Drivers use active gaze to monitor waypoints during automated driving

Peer reviewe

Vehicle and Traffic Safety

The book is devoted to contemporary issues regarding the safety of motor vehicles and road traffic. It presents the achievements of scientists, specialists, and industry representatives in the following selected areas of road transport safety and automotive engineering: active and passive vehicle safety, vehicle dynamics and stability, testing of vehicles (and their assemblies), including electric cars as well as autonomous vehicles. Selected issues from the area of accident analysis and reconstruction are discussed. The impact on road safety of aspects such as traffic control systems, road infrastructure, and human factors is also considered

Advanced Sensing and Control for Connected and Automated Vehicles

Connected and automated vehicles (CAVs) are a transformative technology that is expected to change and improve the safety and efficiency of mobility. As the main functional components of CAVs, advanced sensing technologies and control algorithms, which gather environmental information, process data, and control vehicle motion, are of great importance. The development of novel sensing technologies for CAVs has become a hotspot in recent years. Thanks to improved sensing technologies, CAVs are able to interpret sensory information to further detect obstacles, localize their positions, navigate themselves, and interact with other surrounding vehicles in the dynamic environment. Furthermore, leveraging computer vision and other sensing methods, in-cabin humans’ body activities, facial emotions, and even mental states can also be recognized. Therefore, the aim of this Special Issue has been to gather contributions that illustrate the interest in the sensing and control of CAVs

The Psychology of Vehicle Performance: Implications for the Uptake of Electric Vehicles

Road transport accounts for around 16% of global CO2 emissions, and electric vehicles (EVs) represent a potential mitigation route. High performance might offset the disadvantages of higher cost and short range that make their uptake problematic. This research investigated how consumer drivers construe, perceive and value vehicle performance. Research with UK drivers, using the repertory grid method, found that drivers construe vehicle performance as having two independent dimensions, dynamic and cruising performance. A new inter-goal dynamics and feedback control model of driving behaviour was developed to account for differences in the opportunities afforded to perceive vehicle performance in naturalistic driving. This was embedded in a Bayesian model for perception of available vehicle performance. Driving simulation and test track experiments with UK drivers found that: driving behaviour was strongly affected by goal activation; drivers could perceive performance differences in naturalistic driving, but only if they were large; the lowest perceptual difference threshold, for mid-range available vehicle acceleration, was 7.7%; smaller differences could affect driving behaviour (overtaking) through a process of implicit learning. The symbolic value of products is conferred by their symbolic meanings. Two new methods were developed to quantify symbolic meanings, grounded in costly signalling theory, which represents them in terms of personality traits of a typical user. The symbolic meanings of car types, performance attributes and driving styles were all measured. In a randomised controlled trial, UK consumer drivers rated an EV better on dynamic and cruising performance than a conventional ICE control, but this benefit was insufficient to outweigh the disadvantages. The symbolic meaning of an EV was found to be consistent with cruising performance, but inconsistent with dynamic performance. Extended-range EVs would have the dynamic and cruising performance benefits of EVs without the range disadvantages, and may be a desirable option for many once costs reduce

A Unifying Theory of Driver Perception and Steering Control on Straight and Winding Roads

Novel driver support systems potentially enhance road safety by cooperating with the human driver. To optimize the design of emerging steering support systems, a profound understanding of driver steering behavior is required. This article proposes a new theory of driver steering, which unifies visual perception and control models. The theory is derived directly from measured steering data, without any a priori assumptions on driver inputs or control dynamics. Results of a human-in-the-loop simulator experiment are presented, in which drivers tracked the centerline of straight and winding roads. Multiloop frequency response function (FRF) estimates reveal how drivers use visual preview, lateral position feedback, and heading feedback for control. Classical control theory is used to model all three FRF estimates. The model has physically interpretable parameters, which indicate that drivers minimize the bearing angle to an 'aim point' (located 0.25-0.75 s ahead) through simple compensatory control, both on straight and winding roads. The resulting unifying perception and control theory provides a new tool for rationalizing driver steering behavior, and for optimizing modern steering support systems.Control & Simulatio

Vision and Driving after Stroke

Driving a car is often an essential part of maintaining mobility and quality of life, but after a stroke many are forced to cease driving. Homonymous visual field defects (HVFDs) and unilateral spatial neglect (USN) are common sequelae of stroke. For people with HVFDs a legal threshold for extent of field loss exists beyond which a person is not allowed to drive, and most people with clinically detectable USN are also censured from driving. However, some people with HVFDs have been deemed safe to drive, and some with USN have shown normal performance on other skilled visuo-motor tasks. It seems that there is great variation in abilities across individuals with HVFDs and USN, and driving performance cannot be predicted from simple measures such as extent of visual field loss. Several studies have suggested that compensatory eye-movement strategies (particularly saccades into the affected visual field) may be linked with functional improvements post-stroke. This thesis investigates whether eye-movement behaviours are important for stroke patients performing skilled actions such as driving. To test this theory 18 people with HVFDs and/or USN following a stroke and 18 older adult controls were recruited. A series of behavioural measures were taken using a battery of tests: Cognitive and visuospatial measures from classic pen and paper tasks and visual field mapping, saccadic and smooth pursuit accuracy, visual search, simulated steering and simulated hazard perception measures. Across these measures there was a consistent theme that impairments to perception-action functions varied considerably across participants with stroke, but that some individuals were able to function remarkably well. Compensatory eye movement patterns were observed in many, and driving performance was predicted to some extent by saccadic accuracy and visual search performance. The implications are discussed with respect to using eye-movements as a potential target for rehabilitation treatment