The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Driver-in-the-loop and different human-machine goal consistency should be considered when designing driver-AFS interactive steering control system. In this paper, a novel design approach, namely dynamic game theory is used for the modelling of shared steering control between driver and AFS. Linear Quadratic dynamic optimization approach is used to derive the non-cooperative Nash, non-cooperative Stackelberg,...
The main interest of this study is to find a system that could detect typical signs of drowsiness progression and warn a car driver before driving behavior becomes dangerous. An early detection of impaired conditions due to drowsiness would probably lead to a reduction in traffic accidents. In this matter, a lot of researches have already been done but although many detection devices are available...
In order to reduce the number of accidents caused by the call when the driver was driving, this paper uses the computer vision technology to dectet the behavior of the driver. Based on the constrained local models (CLM) to detect the characteristic changes of the mouth area, combine the HSV color space and the template matching to detect the hand characteristics to judge whether the driver has the...
Real-time simulation tools are commonly used for designing and testing of automotive embedded control systems. In addition, the Hardware-In-the-Loop (HIL) technique enables previous verification and validation of control strategy avoiding an expensive and time-consuming field test. For this reason, this paper shows a HIL platform for designing and testing of Electrical Power Assisted Steering Systems...
This paper aims to present an improved traffic risk predictor, applying a fuzzy version of Harmonic Systems. The topic has many contributions from many diverse fields. From the practical perspective, there are a few tools that may be successfully used for a driver, pedestrian and cyclist risk prediction at the same time, with no extra devices. The proposed predictor can be used in any mobile device,...
The main causes of highways mortality are fatigue and sleepiness while driving. In this paper, we propose a method to detect the transition between wakefulness and sleepiness states based on driver's brain activity recorded through Electroencephalography (EEG). Our new method uses the Phase Locking Value (PLV)to extract data that are directly related and correlated to the sleepiness. PLV measures...
This paper presents the design and implementation of a current controlled Rotor Flux Oriented PMSM for automotive steer-by-wire applications. The development of a realistic torque feedback reference is carried out by monitoring the steering torque while driving a commercial vehicle. The paper shall discuss the torque dynamics of the PMSM drive with respect to position demands replicating a driver...
This paper investigates visual attention control using the presentation of directional flow stimulus to peripheral vision. Peripheral vision is known to have a superior motion-perception capability. Since central vision is usually used for a primary visual task, it would be quite useful if we could control one's attention by providing assistive information through peripheral motion cues without interfering...
Emerging technologies in the field of automatization meanwhile enable partially and highly automated vehicles in the aviation and automotive domains, where the human operators are assisted or (partially/temporarily) replaced in their tasks by advanced automation systems. Nevertheless due to technological limitations and ethical reasons, full autonomous vehicles in both domains might not be realizable...
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...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.