four distinct group...

The field of travel behaviour dynamics represented a vibrant research area in the 1980s and the 1990s (Golob & Meurs, 1987; Golob, Kitamura, & Long, 1997; Kitamura, 1990), but has since, probably due to lack of mobility panel data, received relatively little attention by transportation researchers. Nevertheless, through the use of panel data (repea...

In this project we seek to fill a gap in empirically supported knowledge linking the survival and economic success of business establishments to local land use and access to the transportation system that serves these establishments. We investigate this relationship for the entire State of California over the last two decades while controlling in a...

In this paper, we demonstrate the use of an inexpensive and easy-to-collect long-term dataset to address the problems caused by basing activity space studies off short-term data. In total, we use 63,114 geo-tagged tweets from 116 unique users to create individuals’ activity spaces based on minimum bounding geometry (convex hull). By using polygon d...

For elderly people (those 65 years of age or older), transportation mobility is critical to meeting activity engagement needs and maintaining life satisfaction and well-being. This paper explores the underlying correlation structure between activity time-use patterns and the degree of episode well-being (or happiness) of the elderly population. The...

Integrated models of land use and transportation are aimed at addressing regional issues related to congestion, mobility, and economic competitiveness. Integral to these model systems is freight transport, which plays a huge role in the economic vitality of the region in the form of distribution and complex interactions between various stakeholders...

In this paper we use Twitter data and a recently developed algorithm at the University of California Santa Barbara to extract Origin-Destination pairs in the Greater Los Angeles metropolitan area known as the Southern California Association of Governments (SCAG) region. This algorithm contains two steps: individual-based trajectory detection and pl...

We usually assume that each commuter is an efficient traveller, which means they maximize trip utility. From a spatial optimization perspective, a commuter might therefore choose the nearest station to reach their destination. However, based on a survey at seven train stations in Perth, Western Australia, only between 30 and 80 percent of commuters...

Longitudinal data have the potential to reveal the causal mechanism underlying changes in observed behavior, can protect us from finding spurious relationships, study time precedence, and offer strength in helping discover association among variables. In this paper, we expand our previous analysis of the only longitudinal database in the US that ha...

In this paper we explore the relationships among long distance travel, Subjective WellBeing (SWB), and Sense of Place (SOP) for a sample of 789 students at the University of California Santa Barbara (UCSB). SWB is measured using Satisfaction With Life Scale (SWLS) items developed by Diener. SOP is measured using an updated version of questions used...

In this paper longitudinal mixed Markov latent class analysis is used to explore patterns of behavioral change in the ten waves of the Puget Sound Transportation Panel. We explore this pattern recognition in databases that include households participating in all waves (230 households) and households participating in five waves (461) but enter the p...

In this paper, we employ structural regression models to identify the differences and commonalities among life cycle stages in daily interpersonal contacts and their activity-travel time allocation. We use data from a two-day geocoded time use survey that enables the creation of variables depicting daily contacts with family, friends, schoolmates,...

The application of a comprehensive model system of vehicle fleet composition and evolution is described; this model system is capable of taking a base-year vehicle fleet and making it evolve over time in annual time steps through the events of vehicle disposal, replacement, and acquisition. The model system is sensitive to a host of socioeconomic,...

This research draws on advances in spatial networks by representing a city as a weighted primal graph of a street network; this format takes into account the context of the location and its importance. The link-based multiple centrality indexes (L-MCIs) are introduced to represent location properties in terms of closeness, intermediacy, straightnes...

The way in which a person organizes his or her day, both temporally and spatially, is a highly important matter to travel behavior and travel demand modeling. Many times, the focus of these models is to accurately predict the “where” and “when”, without paying adequate attention to the “why.” The participation in activities, and therefore the selec...

In this paper, we explore the diurnal dynamics of joint activity participation in a small city in Pennsylvania, USA, using behavioral data and an inventory of business establishments. We account for the variation caused by the collective impact of social, temporal and spatial choices of individuals to produce predicted space–time visualizations of...

Understanding the way in which people conduct their daily activities is the central focus of travel behavior modelers. This often requires an understanding of the way in which people interact with their surroundings. Theorists have paid special attention to the interactions of people and place, specifically the endowment of meaning to places (terme...

Mobility is critical for social integration in a complex urban society and essential to the maintenance of life satisfaction and well-being. Subjective well-being has recently become a topic of interest within the transportation research community. This paper aims to understand the fundamental linkages between subjective well-being or happiness and...

Household vehicle ownership and fleet composition are choice dimensions that have important implications for policy making, particularly in the arena of energy and environmental sustainability. In the context of household vehicle ownership and type choice, it is conceivable that substantial spatial interaction effects are caused by both observed an...

This paper develops and estimates a multiple discrete continuous extreme value model of household activity generation that jointly predicts the activity participation decisions of all individuals in a household by activity purpose and the precise combination of individuals participating. The model is estimated on a sample obtained from the post cen...

The aim of this paper is to investigate the interrelationship between urban environment and walking to school, and how teenagers’ perceptions towards walkability constraints affect their mode choice. An advanced hybrid mode choice model is developed, where the utilities of the alternative modes depend on the modes’ characteristics, teenagers’ socio...

Models explaining and predicting human travel behavior have gone through many changes in the past few decades. As researchers attempt to explain more and predict with more accuracy, the inclusion of social interactions in modeling and simulation is being recognized as a necessity. Among these efforts, researchers have focused on issues such as the...

Purpose — In this paper we describe a total design data collection method (expanding the definition of the usual “total design” terminology used in typical household travel surveys) to emphasize the need to describe individual and group behaviors embedded within their spatial, temporal, and social contexts. Methodology/approach — We first offer an...

Island communities are often not capable of autonomously developing comprehensive plans for environmental protection, transport and tourism development; at the same time, they are increasingly anxious to preserve their identity, environment, natural and cultural wealth. Sustainable (green) transportation offers a solution in the form of an integrat...

This paper continues a series of papers that address the relationship between travel behavior and land use patterns under a structural equations modeling framework in different contexts for comparative purposes. The proposed model structure in this paper is, by design, heavily influenced by a model developed for Lisbon, Portugal; Seattle, Washingto...

In this paper an estimation-is made of a joint household-level-model-of the number of vehicles owned by a household, the vehicle type choice of each vehicle, the annual mileage on each vehicle, and the individual assigned as the primary driver for each vehicle. A version of the proposed model system currently serves as the engine for a household ve...

This paper presents results from the application of a comprehensive socioeconomic and demographic model system in conjunction with a continuous-time, activity-based microsimulation model of travel demand developed for the Southern California Association of Governments. The socioeconomic model system includes two major components. The first is a syn...