Is Drivers' Situation Awareness Influenced by a Fully Automated Driving Scenario?

This paper presents results from a study conducted for the European FP6 project CityMobil. The experiment described here is part of four cross-site experiments designed to study the human factors issues associated with various degrees of automated driving. Thirty-nine drivers were asked to drive a simulated route with two zones in a within-subjects design, with a main factor of automation. Driver behaviour in “manual” driving, where all driving manoeuvres and decisions were made by the drivers, was compared to “highly automated” driving, where lateral and longitudinal control of the driving task was dictated by the “automated system”. In this condition, drivers were asked to take their foot off the pedals and their hands off the steering wheel and allow the vehicle to be driven for them. Situation awareness in both driving environments was measured by computing drivers‟ response time to a series of unexpected/critical traffic events. Results showed that drivers‟ response to these events was significantly later in the highly automated condition, implying both reduced situation awareness and perhaps an excessive trust in the automated system

The validity of a low-cost simulator for the assessment of the effects of in-vehicle information systems

This study explored the validity of using a low-cost simulator for the assessment of driver distraction arising from the use of an in-vehicle information system. Eighteen participants drove on a rural road whilst carrying out distractor tasks of various levels of difficulty, in both a low-cost simulator (with gaming console steering wheel and pedals with single monitor display) and a medium-cost one (fixed-base, complete vehicle cab, wrap-around visuals). The distractor tasks were presented at identical locations in each of the drives and an identical suite of driver performance and subjective rating measures were elicited to allow a robust comparison between the two simulator environments. As expected, there was a reduction in mean speed when drivers were completing the distraction tasks and this effect was observed in both simulators. However, drivers spent more time at shorter headways in the low-cost version and demonstrated more erratic steering behaviour in the low-cost version. This could be due to a reduced peripheral view and inferior kinaesthetic feedback through the driver controls, but low-cost simulators could play a significant role in the early stages of design and evaluation of in-vehicle information systems

The design of haptic gas pedal feedback to support eco-driving

Previous literature suggests that haptic gas pedals can assist the driver in search of maximum fuel economy. This study investigated three haptic pedal designs, each with high and low intensities of feedback, in a rapid prototyping, paired comparison design. Twenty drivers took part, experiencing the systems in a high-fidelity driving simulator. Results suggested that drivers were best guided towards an “idealized” (most fuel efficient) gas pedal position by force feedback (where a driver feels a step change in gas pedal force) as opposed to stiffness feedback (where a driver feels a changing gas pedal firmness). In either case, high levels of force/stiffness feedback were preferred. Objective performance measures mirrored the subjective results. Whilst the short-term nature (brief system exposure) of this study led to difficulties in drawing longer-term conclusions, it would appear that force feedback haptics are better suited than stiffness feedback to augment an effective driver interface supporting “green” driving

Highly Automated Driving, Secondary Task Performance, and Driver State

Objective: a driving simulator study compared the effect of changes in workload on performance in manual and highly automated driving. Changes in driver state were also observed by examining variations in blink patterns. Background: With the addition of a greater number of advanced driver assistance systems in vehicles, the driver’s role is likely to alter in the future from an operator in manual driving to a supervisor of highly automated cars. Understanding the implications of such advancements on drivers and road safety is important. Method: a total of 50 participants were recruited for this study and drove the simulator in both manual and highly automated mode. As well as comparing the effect of adjustments in driving-related workload on performance, the effect of a secondary Twenty Questions Task was also investigated. Results: in the absence of the secondary task, drivers’ response to critical incidents was similar in manual and highly automated driving conditions. The worst performance was observed when drivers were required to regain control of driving in the automated mode while distracted by the secondary task. Blink frequency patterns were more consistent for manual than automated driving but were generally suppressed during conditions of high workload. Conclusion: highly automated driving did not have a deleterious effect on driver performance, when attention was not diverted to the distracting secondary task. Application: as the number of systems implemented in cars increases, an understanding of the implications of such automation on drivers’ situation awareness, workload, and ability to remain engaged with the driving task is important

Designing an in-vehicle eco-driving support system to assist drivers in conserving fuel

Environmentally friendly driving – or eco-driving – refers to the driving of a vehicle in a way that conserves fuel and reduces emissions. Large fuel savings are possible by targeting the role of driver behaviour in the protection of the environment, and teaching them how to ‘eco-drive’. This study forms part of the ecoDriver project, which aims to develop an in-vehicle eco-driving support system. While many current systems offer after-trip feedback on the fuel efficiency of driving or simple in-trip recommendations (e.g. gear shift indicators), this study investigates a number of systems that provide real-time, feed-forward guidance on how to alter accelerator usage in the upcoming moments to minimise fuel consumption. A driving simulator was used to test three potential eco-driving interfaces which used a common eco-driving guidance algorithm. Two systems used a haptic accelerator pedal, while one presented multi-modal visual and auditory information. Objective eco-driving performance was measured as the error between desired accelerator position defined by the system and accelerator position selected by the driver. Subjective feedback on workload and acceptability of the system was analysed and driver visual distraction was monitored throughout. This study informs on the most effective and acceptable presentation methods for real-time in-vehicle guidance on eco-driving

Engaging with highly automated driving: To be or not to be in the loop?

This desktop driving simulator study investigated the effect of engagement in a reading task during vehicle automation on drivers’ ability to resume manual control and successfully avoid an impending collision with a stationary vehicle. To avoid collision, drivers were required to regain control of the automated vehicle and change lane. The decision-making element of this lane change was manipulated by asking drivers to move into the lane they saw fit (left or right) or to use the colour of the stationary vehicle as a rule (blue – left, red – right). Drivers’ reaction to the stationary vehicle in manual control was compared to two automation conditions: (i) when drivers were engaged and observing the road during automation, and (ii) when they were reading a piece of text on an iPad during automation. Overall, findings suggest that drivers experiencing automation were slower to identify the potential collision scenario, but once identified, the collision was evaded more erratically and at a faster pace than when drivers were in manual control of the vehicle. Short (1-minute) periods of automation used in this study did not appear to impede drivers’ ability to complete simple operational and tactical-level driving tasks, following a system initiated take-over request. Results suggest that until there is an effective strategy to help drivers regain situation awareness during the resumption of control from Highly Automated Driving, they should be encouraged to remain in the driving loop.

Using Driver Control Models to Understand and Evaluate Behavioral Validity of Driving Simulators

For a driving simulator to be a valid tool for research, vehicle development, or driver training, it is crucial that it elicits similar driver behavior as the corresponding real vehicle. To assess such behavioral validity, the use of quantitative driver models has been suggested but not previously reported. Here, a task-general conceptual driver model is proposed, along with a taxonomy defining levels of behavioral validity. Based on these theoretical concepts, it is argued that driver models without explicit representations of sensory or neuromuscular dynamics should be sufficient for a model-based assessment of driving simulators in most contexts. As a task-specific example, two parsimonious driver steering models of this nature are developed and tested on a dataset of real and simulated driving in near-limit, low-friction circumstances, indicating a clear preference of one model over the other. By means of closed-loop simulations, it is demonstrated that the parameters of this preferred model can generally be accurately estimated from unperturbed driver steering data, using a simple, open-loop fitting method, as long as the vehicle positioning data are reliable. Some recurring patterns between the two studied tasks are noted in how the model’s parameters, fitted to human steering, are affected by the presence or absence of steering torques and motion cues in the simulator

Understanding Cue Utility in Controlled Evasive Driving Manoeuvres: Optimizing Vestibular Cues for Simulator & Human Abilities

Most daily driving tasks are of low bandwidth and therefore the relatively slow visual system receives enough cue information to perform the task in a manner that is statistically indistinguishable from reality. On the other hand, evasive maneuvers are of such a high bandwidth that waiting for the visual cues to change is too slow and skilled drivers use steering torques and vestibular motion cues to know how the car is responding in order to make rapid corrective actions. In this study we show for evasive maneuvers on snow and ice, for which we have real world data from skilled test drivers, that the choice of motion cuing algorithm (MCA) settings has a tremendous impact on the saliency of motion cues and their similarity with reality. We demonstrate this by introducing a novel optimization scheme to optimize the classic MCA in the context of an MCA-Simulator-Driver triplet of constraints. We incorporate the following four elements to tune the MCA for a particular maneuver: 1) acceleration profiles of the maneuver observed in reality, 2) vestibular motion perception model, 3) motion envelope constraints of the simulator, and 4) a set of heuristics extracted from the literature about human motion perception (i.e. coherence zones). Including these elements in the tuning process, notwithstanding the easiness of the tuning process, respects motion platform constraints and considers human perception. Moreover the inevitable phase and gain errors arising as a major consequence of MCA are always kept within the human coherence zones, and subsequently are not perceptible as false cues. It is expected that this approach to MCA tuning will increase the transfer of training from simulator to reality for evasive driving maneuvers where students need training most and are most dangerous to perform in reality

Structure of the protective nematode protease complex H-gal-GP and its conservation across roundworm parasites

Roundworm parasite infections are a major cause of human and livestock disease worldwide and a threat to global food security. Disease control currently relies on anthelmintic drugs to which roundworms are becoming increasingly resistant. An alternative approach is control by vaccination and ‘hidden antigens’, components of the worm gut not encountered by the infected host, have been exploited to produce Barbervax, the first commercial vaccine for a gut dwelling nematode of any host. Here we present the structure of H-gal-GP, a hidden antigen from Haemonchus contortus, the Barber’s Pole worm, and a major component of Barbervax. We demonstrate its novel architecture, subunit composition and topology, flexibility and heterogeneity using cryo-electron microscopy, mass spectrometry, and modelling. Importantly, we demonstrate that complexes with the same architecture are present in other Strongylid roundworm parasites including human hookworm. This suggests a common ancestry and the potential for development of a unified hidden antigen vaccine