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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 which the two worlds complement one another or substitute for one another. Shopping is one of the activity realms in which the virtual and physical spaces are increasingly interacting. This paper aims to unravel the relationships between online and in-person activity engagement in the shopping domain, while explicitly distinguishing between shopping for non-grocery goods, grocery products, and ready-to-eat meals. Data from the 2017 Puget Sound household travel survey is used to estimate a multivariate ordered probit model of the number of days in a week that a sample of households engages in in-person activity engagement and online activity engagement for each of these shopping activity types – leading to a model of six endogenous outcomes. Model results show that there are intricate complementary and substitution effects between in-person and online shopping activities, that these activities are considered as a single packaged bundle, and that the frequencies of these activities are significantly affected by income, built environment attributes, and household structure. The findings suggest that travel forecasting models should incorporate model components that capture the interplay between in-person and online shopping engagement and explicitly distinguish between non-grocery and grocery shopping activities. Policies that help bridge the digital divide so that households of all socio-economic strata can access goods and services in the virtual world would help improve quality of life for all. Finally, the paper highlights the need to bring passenger and freight demand modeling, at least within urban contexts, into a single integrated structure.

The current study is motivated by the need to better understand the potential impacts that vehicular automation may have on individual decisions of residential and work relocation in a future autonomous vehicle (AV) scenario. The study employs a multivariate approach to model five behavioral dimensions simultaneously: (1) technology-savviness (TS) propensity, (2) interest in productive use of travel time (IPTT) propensity, (3) interest in work relocation, (4) interest in residential relocation, and (5) tolerance to an increase in commute travel time. Data from a web-based survey of commuters in 2017 in the Dallas-Fort Worth Metropolitan Area (DFW) is employed. The results show that both TS and IPTT, as well as demographic variables, impact relocation decisions when individuals have a private AV available for their commute. Importantly, there is considerable heterogeneity across individuals in the willingness to relocate and/or accept longer commute times in an AV future. As such, our model results may be used to inform inputs to land use and travel demand models in an AV future. Also, our results suggest that the magnitude of value of travel time savings (VTTS) decrease considered in many earlier AV impact simulation studies may be much higher than reality. Relative to 50% and even 100% VTTS decreases assumed in many studies, our results suggest a much more modest 30% or so overall decrease in VTTS because of the ability to commute in a privately-owned AV. Finally, our results do predict a rather substantial extent of urban sprawl due to AVs, potentially up to a 68% increase in the horizontal spread of cities such as Dallas-Fort Worth, unless proactive planning and policies are implemented to avert such consequences of AVs.

Even as ride-hailing has become ubiquitous in most urban areas, its impacts on individual travel are still unclear. This includes limited knowledge of demand characteristics (especially for pooled rides), travel modes being substituted, types of activities being accessed, as well as possible trip induction effects. The current study contributes to this knowledge gap by investigating ride-hailing experience, frequency, and trip characteristics through two multi-dimensional models estimated using data from the Dallas-Fort Worth Metropolitan Area. Ride-hailing adoption and usage are modeled as functions of unobserved lifestyle stochastic latent constructs, observed transportation-related choices, and sociodemographic variables. The results point to low residential location density and people’s privacy concerns as the main deterrents to pooled ride-hailing adoption, with non-Hispanic Whites being more privacy sensitive than individuals of other ethnicities. Further, our results suggest a need for policies that discourage the substitution of short-distance “walkable” trips by ride-hailing, and a need for low cost and well-integrated multi-modal systems to avoid substitution of transit trips by this mode.

New app-based mobility services are revolutionizing urban transport. Particularly, ride-hailing has experienced a worldwide boom in the last decade since it provides a convenient, on-demand door-to-door service for urban trips. In parallel, an increasing number of studies have been conducted, mainly analyzing individuals’ behavior towards this transport option, mobility patterns, as well as ride-hailing effects on urban sustainability. Nevertheless, the majority of these contributions focus on US cities, while almost no efforts have been devoted to other geographic areas, such as Europe. Cities in this continent present some particular characteristics that make them a case worth investigating, such as a higher presence of public transport modes or a great public concern on environmental issues. The aim of this paper is to explore travel behavior towards ride-hailing services in a European city. Based on the information collected from a survey campaign in the city of Madrid (Spain), we estimate a Generalized Heterogeneous Data Model approach to identify the key factors motivating ride-hailing adoption and frequency of use. The paper identifies a higher adoption of ride-hailing services among young, well-educated, wealthy individuals, who are familiar with new technologies. More interestingly, the research suggests a noticeable role played by environmental consciousness in ride-hailing frequency of use, compared to US cities. Particularly, individuals with lower environmental consciousness are more car-oriented, which is also linked to a more intense use of ride-hailing. By contrast, individuals with a higher environmental consciousness tend to reduce their use of ride-hailing, which reflects their propensity towards public transport in a transit-intensive background.

The objective of this paper is to evaluate the effectiveness of a dedicated short-range communication (DSRC)-based wireless vehicle-to-vehicle (V2V) communication system, called the overtaking assistant, devised for improving safety during overtaking (also referred to as passing) maneuvers on two-lane rural highways. Specifically, the paper examines the influence of vehicular kinematics (vehicle speeds, accelerations and distances), driver behavior (drivers’ perception/reaction time and overtaking rate), and DSRC characteristics (power settings, communication range, packet errors, sensor errors, and estimation inaccuracy) on the effectiveness of DSRC systems in predicting unsafe overtaking maneuvers. To this end, the paper utilizes a microscopic traffic simulator called VEhicles In Network Simulation (VEINS) that supports the simulation of wireless communication protocols in Vehicular Ad-hoc NEtworks (VANETs). 18,000 overtaking maneuvers – with roughly 10,000 collision maneuvers – were simulated to consider heterogeneity in vehicular kinematics, driver behavior, and DSRC performance. The overtaking assistant predicts whether a collision will occur and warns the driver before the maneuver begins. A descriptive analysis followed by a multivariate analysis (using binary discrete outcome models) of the simulated data reveals that the majority of collisions that could not be detected were due to the vehicles being out of communication range for the communication power settings used in the simulation. Packet errors, or failed communications, at a rate of up to 50% did not have a significant influence on the ability to detect collisions. These results suggest that the most important step in paving the way toward advanced driver assistance systems for rural highway overtaking maneuvers is to broaden the communication range of DSRC devices.

Pooled mobility services hold substantial promise as a means to provide better accessibility to those who may find it difficult to drive themselves, while also promoting sustainable transportation efforts. In this paper, we develop a joint revealed preference-stated preference model for the choice between pooled versus private ride-hailing that (a) accommodates a suite of individual-level socio-demographics, individual-level psycho-social attributes, built environment variables, and trip-level variables, and (b) explicitly recognizes the importance of considering familiarity with pooled ride-hailing (RH) as an integral element of the pooled RH choice process. The primary source of data for the analysis is drawn from a 2019 survey of Austin, Texas residents. Our results underscore the value of using psycho-social latent constructs in the adoption of current and emerging mobility services, both in terms of improved prediction fit as well as in terms of designing proactive strategies to promote pooled RH service adoption. Women, older adults, and non-Hispanic/non-Latino Whites have a low propensity to choose the pooled RH mode, while employed individuals, highly educated individuals, and those living in high density urban areas have a high propensity. Overall, the average VTT estimate is $27.80 per hour for commute travel, $19.40 per hour for shopping travel, and $10.70 per hour for leisure travel, while the willingness to pool (that is, the willingness to pay to not pool a ride or WTS) averages about 62 cents for commute travel, $1.70 for shopping travel and $1.32 for leisure travel. These estimates can be used by TNCs and cities to consider new integrated pooled RH-fixed transit service designs, position traffic congestion alleviation strategies and new mobility services, and customize information campaigns to promote pooled RH mode use.

Technology providers, car manufacturers, and public agencies all need to work together to undertake extensive testing of fully autonomous vehicles (AVs) on public roads before such AVs are allowed to freely travel in ways similar to human-driven vehicles. This raises the importance of understanding public perceptions regarding safety considerations when traveling alongside AVs. This study makes use of a national survey conducted by the Pew Research Center to identify the affective, socio-demographic and technology-use attributes that affect an individual’s perception of the safety of sharing the road with AVs (PSSRAV) and identifies measures and interventions that can be undertaken to improve PSSRAV. Additionally, we evaluate individual preferences for AV regulations. Our results underscore the importance of the need for service providers and public agencies to be cognizant of the demographic and lifestyle/affective emotion considerations shaping AV safety perceptions and opinions about AV regulations. In particular, there is a need not only to focus on technological and other infrastructure components of AV development, but also to recognize the socio-technical considerations and human-related factors of the end-users. Our findings should be of substantial interest in the planning, design, deployment, and introduction of AVs within a safe and minimally regulated public operating arena.

Understanding the “if” and “when” of autonomous vehicle (AV) adoption is of clear interest to car manufacturers in their positioning of business processes, but also to transportation planners and traffic engineers. In this paper, we examine the individual-level AV adoption and timing process, considering the psycho-social factors of driving control, mobility control, safety concerns, and tech-savviness. A ranked choice stated preference design is used to elicit responses from Austin area residents regarding AV adoption. Our results underscore the need to examine the adoption of technology through a psycho-social lens. In particular, technology developments and design should not be divorced from careful investigations of habits and consumption motivations of different groups of individuals in the population. The findings from our analysis are translated to specific policy actions to promote AV adoption and accelerate the adoption time frame.

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 planning for possible market adoption scenarios, calls for the collection and analysis of consumer preference data related to these emerging technologies. This study aims to address this need, offering a detailed analysis of consumer preference for alternative fuel types and technology options using data collected in stated choice experiments conducted on a sample of consumers from six metropolitan cities in South Korea. The results indicate that there is considerable heterogeneity in consumer preferences for various smart technology options such as wireless internet, vehicle connectivity, and voice command features, but relatively less heterogeneity in the preference for smart vehicle applications such as real-time traveler information on parking and traffic conditions.

Recent advances in global positioning systems (GPS) technology have resulted in a transition in household travel survey methods to test the use of GPS units to record travel details, followed by the application of an algorithm to both identify trips and impute trip purpose, typically supplemented with some level of respondent confirmation via prompted-recall surveys. As the research community evaluates this new approach to potentially replace the traditional survey-reported collection method, it is important to consider how well the GPS-recorded and algorithm-imputed details capture trip details and whether the traditional survey-reported collection method may be preferred with regards to some types of travel. This paper considers two measures of travel intensity (survey-reported and GPS-recorded) for two trip purposes (work and non-work) as dependent variables in a joint ordered response model. The empirical analysis uses a sample from the full-study of the 2009 Indianapolis regional household travel survey. Individuals in this sample provided diary details about their travel survey day as well as carried wearable GPS units for the same 24-h period. The empirical results provide important insights regarding differences in measures of travel intensities related to the two different data collection modes (diary and GPS). The results suggest that more research is needed in the development of workplace identification algorithms, that GPS should continue to be used alongside rather than in lieu of the traditional diary approach, and that assignment of individuals to the GPS or diary survey approach should consider demographics and other characteristics.

A number of Advanced Traveler Information System (ATIS) field experiments are being undertaken to study the effectiveness of the ATIS concept in ameliorating traffic congestion and reducing delays. Many of these experiments require the participation of private drivers willing to allow in-vehicle navigation units to be installed in their vehicles over an extended period of time. A critical part of any ATIS field experiment is the selection or recruitment of private drivers to fulfill the multi-purpose participation needs of the ATIS experiment. To provide an informed basis for designing such a driver recruitment effort, it is important to understand the factors affecting driver recruitability or “willingness to participate.” This research presents the results of a quantitative analysis of driver recruitability conducted to aid in the design of recruitment procedures for ADVANCE (Advanced Driver and Vehicle Advisory Navigation Concept), the largest ATIS field experiment of its kind. The approach used a telephone survey to assess driver willingness to participate in the ADVANCE field experiment and to explore variations in that willingness among different drivers and across characteristics of the ADVANCE system and experimental design. The results indicate that the willingness to participate in the ADVANCE field test is greater for men, persons who hold executive or managerial occupations, individuals who drive extensively, persons who use electronic devices such as personal computers and car phones regularly, and persons who have positive beliefs regarding the usefulness of the ADVANCE concept. The result also suggest that drivers' willingness to participate is not strongly affected by monitoring/reporting requirements such as responding to surveys, mailing electronically stored records of system operation, and periodic service requirements. However, the willingness decreases considerably if drivers have to bear the financial responsibility for damage of the navigation equipment and any equipment-caused electrical failures to the car. Finally, the incentive of a lottery prize raises the level of participation willingness. These results have important implications for the recruitment effort, both in terms of recruiting drivers for participation in the demonstration and specifying the operational details of the field test.