Predicting pedestrians’ intention to cross the road in front of automated vehicles in risky situations

Due to the absence of a human driver, the introduction of fully automated vehicles (FAVs) may bring new safety challenges to the traffic system, especially when FAVs interact with vulnerable road users such as pedestrians. To ensure safer interactions between pedestrians and FAVs, this questionnaire-based study aims to understand Australian pedestrians’ intention to engage in risky road-crossing behaviors when they interact with FAVs vs. human-driven vehicles (HDVs). A 2 × 2 between-subject design was utilized, in which two risky road-crossing scenarios were designed and took into account the vehicle type (FAV vs. HDV) and vehicle speed (30 km/h vs. 50 km/h). A total of 493 participants (aged 18–77) were randomly assigned to one of the four experimental conditions and completed an online questionnaire based on the extended Theory of Planned Behavior (TPB). This questionnaire measured pedestrians’ intentions to cross the road in the assigned scenarios as well as the motivational factors behind these intentions in terms of attitude, subjective norm, perceived behavioral control, perceived risk and trust in the vehicle. The results show that pedestrians had significantly higher intentions to cross the road in front of approaching FAVs than HDVs. Participants also reported a lower risk perception of crossing in front of FAVs and greater trust in this type of vehicle. Attitude, subjective norm, and perceived behavioral control were significant predictors of intentions to engage in risky road-crossing behavior. Findings of this study provide important implications for the development and implementation of FAVs in the future road transport system.     

Teenage bicyclists' perceptions toward automated vehicles and their associated traffic infrastructure: A focus group discussion

Automated vehicles (AVs) can improve traffic safety for vulnerable road-users like bicyclists. It is most likely that current young people will be the ones to use these vehicles and interact with them. However, very few studies have focused on bicyclist-AV interaction, with little to no inclusion of teenage bicyclists. This research used a virtual focus group study with 25 teenage bicyclists in six groups. Participants were presented with potential designs of infrastructures and communicating interfaces, they discussed pros and cons for each design, and answered multiple surveys. Overall, teenage bicyclists showed positive perceptions toward AVs. They preferred spacious lanes for bicyclists and physical barriers separating AVs and bicyclists. Teenagers chose visual interfaces with familiar icons; nevertheless, they recommended both visual and audible interfaces to ensure bicyclists’ attention and address the need of visually and audibly impaired populations. Future researchers and stakeholders will be benefited from the methodology and outcomes of this research.     

Effects of mode distinction,user visibility,and vehicle appearance on mode confusion when interacting with highly automated vehicles

Automated vehicles are expected to communicate with pedestrians at least during the introductory phase, for example, via LED strips, displays, or loudspeakers. While these are added to minimize confusion and increase trust, the human passenger within the vehicle could perform motions that a pedestrian could misinterpret as opposing the vehicle’s communication. To evaluate potential solutions to this problem, we conducted an online video-based within-subjects experiment (N = 59). The solutions under evaluation were mode distinction, vehicle appearance, and the visibility of the passenger via a tintable windshield. Our results show that especially the mode distinction and the conspicuous sensor attached to the automated vehicle showed positive effects. A tintable windshield, however, was negatively assessed. Thus, our work helps to design eHMI concepts to introduce automated vehicles safely by informing about feasible methods to avoid mode confusion.     

Experiences of older adults interacting with a shared autonomous vehicle and recommendations for future implementation

IntroductionA recognised potential benefit of autonomous vehicles is increased mobility for older adults. However, this group is more apprehensive about adoption, which may hinder uptake. Shared autonomous vehicles (SAVs) represent a use case that may be especially relevant for older people due to emerging applications in retirement villages and similar precincts. However, little research has examined the SAV-related concerns of older adults and strategies to address them. This study used an exploratory approach involving SAV exposure to identify strategies that may increase older people’s receptiveness to SAVs.MethodOlder adults living in retirement villages (n = 63) were interviewed while interacting with an SAV to examine their needs, expectations, and concerns regarding SAVs. The interview data were coded and thematically analysed.ResultsParticipants recommended the following approaches to ensuring SAVs are useful and acceptable to older adults: providing physical accessibility for those with mobility impairments, comfortable and practical internal layouts, and operating SAVs on convenient routes at useful speeds. Strategies such as exposing older adults to SAVs in operation to encourage uptake and initially ensuring a human assistant is present were suggested methods of increasing receptivity.DiscussionThe findings suggest older passengers are likely to share many of the same reactions to SAVs as the broader population, but with a stronger focus on issues relating to accessibility and the physical layout of the vehicles. The solutions to these issues suggested by the study participants may be useful for those designing SAVs for use in older people’s settings and beyond.     

Investigating driver reactions to movements of autonomous vehicle in permitted right turn through driving simulator experiments

Traffic safety has always been a hot topic for human-driven (HDV) and autonomous vehicles (AV) mixed flow. The conflict between permitted right-turn vehicles (PRT) and opposing through vehicles (TH) at signalized intersections (left-handed traffic) is extraordinarily critical. AVs with aggressive behaviors are able to accept short gap time without losing safety. However, such a turning maneuver may lead to dangerous feelings and cause unexpected reactions of approaching drivers. This study aims to investigate and model drivers’ reactions in TH movements to PRT AVs considering the trust degree of drivers to AVs. Questionnaire surveys and driving simulator experiments were conducted for 41 participants. Results reveal that the right turn timing of PRT AV will significantly influence drivers’ reactions. Basically, TH drivers will brake with a high probability under the situation of small expected post encroachment time (PET). It is also found that female drivers and drivers with low trust in AVs are more vigilant to PRT AVs than other drivers. Based on this finding a two-layer model for reproducing TH drivers’ reactions to PRT AVs is proposed. The first layer is to determine the braking decision and the second layer is to calculate the parameters of braking behaviors (brake lag, braking time, and speed drop). The significance and coefficients variables in these models proved that the trust in AV will influence drivers’ decisions and braking behaviors (brake lag and braking time). The more the drivers trust AVs, the smaller the expected PET to AVs they can accept for passing without braking, and the more gently they will brake (longer brake lag and shorter braking time) due to the cutting in of PRT AVs. This effect will become significant after drivers have experienced several interactions with AVs.     

Understanding charging behaviour of electric vehicle users

We examined the psychological dynamics underlying charging behaviour of electric vehicle (EV) users. Data from 79 EV users were assessed in a 6-month EV field study. On average, users charged their EV three times per week, drove 38 km per day, and they typically had a large surplus of energy remaining upon recharging. Based on first findings concerning charging style among mobile phone users, we hypothesized that user–battery interaction style (UBIS) is a relevant variable for understanding charging behaviour of EV users. We developed measures to assess UBIS. Results show that it is a relatively temporally stable characteristic which also shows some cross-device consistency. As predicted by our conceptual model, UBIS and comfortable range explain the charge level at which people typically recharged. UBIS was related to users’ confidence in their mental model of range dynamics, the utilization of range, and to excess energy from renewable sources. This research has implications for optimizing sustainability of electric mobility systems.     

An electroencephalographic examination of the autonomous sensory meridian response (ASMR)

Autonomous sensory meridian response (ASMR) is a perceptual phenomenon characterized by pleasurable tingling sensations in the head and neck, as well as pleasurable feelings of relaxation, that reliably arise while attending to a specific triggering stimulus (e.g., whispering or tapping sounds). Currently, little is known about the neutral substrates underlying these experiences. In this study, 14 participants who experience ASMR, along with 14 control participants, were presented with four video stimuli and four auditory stimuli. Half of these stimuli were designed to elicit ASMR and half were non-ASMR control stimuli. Brain activity was measured using a 32-channel EEG system. The results indicated that ASMR stimuli—particularly auditory stimuli—elicited increased alpha wave activity in participants with self-reported ASMR, but not in matched control participants. Similar increases were also observed in frequency bands associated with movement (gamma waves and sensorimotor rhythm). These results are consistent with the reported phenomenology of ASMR, which involves both attentional and sensorimotor characteristics.     

Value congruence and teachers’ work engagement: The mediating role of autonomous and controlled motivation

This study aimed to examine the importance of value congruence in work engagement and to extend the previous literature by investigating the potential mediating effects of autonomous and controlled motivation in this relationship. The Perceived Value Congruence, Autonomous and Controlled Motivation and Work Engagement scales were administered to 767 teachers in Mainland China. Correlation analysis revealed that value congruence, autonomous and controlled motivation and work engagement were significantly correlated with each other. Furthermore, structural equation modeling (SEM) analysis showed that value congruence exerted its indirect effect on teacher’s work engagement through the mediating effect of autonomous and controlled motivation. These findings provide a new perspective to explain the complex association between value congruence and work engagement. The possible explanations and the research limitations are discussed.     

A hybrid POMDP-BDI agent architecture with online stochastic planning and plan caching

This article presents an agent architecture for controlling an autonomous agent in stochastic, noisy environments. The architecture combines the partially observable Markov decision process (POMDP) model with the belief-desire-intention (BDI) framework. The Hybrid POMDP-BDI agent architecture takes the best features from the two approaches, that is, the online generation of reward-maximizing courses of action from POMDP theory, and sophisticated multiple goal management from BDI theory. We introduce the advances made since the introduction of the basic architecture, including (i) the ability to pursue and manage multiple goals simultaneously and (ii) a plan library for storing pre-written plans and for storing recently generated plans for future reuse. A version of the architecture is implemented and is evaluated in a simulated environment. The results of the experiments show that the improved hybrid architecture outperforms the standard POMDP architecture and the previous basic hybrid architecture for both processing speed and effectiveness of the agent in reaching its goals.     

LARES: An AI-based teleassistance system for emergency home monitoring

The latest progresses in medicine are helping people live longer and better. An ageing population is a sign of a developed society with an advanced health care system. Improved life expectancy should be welcomed as a major achievement, but it should not cause a financial or social burden. In this scenario, it is critical to support older and handicap adults to continue living independently and retaining their current lifestyle. New technological advances in Wireless Sensors Networks (WSN) and Artificial Intelligence (AI) can facilitate this task.In this direction we present lares, an AI-based system that integrates a (i) WSN for receiving information of the environment and the dependent person, (ii) an autonomous robot able to take decisions based on the received information, and (iii) a Web-based system to provide telecare assistance. lares has been tried in two dependent elderly home environments during several weeks, and the experiments show that is able to detect anomalies and generate alarms in abnormal situations.