Effects of different non-driving-related-task display modes on drivers’ eye-movement patterns during take-over in an automated vehicle

Highly automated vehicles relieve drivers from driving tasks, allowing them to engage in non-driving-related-tasks (NDRTs). However, drivers are required to take over control in certain circumstances due to the limitations of highly automated vehicles. This study focused on drivers’ eye-movement patterns during take-overs when an NDRT (watching videos) was presented via a head-up-display (HUD) and a mobile device display (MDD), compared to no NDRT as the baseline. The experiment was conducted in a high-fidelity driving simulator with real-world driving videos scenarios. Forty-six participants took part in the experiment by completing three drives in three counterbalanced conditions (HUD, MDD and baseline). A take-over-request was issued towards the end of automated driving requesting drivers to stop the NDRT and take over control. Eye-movement data including pupil diameter, blinks, glance duration and number of AOI (Area of Interest) were collected and analysed. The results show that during automated driving, drivers were more engaged in the MDD NDRT with smaller pupil diameter and shorter glance duration on the front scenario compared to the HUD and baseline modes. The number of AOI was reduced during automated driving in both MDD and HUD modes. The take-over-request redirected drivers’ visual attention back to the driving task from NDRT by increasing drivers’ pupil diameter, glance duration and number of AOI. However, the effect of MDD NDRT on pupil diameter and glance duration continued even after the take-over-request when the NDRT was terminated. The study demonstrated HUD is a better display to help maintain drivers’ attention on the road.     

Situational influencing factors on understanding cooperative actions in automated driving

Cooperative interacting vehicles are a promising approach in the context of automated driving. To ensure understanding and acceptance of such systems, the underlying mechanisms of human cooperation in the context of traffic must be understood. In a driving simulator study, we investigated how situational factors influence cooperative behaviour in a lane change situation on a two-lane German highway during automated driving in the left lane. When another car in the right lane was approaching a slower truck, participants (N = 32) were asked by an automated system to either accelerate, decelerate or maintain speed. The driver’s scope of action, the situation’s criticality for the lane-changing vehicle and the display of intention to change lanes were manipulated. A hierarchical multinomial logistic regression revealed that a wider scope of action, a higher situation’s criticality and signalling the intention to change lanes positively influenced cooperative behaviour by accelerating and decelerating. These results might be applied to design user-centred automated cooperatively interacting vehicles.     

Public acceptance of semi-automated truck platoon driving. A comparison between Germany and California

Platooning technology aims at achieving fuel savings by reducing the distance between two or more electronically coupled vehicles. This technology has recently been tested on public highways with heavy trucks in Germany and California. The objective of this study is to assess the level of acceptance among other road users as well as influencing factors of acceptance. An online questionnaire was administered in Germany and California with a total of N = 536 participants. They received information about truck platoon driving (level-1 and level-2 automation) and answered questions about their attitudes towards the technology as well as their behavioral intention to cooperate with the truck platoons. The overall results showed that 70% of respondents indicated acceptance towards the technology, with acceptance rates being significantly higher in California than in Germany. German respondents were more willing to drive into the gap of platoon vehicles and preferred larger platooning gaps. An adaption of the Technology Acceptance Model (TAM) showed that the expected usefulness, and the expected ease of sharing the highway, were the strongest predictors for the behavioral intention to cooperate with platoon vehicles. However, the intention to cut in between platoon vehicles could not be predicted by these variables. Cut-in vehicles are a potential safety risk and decrease the efficiency of platoon driving. Therefore, future research should focus on finding behavioral countermeasures.     

Driver behaviour and traffic accident involvement among professional urban bus drivers in China

The present research aimed to investigate specific behaviors of professional urban bus drivers in China with the revised Driver Behavior Questionnaire (DBQ), and to define the relationships among various driving behaviors (errors, positives, inattention errors, violations), background information (age, years of driving experience, mobility, etc.), self-assessment, and traffic accident. To achieve such goals, the present research designed a four-dimensional DBQ with 20 items for professional urban bus drivers in China. The KMO coefficient of the whole scale was 0.835, and Bartlett’s test was statistically significant (p < 0.000), which demonstrated strong validity of the scale and should be suitable for factor analysis. The four loading factors accounted for 58.991%. In addition, the reliability and effectiveness of the present 20-item scales were measured. The coefficient of internal consistency-Cronbach’s alpha coefficient was 0.881 and the Cronbach’s Alpha Based on Standardized Items was 0.911. This showed that driving behavior scale of professional bus drivers in China was of high reliability and validity. The analysis showed that among the four factors, positive driving behaviors were significantly associated with errors, inattention errors and violations, respectively. Errors, inattention errors and violations correlated positively with each other. This verified that the correlation coefficient of each factor was medium and high, which indicated that the scale had good difference validity. The test content of the total scale was also highly consistent with the test content of each factor, which indicated that the revised scale had good standard related validity. According to the accident prediction model, the variables that significantly affected the occurrence of traffic accidents were daily driving time, positive driving behavior, SE2 (Driving safety), SE3 (Aberrant driver behaviors). The results showed that professional bus drivers often working overtime were most likely to have accidents. The probability of traffic accidents decreased by 53% for every unit of positive driving behavior frequency of professional bus drivers. The more they felt that they had the tendency of aberrant driving behavior, the more likely they were to have traffic accidents. To summary, the present research contributed to validating and improving the DBQ for professional urban drivers in China.     

The effect of visual HMIs of a system assisting manual drivers in manoeuvre coordination in system limit and system failure situations

Ambiguous situations in traffic often require communication and cooperation between road users. In order to resolve these situations and increase cooperative driving behavior in situations of merging or turning left, manual drivers could be assisted by an advanced driver assistance system (ADAS) for cooperative driving. This simulator study investigated the behavior of drivers confronted with system limits and failures of such a system. The ADAS used in this study informed the driver about an upcoming cooperation situation and gave advice on how to behave (e.g. reduce speed, change lane). Two test situations were implemented: a system freeze and an unexpected event, which could not be detected by the system. In order to find the most fitting HMI solution, the place of presentation (head-up display (HUD) vs. instrument cluster) as well as the form of presentation (dynamic vs. symbolic) were varied. The results indicated that the most fitting HMI solution to support the driver in a complex coordinated driving situation is a dynamic HUD, mainly due to the positive effect on glance behavior. However, advantages of both forms of presentation were revealed, as each form of presentation increased the probability of recognition for one of the test situations. The fewest collisions took place with the dynamic form of presentation.     

Autonomous buses: Intentions to use,passenger experiences,and suggestions for improvement

Research on the use of autonomous vehicles as a mode of public transport in a city context is lacking. This paper focuses on the use of recently established autonomous buses (self-driving electric shuttle buses) running along a regular public transport line in a residential area of Oslo, Norway. We use a mixed-methods approach based on survey and interview data from two independent studies. The paper examines intentions to use autonomous buses before and after these were introduced in the case area as well as how passengers experience traveling by autonomous bus. Results show that the intention to use the autonomous buses was mostly positive both before and after using them. Most users felt safe while traveling by autonomous bus. Two suggestions for improvement made by the users were to: increase the speed and reduce the abrupt breaking of the autonomous buses. Overall, outcomes from this paper suggest that residents would be willing to use autonomous buses if these offer more frequent bus departures than the existing ones. However, as full automation has not been achieved yet and there is a host on board who can control the vehicle if necessary, passenger experiences and intentions to use should be reassessed with fully automated buses in future studies.     

Car-following behavioural adaptation when driving next to automated vehicles on a dedicated lane on motorways: A driving simulator study in the Netherlands

Automated vehicles (AVs) are expected to improve traffic flow efficiency and safety. The deployment of AVs on motorways is expected to be the first step in their implementation. One of the main concerns is how human drivers will interact with AVs. Dedicating specific lanes to AVs have been suggested as a possible solution. However, there is still a lack of evidence-based research on the consequence of dedicated lanes for AVs on human drivers’ behavior. To bridge this research gap, a driving simulator experiment was conducted to investigate the behavior of human drivers exposed to different road design configurations of dedicated lanes on motorways. The experiment sample consisted of 34 (13 female) licensed drivers in the age range of 20–30. A repeated measures ANOVA was applied, which revealed that the type of separation between the dedicated lane and the other lanes has a significant influence on the behavior of human drivers driving in the proximity of AV platoons. Human drivers maintained a significantly lower time headway (THW) when driving in the proximity of a continuous access dedicated lane as compared to a limited-access dedicated lane with a guardrail separation for AV platoons. A similar result was found for the limited-access dedicated lane in comparison to the limited-access dedicated lane with guardrail separation. Moreover, the results regarding the empirical relationships between THW and sociodemographic variables indicate a significant THW difference between males and females as well as a significant inverse relationship between THW and the years of driving experience.     

Modeling dispositional and initial learned trust in automated vehicles with predictability and explainability

Technological advances in the automotive industry are bringing automated driving closer to road use. However, one of the most important factors affecting public acceptance of automated vehicles (AVs) is the public’s trust in AVs. Many factors can influence people’s trust, including perception of risks and benefits, feelings, and knowledge of AVs. This study aims to use these factors to predict people’s dispositional and initial learned trust in AVs using a survey study conducted with 1175 participants. For each participant, 23 features were extracted from the survey questions to capture his/her knowledge, perception, experience, behavioral assessment, and feelings about AVs. These features were then used as input to train an eXtreme Gradient Boosting (XGBoost) model to predict trust in AVs. With the help of SHapley Additive exPlanations (SHAP), we were able to interpret the trust predictions of XGBoost to further improve the explainability of the XGBoost model. Compared to traditional regression models and black-box machine learning models, our findings show that this approach was powerful in providing a high level of explainability and predictability of trust in AVs, simultaneously.     

Competence,equipment and behavioural adaptation on Norwegian winter roads: A comparison of foreign and Norwegian HGV drivers

There seems to be a widespread view that foreign lorry drivers’ lack of competence on Norwegian roads, especially related to winter driving, is a significant safety problem. It has, however, been suggested that foreign heavy goods vehicle (HGV) drivers perform better than expected on Norwegian winter roads, as they feel less safe than Norwegian drivers, and adapt by driving slower and more carefully. The aim of the present paper is twofold. First, we examine whether foreign HGV drivers in Norway actually have poorer competence on, training for, experience with and equipment for winter driving than Norwegian HGV drivers. Second, we discuss whether the expected negative effect of these safety challenges is mitigated, as foreign HGV drivers adapt their behaviours. We use four data sources to shed light on the aims: (1) interviews, (2) roadside inspections, (3) small-scale survey and (4) towing incidents. Our data support the hypothesis about behavioural adaptation, indicating that foreign HGV drivers experience winter driving as more difficult or unsafe, as they have supposedly less suitable vehicles and equipment, less experience, training and competence for winter driving. They are therefore more likely to get stuck while driving uphill on winter roads, supposedly as they drive more carefully and slower than Norwegian HGV drivers. Norwegian HGV drivers feel safer and more confident while driving on winter roads, because of their equipment and their experience.     

Drink driving during the COVID-19 pandemic

Due to the COVID-19 pandemic, static roadside random breath testing (RBT) was temporarily suspended between 16 March and 12 June 2020 in Queensland, Australia. In addition to restrictions on travel and social interactions, this provided a unique opportunity to examine changes in drink-driving behaviour during and after a reduction in RBT operations in the community. Three cross-sectional surveys were disseminated at different time points to examine these differences. Over three surveys, 1193 Queensland licensed drivers aged 18 years and over (M = 36.9, SD = 16.7) responded. While overall drink driving decreased over the three survey periods, there were groups where drink driving, or the intention to drink drive, increased over the same period. The overall decrease could be expected as a result of community restrictions on socialising and travel behaviours. In each of the surveys, prior engagement in drink driving was the strongest predictor of intention to increase future engagement and actual engagement. These drink drivers were more likely aged 18–24 years, male, and held restricted licensure. Notably, a small number of participants who reported drink driving, and/or intention to drink drive during the survey period, reported not having engaged in this behaviour previously. This suggested an increased likelihood of drink drivers experiencing punishment avoidance which may promote future engagement in this behaviour. Despite a decrease in social opportunities to drink, and the suspension of highly visible roadside breath testing sites, drink driving persisted. This research highlights the importance of RBTs as a general deterrent for drink driving.