Technological advances are bringing connected and autonomous vehicles (CAVs) to the ever- evolving transportation system. Anticipating the public acceptance and adoption of these technologies is important. A recent internet-based survey was conducted polling 347 Austinites to understand their opinions on smart-car technologies and strategies. Ordered-probit and other model results indicate that respondents perceive fewer crashes to be the primary benefit of autonomous vehicles (AVs), with equipment failure being their top concern. Their average willingness to pay (WTP) for adding full (Level 4) automation ($7,253) appears to be much higher than that for adding partial (Level 3) automation ($3,300) to their current vehicles. This study estimates the impact of demographics, built-environment variables, and travel characteristics on Austinites’ WTP for adding such automations and connectivity to their current and coming vehicles. It also estimates adoption rates of shared autonomous vehicles (SAVs) under different pricing scenarios ($1, $2, and $3 per mile), choice dependence on friends’ and neighbors’ adoption rates, and home-location decisions after AVs and SAVs become a common mode of transport. Higher-income, technology-savvy males, living in urban areas, and those who have experienced more crashes have a greater interest in and higher WTP for the new technologies, with less dependence on others’ adoption rates. Such behavioral models are useful to simulate long-term adoption of CAV technologies under different vehicle pricing and demographic scenarios. These results can be used to develop smarter transportation systems for more efficient and sustainable travel.

Assessing Public Opinions of and Interest in New Vehicle Technologies: An Austin Perspective

This overview article proposes a revised approach to improve the urban realm, against the backdrop of new models for delivering transport services as digitalisation, collaborative consumption and autonomous technologies take hold. We propose the concept of modal efficiency illustrated through a conceptual framework situating both existing and emerging modes of transport around spatial and temporal dimensions. This framework helps us evaluate how the push towards smaller and more flexible transport services in questionable settings can have significant and adverse effects on road capacity, increasing congestion and in the longer term impacting urban form. We propose linking urban land use characteristics to travel price and modal efficiency to improve the broader transport system and guide the sustainable development of our cities. Mobility as a service (MaaS) based on shared mobility and modal integration constitutes a major opportunity to deliver on these ideals, if organised appropriately. Widely diverging service delivery models for MaaS are introduced, including commercially-motivated models (which may exacerbate efficiency issues), and systems which incorporate an institutional overlay. We propose consideration of a government-contracted model for MaaS, where road pricing is incorporated as an input into package price, defined by time of day, geography and modal efficiency. In amidst the hype of new mobility technologies and services, a critical assessment of the realm of possibilities can better inform government policy and ensure that digital disruption occurs to our advantage.

Mobility as a service (MaaS): Charting a future context

Excessive dependence on autonomous vehicles (AVs) may exacerbate traffic congestion and increase exhaust emissions in the future. The diffusion of AVs may be significantly affected by the public’s acceptance. A few factors that may affect people’s acceptance of AVs have been researched in the existing studies, one-third of which cited behavioral theories, while the rest did not. A total of seven factors with behavior theories are screened out that significantly affect the acceptance intention, including perceived ease of use, attitude, social norm, trust, perceived usefulness, perceived risk, and compatibility. Six factors without behavior theories are summed up that affect AV acceptance, namely safety, performance-to-price value, mobility, value of travel time, symbolic value, and environmentally friendly. We found that people in Europe and Asia have substantial differences in attitudes toward AVs and that safety is one of the most concerned factors of AVs by scholars and respondents. Public acceptance of the different types of AVs and consumers’ dynamic preferences for AVs are highlighted in the review too. The quality of literature is systematically assessed based on previously established instruments and tailored for the current review. The results of the assessment show potential opportunities for future research, such as the citation of behavior theories and access to longitudinal data. Additionally, the experimental methods and the utilization of mathematical and theoretical methods could be optimized.

https://www.mdpi.com/2071-1050/12/5/1719/pdf

The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review

https://backend.orbit.dtu.dk/ws/files/149170458/Clusters_self_driving_author_version.pdf

On sceptics and enthusiasts: What are the expectations towards self-driving cars?

Autonomous vehicles (AVs) may significantly change traveler behavior and network congestion. Empty repositioning trips allow travelers to avoid parking fees or share the vehicle with other household members. Computer precision and reaction times may also increase road and intersection capacities. AVs are currently being test driven on public roads and may be publicly available within the next two decades; they therefore may be within the span of 20- to 30-year planning analyses. Despite this time scale, AV behavior has yet to be incorporated into planning models. This paper presents a multiclass, four-step model that includes AV repositioning to avoid parking fees (although incurring additional fuel costs) and increases in link capacity as a function of the proportion of AVs on the link. Demand is divided into classes by value of time and AV ownership. Mode choice—parking, repositioning, or transit—is determined through a nested logit model. Traffic assignment is based on a generalized cost function of ti...

Effects of Autonomous Vehicle Ownership on Trip, Mode, and Route Choice

Automated driving technologies are currently penetrating the market, and the coming fully autonomous cars will have far-reaching, yet largely unknown, implications. A critical unknown is the impact on traveler behavior, which in turn impacts sustainability, the economy, and wellbeing. Most behavioral studies, to date, either focus on safety and human factors (driving simulators; test beds), assume travel behavior implications (microsimulators; network analysis), or ask about hypothetical scenarios that are unfamiliar to the subjects (stated preference studies). Here we present a different approach, which is to use a naturalistic experiment to project people into a world of self-driving cars. We mimic potential life with a privately-owned self-driving vehicle by providing 60 h of free chauffeur service for each participating household for use within a 7-day period. We seek to understand the changes in travel behavior as the subjects adjust their travel and activities during the chauffeur week when, as in a self-driving vehicle, they are explicitly relieved of the driving task. In this first pilot application, our sample consisted of 13 subjects from the San Francisco Bay area, drawn from three cohorts: millennials, families, and retirees. We tracked each subject’s travel for 3 weeks (the chauffeur week, 1 week before and 1 week after) and conducted surveys and interviews. During the chauffeur week, we observed sizable increases in vehicle-miles traveled and number of trips, with a more pronounced increase in trips made in the evening and for longer distances and a substantial proportion of “zero-occupancy” vehicle-miles traveled.

Projecting travelers into a world of self-driving vehicles: estimating travel behavior implications via a naturalistic experiment

While research on developing and testing automated vehicle (AVs) technologies is well underway, research on their implications on travel-related behavior is in its infancy The aim of this paper is to summarize and analyze literature that focuses on travel-related behavior impacts of AVs, namely levels 4 and 5, as well as highlight important directions of research We review five methods used to quantitatively investigate these implications and how each method contributes to this literature: 1) controlled testbeds, 2) driving simulators and virtual reality, 3) agent-based and travel-demand models, 4) surveys, and 5) field experiments We also present five critical research questions regarding the implications of AVs on the demand side of transportation and summarize findings from the current literature on: 1) what is the willingness to adopt the technology? and what are the impacts of the technology on 2) in-vehicle behavior? 3) value of time? 4) travel-related behaviors (activity pattern, mode, destination, residential location)? and 5) vehicle miles traveled (VMT)? Results can be divided into four categories The first category corresponds to results on research questions with numerous data points where the direction of the impact is consistent across the literature, albeit the magnitude varies considerably For instance, surveys indicate 19% to 68% of people are unwilling to adopt AV technology, a sentiment that is fading over time Moreover, people prefer owning AVs over sharing them and don’t believe their car ownership will decrease Regarding VMT, most studies predict an increase that varies from a low of 1% to a high of 90% depending on the scenario and assumptions under study The second category of findings corresponds to research questions with limited and consistent, albeit highly variable data points For example, a few stated preference survey studies indicate that reduced stress and multitasking during travel will reduce the value of time between 5% and 90% The third category of results is on research questions with a few but conflicting data points For instance, surveys indicate that people (80% to 85%) do not believe their residential location will be impacted by the adoption of AVs Some simulation studies, however, indicate that lower travel costs will drive people away from cities and into suburbs while other studies report the opposite The final category of results corresponds to research question with a single or no data points For instance, one study explores how users will use vehicles to run errands while no studies investigate user preferences for vehicle types (eg mobile-homes vs right-sized) or how they plan to use their vehicles when they are not needed (eg rent out vs leave them idle) Moving forward, the goal is to shift all results into the first category while simultaneously tightening the prediction interval of the magnitude of the impacts This can be achieved by: 1) focusing more efforts on research questions that fall under the three remaining categories to fill the holes in the literature, and 2) establishing consistency and clarity of assumptions used by researchers to enable comparisons and transferability of results

What do we (Not) know about our future with automated vehicles

Projecting Travelers into a World of Self-Driving Vehicles: Estimating Travel Behavior Implications via a Naturalistic Experiment

To explore potential travel behavior shifts induced by personally owned, fully autonomous vehicles (AVs), we ran an experiment that provided personal chauffeurs to 43 households in the Sacramento r...

Glimpse of the Future: Simulating Life with Personally Owned Autonomous Vehicles and Their Implications on Travel Behaviors:

Author(s): Taylor, Margaret; Fujita, K; Zhang, Jinjjing; Harb, Mustapha; Tamerius, James; Jones, Michelle; Jones, Michelle; Price, Sarah

/pdf/explaining-jurisdictional-compliance-with-california-s-top-2k83e5rmj5.pdf

Mustapha Harb

Papers

Projecting travelers into a world of self-driving vehicles: estimating travel behavior implications via a naturalistic experiment

What do we (Not) know about our future with automated vehicles

Projecting Travelers into a World of Self-Driving Vehicles: Estimating Travel Behavior Implications via a Naturalistic Experiment

Glimpse of the Future: Simulating Life with Personally Owned Autonomous Vehicles and Their Implications on Travel Behaviors:

Explaining jurisdictional compliance with California’s top-down streamlined solar permitting law (AB 2188)