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

E-bikes in the Mainstream: Reviewing a Decade of Research

Introduction matters: Manipulating trust in automation and reliance in automated driving.

Swedish national road and transport research institute

The use of mobile phones while driving—one of the most common driver distractions—has been a significant research interest during the most recent decade. While there has been a considerable amount research and excellent reviews on how mobile phone distractions influence various aspects of driving performance, the mechanisms by which the interactions with mobile phone affect driver performance is relatively unexamined. As such, the aim of this study is to examine the mechanisms involved with mobile phone distractions such as conversing, texting, and reading and the driving task, and subsequent outcomes. A novel human-machine framework is proposed to isolate the components and various interactions associated with mobile phone distracted driving. The proposed framework specifies the impacts of mobile phone distraction as an inter-related system of outcomes such as speed selection, lane deviations and crashes; human-car controls such as steering control and brake pedal use and human-environment interactions such as visual scanning and navigation. Eleven literature-review/meta-analyses papers and 62 recent research articles from 2005 to 2015 are critically reviewed and synthesised following a systematic classification scheme derived from the human-machine system framework. The analysis shows that while many studies have attempted to measure system outcomes or driving performance, research on how drivers interactively manage in-vehicle secondary tasks and adapt their driving behaviour while distracted is scant. A systematic approach may bolster efforts to examine comprehensively the performance of distracted drivers and their impact over the transportation system by considering all system components and interactions of drivers with mobile phones and vehicles. The proposed human-machine framework not only contributes to the literature on mobile phone distraction and safety, but also assists in identifying the research needs and promising strategies for mitigating mobile phone-related safety issues. Technology based countermeasures that can provide real-time feedback or alerts to drivers based on eye/head movements in conjunction with vehicle dynamics should be an important research direction.

/pdf/understanding-the-impacts-of-mobile-phone-distraction-on-50a5uv8wuo.pdf

Understanding the impacts of mobile phone distraction on driving performance: A systematic review

The German Naturalistic Cycling Study - comparing cycling speed of riders of different e-bikes and conventional bicycles

To harness the potential of advanced driver assistance systems, drivers must learn how to use them in a safe and appropriate manner. The present study investigates the learning process, as well as the development of trust, acceptance and the mental model for interacting with adaptive cruise control (ACC). Research questions aim to model the learning process in mathematical/statistical terms, examine moments and conditions when these processes stabilize, and assess how experience changes the mental model of the system. A sample of fifteen drivers without ACC experience drove a test vehicle with ACC ten consecutive times on the same route within a 2-month period. All participants were fully trained in ACC functionality by reading the owner’s manual in the beginning. Results show that learning, as well as the development of acceptance and trust in ACC follows the power law of learning. All processes stabilize at a relatively high level after the fifth session, which corresponds to 185 km or 3.5 h of driving. No decline is observable with ongoing system experience. However, limitations that are not experienced tend to disappear from the mental model if they are not activated by experience. Therefore, it is recommended that users be periodically reminded of system limitations (e.g. by intelligent tutoring systems) to make sure that corresponding knowledge nodes are activated.

Learning and development of trust, acceptance and the mental model of ACC. A longitudinal on-road study

On the relationship between pedestrian gap acceptance and time to arrival estimates

The COVID-19 pandemic and the measures taken to combat it led to severe constraints for various areas of life, including mobility. To study the effects of this disruptive situation on the mobility behaviour of entire subgroups, and how they shape their mobility in reaction to the special circumstances, can help to better understand, how people react to external changes. Aim of the study presented in this article was to investigate to what extent, how and in what areas mobility behaviour has changed during the outbreak of SARS-CoV-2 in Germany. In addition, a focus was put on the comparison of federal states with and without lockdown in order to investigate a possible contribution of this measure to changes in mobility. We asked respondents via an online survey about their trip purposes and trip frequency, their choice of transport mode and the reasons for choosing it in the context of the COVID-19 crisis. For the analyses presented in this paper, we used the data of 4157survey participants (2512 without lockdown, 1645 with lockdown). The data confirmed a profound impact on the mobility behaviour with a shift away from public transport and increases in car usage, walking and cycling. Comparisons of federal states with and without lockdown revealed only isolated differences. It seems that, even if the lockdown had some minor effects, its role in the observed behavioural changes was minimal.

/pdf/impact-of-sars-cov-2-on-the-mobility-behaviour-in-germany-3oun2aqii2.pdf

Impact of SARS-CoV-2 on the mobility behaviour in Germany

The prevalence of electric bicycles (e-bikes) has increased considerably in the past few years. Because of their potential to reach higher speeds than conventional bicycles, concerns have been raised about a possible increase in traffic conflicts and crashes. The goal of this study was to examine if there are differences between conventional cyclists and e-bike riders with regard to the probability to be involved in a traffic conflict. In addition, the circumstances under which conflicts occur were investigated to identify potential differences in risk dependent on contextual factors. Utilising the naturalistic cycling approach, the personal bicycles of 80 participants (31 conventional cyclists and 49 e-bike riders) were equipped with a data acquisition system that included two cameras and a speed sensor. Four weeks of “normal” cycling were recorded for each participant. The analysis showed no difference between bicycles and e-bikes with regard to their overall involvement in traffic conflicts, as well as for the role of most contextual factors. One notable exception were intersections, where the risk of being involved in a conflict was twice as high for e-bikes as for conventional bicycles. The speed immediately preceding a conflict was higher for riders of e-bikes compared to conventional bicycles, a pattern that was also found for mean speed. While the general safety concerns regarding e-bikes could not be confirmed, the finding that e-bike riders are somewhat more at risk around intersections shows that under specific circumstances, other road users might still need time to adapt to this relatively new type of vehicle.

Tibor Petzoldt

Papers

The German Naturalistic Cycling Study - comparing cycling speed of riders of different e-bikes and conventional bicycles

Learning and development of trust, acceptance and the mental model of ACC. A longitudinal on-road study

On the relationship between pedestrian gap acceptance and time to arrival estimates

Impact of SARS-CoV-2 on the mobility behaviour in Germany

Traffic conflicts and their contextual factors when riding conventional vs. electric bicycles