Modeling Cross-National Differences in Automated Vehicle Acceptance

Robots at your doorstep: acceptance of near-future technologies for automated parcel delivery

The logistics and delivery industry is undergoing a technology-driven transformation, with robotics, drones, and autonomous vehicles expected to play a key role in meeting the growing challenges of last-mile delivery. To understand the public acceptability of automated parcel delivery options, this U.S. study explores customer preferences for four innovations: autonomous vehicles, aerial drones, sidewalk robots, and bipedal robots. We use an Integrated Nested Choice and Correlated Latent Variable (INCLV) model to reveal substitution effects among automated delivery modes in a sample of U.S. respondents. The study finds that acceptance of automated delivery modes is strongly tied to shipment price and time, underscoring the importance of careful planning and incentives to maximize the trialability of innovative logistics options. Older individuals and those with concerns about package handling exhibit a lower preference for automated modes, while individuals with higher education and technology affinity exhibit greater acceptance. These findings provide valuable insights for logistics companies and retailers looking to introduce automation technologies in their last-mile delivery operations, emphasizing the need to tailor marketing and communication strategies to meet customer preferences. Additionally, providing information about appropriate package handling by automated technologies may alleviate concerns and increase the acceptance of these modes among all customer groups.

The preference of onboard activities in a new age of automated driving

According to the economic theory assumption, travelers tend to monetize travel time based on factors related to their individual and trip characteristics. In the literature, a limited number of studies evaluating onboard activities on traveler's utility in the presence of the autonomous vehicle (AV) are found. In the current research, traveler preferences on board of three transport modes: individual-ride autonomous vehicle (IR-AV), shared-ride autonomous vehicle (SAV), and public transport (PT) are studied. The focus of this paper is the examination of travelers in urban areas, where traveling is relatively short, and the study of the travelers' main trip purposes. The impact of travel time, travel cost, and main onboard activity is estimated based on a discrete choice experiment (DCE). The in-vehicle onboard activities are divided into six onboard activities, where active and passive activities are considered. An experimental design and a stated preference (SP) survey are carried out. The result of the SP survey is analyzed, where a Mixed Logit (ML) model, which includes various explanatory variables, is applied. The developed model contains such variables as trip time, trip cost, main onboard activity, frequent transport mode, job, age, and car ownership. These variables show various effects on the probability of choosing a transport mode. The impact of change in travel time, travel cost, and each of the six onboard activities on traveler preferences is highlighted. As a result, variations on the impact of time, cost, and onboard activities are demonstrated. Furthermore, it is presented that people prefer using IR-AV over SAV and PT, while the probability of choosing SAV is the lowest. Besides, reading and using social media affect the utility of travelers positively (i.e., higher probability) to a greater extent than other activities, while writing alone demonstrates negative utility.

Evaluating highway designs considering uncertain mobility patterns and flexibility using real options

Determining how infrastructure corridors are to be optimally designed and modified over time is challenging due to the considerable uncertainty associated with potential changes in mobility patterns. This is because of factors such as the dynamisms of urban areas and the potential of transitioning to autonomous vehicles. Although currently this future uncertainty is taken into consideration in decisions with respect to highway designs and modifications in a qualitative manner, there is potential benefit to using quantitative methods and explicitly considering how highways may be modified in the future as a function of the actual future that emerges. In this article, the use of a quantitative evaluation method using real options is explored to evaluate highway designs, considering uncertainties in future mobility patterns and management flexibility. The usefulness of the method is investigated on the fictive but realistic case study based on the completion of the A15 highway, in the canton of Zürich, Switzerland. The results of this exploratory work indicate significant value in the use of the proposed method to ensure that infrastructure networks are optimally prepared to support society in an unknown future, and it is expected that it can be used more extensively in future spatial planning.

Application of the Theory of Planned Behavior in Autonomous Vehicle-Pedestrian Interaction

Automobile manufacturers, alongside technology providers, researchers, and public agencies, are conducting extensive testing to design autonomous vehicles (AVs) algorithms that will provide a complete understanding of road users, specifically pedestrians. Pedestrian behavior and actions determination are highly unpredictable depending on behavioral beliefs, context, and socio-demographic variables. Context includes everything that potentially affects one’s behavior; in AVs–pedestrian interaction, context may consist of weather conditions, road structure, social factors norms, and traffic volume. These influencing elements, therefore, need to be focused on during the development of pedestrian interaction algorithms. For this purpose, the pedestrian behavior questionnaire for FAVs (PBQF) is designed based on the theory of planned behavior (TPB). A total of almost 1000 voluntary participants completed this multilingual survey. As socio-demographic values and physiological perception varies with local norms, regions, and ethnicity, participants from 27 countries were therefore chosen to account for this variation. One of the key findings of this study is the influence of pedestrian attributes and the context on pedestrian behavior. Pedestrian action cannot be understood without visual observation of the pedestrian themselves and their context. The findings showed that pedestrians build communication with vehicles based on their driving styles. The vehicle’s driving style leads pedestrians to think that the vehicle is human-driven or autonomous. The results also revealed that pedestrians use several cues to show their intention. The general perception of AVs was also analyzed, and the communication between AVs and pedestrians with different displaying options was investigated.

Premises for the Future Deployment of Automated and Connected Transport in Romania Considering Citizens’ Perceptions and Attitudes towards Automated Vehicles

This paper is an initial exploratory study that provides recommendations for the sustainable development of future automated and connected transport (ACT) systems in Romania. To achieve this, our paper investigates the different factors that influence mobility behaviour related to ACT systems through two different themes. The first part analyses (i) the strategic framework that is relevant to future ACT deployment and (ii) the spatial development patterns of large cities in Romania that might influence future mobility behaviour based on ACT systems. We presumed, and the study confirmed, that there is currently a poor focus on ACT systems in strategic documents and that the current spatial patterns show some premises for unsustainable mobility behaviour based on ACT systems. The second part describes the results of our analysis on the WISE-ACT survey deployed in Romania. We explored how informed Romanian citizens are about AVs; whether they are ready to use them; and what perceptions, concerns, and attitudes might influence their mobility behaviour when using ACT systems. The present analysis mainly shows that the perceptions of Romanian citizens are widely similar to those of citizens from other countries and that, for Romania, the orientation towards unsustainable forms of individual travel is maintained in terms of the future use of AVs. The recommendations that are presented here primarily address the spatial and attitudinal factors that have been identified as prerequisites for unsustainable future mobility behaviour linked to ACT systems.

The Influence of Introducing Autonomous Vehicles on Conventional Transport Modes and Travel Time

Introducing autonomous vehicles (AVs) on the market is likely to bring changes in the mobility of travelers. In this work, extensive research is conducted to study the impact of different levels of automation on the mobility of people, and full driving automation needs further study because it is still under development. The impacts of AVs on travel behavior can be studied by integrating AVs into activity-based models. The contribution of this study is the estimation of AVs’ impacts on travelers’ mobility when different travel demands are provided, and also the estimation of AVs’ impact on the modal share considering the different willingness of pay to travel by AVs. This study analyses the potential impacts of AVs on travel behavior by investigating a sample of 8500 travelers who recorded their daily activity plans in Budapest, Hungary. Three scenarios are derived to study travel behavior and to find the impacts of the AVs on the conventional transport modes. The scenarios include (1) a simulation of the existing condition, (2) a simulation of AVs as a full replacement for conventional transport modes, and (3) a simulation of the AVs with conventional transport modes concerning different marginal utilities of travel time in AVs. The simulations are done by using the Multi-Agent Transport Simulation (MATSim) open-source software, which applies a co-evolutionary optimization algorithm. Using the scenarios in the study, we develop a base model, determine the required fleet size of AVs needed to fulfill the demand of the different groups of travelers, and predict the new modal shares of the transport modes when AVs appear on the market. The results demonstrate that the travelers are exposed to a reduction in travel time once conventional transport modes are replaced by AVs. The impact of the value of travel time (VOT) on the usage of AVs and the modal share is demonstrated. The decrease in the VOT of AVs increases the usage of AVs, and it particularly decreases the usage of cars even more than other transport modes. AVs strongly affect the public transport when the VOT of AVs gets close to the VOT of public transport. Finally, the result shows that 1 AV can replace 7.85 conventional vehicles with acceptable waiting time.

Who Is Willing to Share Their AV? Insights about Gender Differences among Seven Countries

The introduction of shared autonomous vehicles into the transport system is suggested to bring significant impacts on traffic conditions, road safety and emissions, as well as overall reshaping travel behaviour. Compared with a private autonomous vehicle, a shared automated vehicle (SAV) is associated with different willingness-to-adopt and willingness-to-pay characteristics. An important aspect of future SAV adoption is the presence of other passengers in the SAV—often people unknown to the cotravellers. This study presents a cross-country exploration of user preferences and WTP calculations regarding mode choice between a private non-autonomous vehicle, and private and shared autonomous vehicles. To explore user preferences, the study launched a survey in seven European countries, including a stated-preference experiment of user choices. To model and quantify the effect of travel mode attributes and socio-demographic characteristics, the study employs a mixed logit model. The model results were the basis for calculating willingness-to-pay values for all countries and travel modes, and provide insight into the significant heterogeneous, gender-wise effect of cotravellers in the choice to use an SAV. The study results highlight the importance of analysis of the effect of SAV attributes and shared-ride conditions on the future acceptance and adoption rates of such services.

The Role of Human Operators in Safety Perception of AV Deployment—Insights from a Large European Survey

Autonomous vehicles are anticipated to play an important role on future mobility offering encouraging solutions to today’s transport problems. However, concerns of the public, which can affect the AVs’ uptake, are yet to be addressed. This study presents relevant findings of an online survey in eight European countries. First, 1639 responses were collected in Spring 2020 on people’s commute, preferred transport mode, willingness to use AVs and demographic details. Data was analyzed for the entire dataset and for vulnerable road users in particular. Results re-confirm the long-lasting discourse on the importance of safety on the acceptance of AVs. Spearman correlations show that age, gender, education level and number of household members have an impact on how people may be using or allowing their children to use the technology, e.g., with or without the presence of a human supervisor in the vehicle. Results on vulnerable road users show the same trend. The elderly would travel in AVs with the presence of a human supervisor. People with disabilities have the same proclivity, however their reactions were more conservative. Next to safety, reliability, affordability, cost, driving pleasure and household size may also impact the uptake of AVs and shall be considered when designing relevant policies.