On-road trust and perceived risk in Level 2 automation

To encourage appropriate use of driving automation, we need to understand and monitor driver’s trust and risk perception. We examined (1) how trust and perceived risk are affected by automation, driving conditions and experience and (2) how well perceived risk can be inferred from behaviour and physiology at three levels: over traffic conditions, aggregated risk events, and individual risk events.30 users with and without automation experience drove a Toyota Corolla with driving support. Safety attitude, subjective ratings, behaviour and physiology were examined.Driving support encouraged a positive safety attitude and active driver involvement. It reduced latent hazards while maintaining saliently perceived risks. Drivers frequently overruled lane centring (3.1 times/minute) and kept their feet on or above the pedals using ACC (65.8% of time). They comfortably used support on curvy motorways and monotonic and congested highways but less in unstable traffic and on roundabouts. They trusted the automation 65.4%, perceived 36.0% risk, acknowledged the need to monitor and would not engage in more secondary tasks than during manual driving.Trust-in situation reduced 2.0% when using automation. It was 8.2% higher than trust-in-automation, presumably due to driver self-confidence. Driving conditions or conflicts between driver and automation did not affect trust-in-automation.At the traffic condition level, physiology showed weak and partially counter-intuitive effects. For aggregated risk events, skin conductance had the clearest response but was discernible from baseline in  < 50%. Pupil dilation and heart rate only increased with strong braking and active lane departure assist. For individual risk events, a CNN classifier could not identify risk events from physiology. We conclude that GSR, heart rate and pupil dilation respond to perceived risk, but lack specificity to monitor it on individual events.     

Active vehicle pitch motion for communication in automated driving

The number of automated vehicles (AVs) is expected to successively increase in the near future. This development has a considerable impact on the informal communication between AVs and pedestrians. Informal communication with the driver will become obsolete during the interaction with AVs. Literature suggests that external human machine interfaces (eHMIs) might substitute the communication between drivers and pedestrians. In the study, we additionally test a recently discussed type of communication in terms of artificial vehicle motion, namely active pitch motion, as an informal communication cue for AVs.N = 54 participants approached AVs in a virtual inner-city traffic environment. We explored the effect of three communication concepts: an artificial vehicle motion, namely active pitch motion, eHMI and the combination of both. Moreover, vehicle types (sports car, limousine, SUV) were varied. A mixed-method approach was applied to investigate the participantś crossing behavior and subjective safety feeling. Furthermore, eye movement parameters were recorded as indicators for mental workload.The results revealed that any communication concept drove beneficial effects on the crossing behavior. The participants crossed the road earlier when an active pitch motion was present, as this was interpreted as a stronger braking. Further, the eHMI and a combination of eHMI and active pitch motion had a positive effect on the crossing behavior. The active pitch motion showed no effect on the subjective safety feeling, while eHMI and the combination enhanced the pedestrianś safety feeling while crossing. The use of communication resulted in less mental workload, as evidenced by eye-tracking parameters. Variations of vehicle types did not result in significant main effects but revealed interactions between parameters. The active pitch motion revealed no learning. In contrast, it took participants several trials for the eHMI and the combination condition to affect their crossing behavior. To sum up, this study indicates that communication between AVs and pedestrians can benefit from the consideration of vehicle motion.     

External communication of automated vehicles in mixed traffic: Addressing the right human interaction partner in multi-agent simulation

The urban traffic system is most likely to change in the next years to a mixed traffic with human drivers, vulnerable road users, and automated vehicles. In the past, the development of external communication approaches for automated vehicles focused on scenarios where an automated vehicle communicates with either a pedestrian or a human driver. However, interactions with more than one traffic partner are more realistic. Therefore, a study with 42 participants was conducted with a multi-agent simulation in which an automated vehicle interacted simultaneously with two participants, a pedestrian and a driver of a manual vehicle. In this study, two main scenarios were investigated in order to evaluate the safety and efficiency of the interactions and to determine whether the human road users feel correctly addressed. In one scenario, the pedestrian had to cross the road in front of the automated and the manual vehicle, which were approaching from different sides. In the other, the manual vehicle had to drive through a bottleneck in front of the oncoming automated vehicle, while the pedestrian had to cross the road after both vehicles passed. The communication approach of the automated vehicle consisted of implicit signals using a speed profile and lateral offset within its lane, and explicit signals using an external human–machine interface. The results of the study show that no collisions were observed in terms of safety and no significant negative effects on efficiency were measured. However, in contrast to single agent interactions, a majority of participants felt wrongly addressed in situations where the automated vehicle signals the right-of-way to the other human road user. It can be concluded that the communication approach of the automated vehicle needs to be modified in order to address certain road users more clearly.     

Effect of multimodal takeover request issued through A-pillar LED light,earcon, speech message,and haptic seat in conditionally automated driving

The driver of a conditionally automated vehicle equivalent to level 3 of the SAE is obligated to accept a takeover request (TOR) issued by the vehicle. Considerable research has been conducted on the TOR, especially in terms of the effectiveness of multimodal methods. Therefore, in this study, the effectiveness of various multimodalities was compared and analyzed. Thirty-six volunteers were recruited to compare the effects of the multimodalities, and vehicle and physiological data were obtained using a driving simulator. Eight combinations of TOR warnings, including those implemented through LED lights on the A-pillar, earcon, speech message, or vibrations in the back support and seat pan, were analyzed to clarify the corresponding effects. When the LED lights were implemented on the A-pillar, the driver reaction was faster (p = 0.022) and steering deviation was larger (p = 0.024) than those in the case in which no LED lights were implemented. The speech message resulted in a larger steering deviation than that in the case of the earcon (p = 0.044). When vibrations were provided through the haptic seat, the reaction time (p < 0.001) was faster, and the steering deviation (p = 0.001) was larger in the presence of vibrations in the haptic seat than no vibration. An interaction effect was noted between the visual and auditory modalities; notably, the earcon resulted in a small steering deviation and skin conductance response amplitude (SCR amplitude) when implemented with LED lights on the A-pillar, whereas the speech message led to a small steering deviation and SCR amplitude without the LED lights. In the design of a multimodal warning to be used to issue a TOR, the effects of each individual modality and corresponding interaction effects must be considered. These effects must be evaluated through application to various takeover situations.     

User acceptance of automated shuttles in Berlin-Schöneberg: A questionnaire study

Automated shuttles are now in a prototyping phase in several research projects. However, there is still a paucity of knowledge on the acceptance of these shuttles. This paper presents the results of a questionnaire study among individuals (n = 384) who physically experienced an automated shuttle on an office campus in Berlin-Schöneberg. The findings indicate that the respondents were positive towards automated shuttles and could envision their use as feeders to public transport systems, in both urban and rural areas. The respondents were less satisfied with the effectiveness of the shuttle compared to their existing form of travel, the speed of the shuttle, and the space for luggage. A principal component analysis resulted in the retention of three components: (1) intention to use, (2) shuttle and service characteristics, and (3) shuttle effectiveness compared to existing transport. Older respondents expressed a higher intention to use, but found the shuttle less effective than their existing travel. We argue that automated shuttles are a valued concept, but speed and efficiency have to improve, in order for automated shuttles to become viable on a wide scale. Future research should use more objective measures and establish long-term effects in larger, more representative samples.     

Auditory localisation of conventional and electric cars: Laboratory results and implications for cycling safety

When driven at low speeds, cars operating in electric mode have been found to be quieter than conventional cars. As a result, the auditory cues which pedestrians and cyclists use to assess the presence, proximity and location oncoming traffic may be reduced, posing a safety hazard. This laboratory study examined auditory localisation of conventional and electric cars including vehicle motion paths relevant for cycling activity. Participants (N = 65) in three age groups (16–18, 30–40 and 65–70 year old) indicated the location and movement direction (approaching versus receding) of cars driven at 15, 30 and 50 km/h in two ambient sound conditions (low and moderate). Results show that low speeds, higher ambient sound level and older age were associated with worse performance on the location and motion direction tasks. In addition, participants were less accurate at determining the location of electric and conventional car sounds emanating from directly behind the participant. Implications for cycling safety and proposals for adding extra artificial noise or warning sounds to quiet (electric) cars are discussed.     

Too individualistic for safety culture? Non-traffic related work safety among heavy goods vehicle drivers

IntroductionThis article reports on a study of non-traffic related work safety among drivers of heavy goods vehicles in Denmark. In the heavy goods vehicle transport (HGV) sector only 6.4% of workplace accidents involving drivers are traffic related. HGV work is characterised by solitary work, as drivers tend to work at a physical distance from their own company and their working environment is also influenced by the working environment of other companies e.g. the places where they deliver goods. This study focuses on an analysis of HGV drivers’ and managers’ differentiated understandings of risk and safety and its management within an organisational context. The situational focus involves viewing HGV drivers’ working environment as a part of the organisational structure as well as of other social relationships. An understanding of safety culture as practice is applied with the view of identifying values and attitudes as well as organisational and technical aspects in relation to how individualist or collectivist understandings of risk and safety influence the working environment in HGVs.MethodThe study applied a mixed methods approach and in this article the qualitative interviews conducted with drivers and managers is the primary data source.ResultsThis study suggests a widespread understanding of drivers as being individually oriented in their work, from drivers and management alike. However, the study also demonstrates that, in conducting their work, the drivers are actually interdependent, and share knowledge frequently, albeit informally. The organisational structure of the company shapes their individual attitudes towards safety but they also report being dependent on relationships with, and information from, their fellow colleagues, former colleagues and friends who shape their understandings and attitudes towards hazards and safety practices. The analysis points to risk-taking and unsafe practices as prevalent among HGV drivers, who often refer to risk as trivial and the management of such risks as one’s own responsibility. Knowledge of how to manage risks in everyday practice is shown to be principally related to personal experiences but also to the good advice and examples of fellow drivers.ConclusionsThe analysis points to interdependent and collectivist practices among HGV drivers even though they are perceived as being individualistically oriented when it comes to safety. Therefore, non-traffic related safety practices, in this case the loading and unloading of vehicles, occur in the grey zone of organisational safety management. Despite the fact that organisational safety initiatives are initiated, the management sees limited possibilities for enforcing them and hence safety practice is often left to the individual driver.Practical applicationsA safety culture perspective might enhance work safety among HGV drivers if we are able to understand workplace culture in a pluralistic way. Collectivist practice among the drivers can be utilised in order to improve knowledge sharing and situational safety practices. The informal communication identified among the drivers might offer a new model for safety initiatives based on more collectivist, albeit informal, safety culture practices on behalf of HGV companies.     

Human factors of transitions in automated driving: A general framework and literature survey

The topic of transitions in automated driving is becoming important now that cars are automated to ever greater extents. This paper proposes a theoretical framework to support and align human factors research on transitions in automated driving. Driving states are defined based on the allocation of primary driving tasks (i.e., lateral control, longitudinal control, and monitoring) between the driver and the automation. A transition in automated driving is defined as the process during which the human-automation system changes from one driving state to another, with transitions of monitoring activity and transitions of control being among the possibilities. Based on ‘Is the transition required?’, ‘Who initiates the transition?’, and ‘Who is in control after the transition?’, we define six types of control transitions between the driver and automation: (1) Optional Driver-Initiated Driver-in-Control, (2) Mandatory Driver-Initiated Driver-in-Control, (3) Optional Driver-Initiated Automation-in-Control, (4) Mandatory Driver-Initiated Automation-in-Control, (5) Automation-Initiated Driver-in-Control, and (6) Automation-Initiated Automation-in-Control. Use cases per transition type are introduced. Finally, we interpret previous experimental studies on transitions using our framework and identify areas for future research. We conclude that our framework of driving states and transitions is an important complement to the levels of automation proposed by transportation agencies, because it describes what the driver and automation are doing, rather than should be doing, at a moment of time.     

A single sensor system for mapping in GNSS-denied environments

Autonomous robotic vehicles need accurate positioning to navigate. For outdoor autonomous vehicles, the localization problem has been solved using GNSS systems. However, many places suffer from problems in the signal of those systems, known as GNSS-denied environments. To face such a problem, several approaches first map the environment to thereafter localize the vehicle within it. The solutions for mapping in GNSS-denied places, mostly, are tested indoors, and the revisited areas are generally close from the starting position. In this work, we develop a single sensor system for mapping in large-scale GNSS-denied sites, based exclusively on a 3D LiDAR system. The proposed work consists of a 3D-LiDAR with a LiDAR Odometry approach (LO) estimating movements between frames thus providing of dead-reckoning estimates of the vehicle. The LiDAR Odometry is the input to a virtual GNSS system based on a Particle Filter Localization which matches the estimated dead-reckoning with a road map, with the assumption that the vehicle usually navigates on roads. The global position produced by the virtual GNSS is used to detect and correct loop closures in case of revisited areas. A GraphSLAM implementation fuses the outcomes from LiDAR Odometry, virtual GNSS and loop closure, and yield a feasible pose of the vehicle. Finally, a mapping procedure places every 3D frame and builds 2D occupancy grid maps. The system developed here is evaluated empirically using two datasets collected in a dynamic environment with paths of 3.7 and 6.5 km long, respectively. For both datasets, the system presents an RMS of 6.5 m according to GNSS sensor readings used for comparison purposes.     

Measuring driving workload of heavy vehicles at roundabouts

Correctly designed roundabouts proved to have positive safety and functional performances. However, they are also affected by peculiar disadvantages. In particular, they are difficult to manoeuvre, especially for heavy vehicle drivers. Despite these concerns, there are currently no driving workload metrics devoted to roundabouts.A novel methodological approach is proposed for trying to quantify workload impinging on heavy vehicle drivers when manoeuvring through complex at-grade intersections. Proper acquisition of input data constitutes the starting point for future research about ascertainment of workload for these particular road scenarios. The described procedure enables recording steering wheel angles performed by a driver when manoeuvring an articulated lorry through a complex at-grade intersection. A field trial was carried out for verifying the practical feasibility of proposed method in capturing driver’s steering behaviour. Dynamic data acquired via global navigation satellite system instrumentation were related to actual driver’s steering wheel behaviour captured by camera frames. As a complement to the experiment, selected steering behaviour metrics were calculated. Steering Entropy attributed a high difficulty level to the manoeuvres performed through the roundabout, whereas High Frequency Component and Steering Reversal Rate showed intensity and occurrences of driver’s corrections needed for controlling position of the semitrailer at the ring. It appears that even a single roundabout may represent an arduous task for drivers. The study concludes with recommendations for further research about workload imposed by roundabouts to heavy vehicle drivers, with special attention to successions of closely spaced roundabouts.