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Autonomous driving is on the horizon. Vehicles with partially automated driving capabilities are already in the market. Before the widespread adoption however, human factors issues regarding automated driving need to be addressed. One of the key issues is how much drivers trust in automated driving systems and how they calibrate their trust and reliance based on their experience. In this paper, we...
The feedback of state transitions and intentions of the automation system is very important for obtaining and/or increasing the driver's awareness of the automation system's state during partially automated driving. In this paper, the feedback is realized via rotational vehicle motions and not, as usual, visually. The detailed design of active pitch motions for feeding back state transitions and intentions...
The interaction between a human driver and an automated driving system may improve when the automation is designed in such a way that it behaves in a human-like manner. This paper introduces a human-like steering model, in which the driver adapts to the risk due to uncertainty in the environment. Current steering models take a risk-neutral approach, while the fields of economics and sensorimotor control...
This paper considers the problem of the absent-minded driver who must choose between alternatives with different payoff under the conditions of imperfect recall and varying degrees of knowledge of the system. We show that agents with access to quantum resources, or with a quantum mechanical basis, can obtain superior performance as compared to classical agents. The paper also considers the problem...
We present here deep covariance learning models for predicting drivers' drowsy and alert states from Electroencephalography (EEG). Three types of deep covariance learning models are proposed: SPDNet, CNN, and DNN on covariance matrices. Our test results show that all the deep covariance learning methods reported better performance than shallow learning methods including Riemannian methods and STCNN,...
With new technologies in the area of assistance and automation on the market, the dream of driving in automated vehicles becomes reality. While certain research areas predict fully autonomous vehicles in the near future, a more feasible composition still has a driver, at least as a back-up solution, operating the vehicle in certain situations with certain degrees of control, cooperating with the automation...
In this paper, we experimentally examine the relationship between visual cognition difficulty and target-tracking eye movements, which recorded during moving target cognition. Generally, such eye movements are observed when humans perceive a moving object and they vary widely due to many factors, such as target shape, backgrounds, illumination conditions, and so on. Several systems have been proposed...
Conventional traffic light control systems are based on fixed time intervals of the traffic lights. These conventional fixed traffic light controllers have limitations and are less efficient because they use a hardware, which functions according to the program that lacks the flexibility of modification and adaptation on a real time basis. Thus due to the fixed time intervals of green and red signals...
To drive low-frequency resonant loads with high output power and low emission, Class-AB push-pull stages are state of the art. But their theoretically superior emission performance is often sacrificed for efficiency. A differential Class-D concept is a promising alternative, because it can combine both excellent power efficiency and low missions. This work is a survey on the main sources of distortions...
In this paper we propose a vehicular speed learning framework that recommends best traffic load based on a particularly required latency and throughput conditions to be achieved. The framework is composed of two main layers, the base layer and two enhancement layers. The base layer aims at providing an in-vehicle wireless receiver to inform the driver about the speed limit within the area he/she is...
The basis of this study is to create an insight for target vehicle path following or improving situational awareness by using path accumulation and ego-motion compensation. Possible application variants of the strategy, for highways and urban roads are also described. The study is also extended for enhancing path accumulation in noisy environment or sensing by making use of spline based curve approximation...
Highly automated driving tremendously reduces workload of drivers. However, the drivers may lose their visual attention to road ahead due to the out-of-the-loop problem. Haptic guidance has been developed to reduce drivers' workload while keeping the drivers in the control loop. The haptic guidance system continuously provides assistant torques on the steering wheel so that both the driver and the...
Even highly sophisticated and reliable driver assistance systems might encounter critical situations that are outside system design capacity. This can lead to a conflict in viewpoints between the driver and automation. To evaluate the effects of such conflicts on human-machine interaction and cooperation, overall performance, and safety, an experiment was designed to determine driver responses to...
This paper describes the design of a new haptic shared steering control framework for automated driving systems. In this framework, the shared control problem is formulated as a constrained optimization problem which is solved online by a model predictive controller. Without driver's intervention, the system assumes automatic lane-keeping control. When the driver takes over control, by adapting the...
At higher automation levels, drivers do not need to permanently monitor the surrounding traffic environment and are allowed to focus on other tasks, while an advanced driver assistance system controls the vehicle. However, there is evidence that human drivers are prone to driving mistakes when they have to take over control from the ADAS due to their lack of situation awareness. Smoothly shifting...
Visual field defects, which are partial losses of the visual field, may have an impact on driver behavior. They affect the driver's information processing and are a possible cause of traffic accidents. Some patients who suffer from optic diseases related to visual field defects try to compensate for their disability by more actively moving their head in order to look around more carefully. Compensation...
Conditionally automated driving systems may soon be available on the market. Even though these systems exempt drivers from the driving task for extended periods of time, drivers are expected to take back control when the automation issues a so-called take-over request. This study investigated the interaction between take-over request modality and type of non-driving task, regarding the driver's reaction...
Speed limit traffic sign recognition plays a key role in intelligent transport system (ITS), especially in driver assistant system (DAS) and intelligent autonomous vehicles (IAV). Although traffic signs are clearly defined in color, shapes for easily detecting purpose, an excellent traffic sign detection system still be a challenge for researchers and manufactures because of the strict requirements...
In our daily life we develop many activities that result imperceptible for the majority of us because the null effort that they represent to develop them, however, when we most develop those activities with any type of restriction, they acquire a higher level of difficulty. One simple activity is the communication process; we develop it in an easy way during almost all day, however, for people with...
This paper presents a cooperative shared control driver assistance system which supports the driver in the longitudinal vehicle control. The system architecture design enables the driver and the assistance system to apply a force on the accelerator pedal. Therefore, a cooperative control algorithm has to be developed. This design problem can be described mathematically as a differential game. For...
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