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Many of the fatalities involved on-road accidents are associated with driver distraction. In order to reduce the possible chances of road disasters, it is essential to characterize the pre-requisites of driver distraction. While driving, the driver might get distracted by several ways such as talking on the cell phone, texting, and having a conversation with the passenger. There has been extensive...
Distracted driving is the major cause for injuries and fatalities due to road accidents. Driving is a continuous task which requires constant attention of the driver; a certain level of distraction can cause the driver lose his/her attention to the driving task which might lead to an accident. Thus, detection of distraction will help reduce the number of accidents. There has been much research conducted...
This paper presents a new Electroencephalography (EEG)-based method to detect emergency situations while drivers employ a brain-machine interface but not using limbs to operate an assistive vehicle. EEG signals were first preprocessed to remove the blinking artifact. The sums of powers of five rhythms (including alpha, delta, beta, theta, and low gamma rhythms) from 16 channels were then computed...
The traffic sign detection and recognition is an integral part of Advanced Driver Assistance System (ADAS). Traffic signs provide information about the traffic rules, road conditions and route directions and assist the drivers for better and safe driving. Traffic sign detection and recognition system has two main stages: The first stage involves the traffic sign localization and the second stage classifies...
With rapid digital expansion, usage of digital meters are gaining momentum. However, analog dials are still prevalent in instrument panels due to performance purposes and user appeasement. In teleoperated vehicles and remote monitoring applications there is necessity for processing and wireless transmission of the data collected from the analog gauges. In this paper a methodology for automatic interpretation...
In the paper a 79GHz radar located at an intersection is used for classification of pedestrians from vehicles. Compared to in-vehicle radars, radars used for intersection surveillance meet more complicated recognition requirements because of the diversity of moving patterns of both pedestrians and vehicles. We propose to extract a dual set of features from radar measurements and to use them with two...
Fatigue driving has become one of the main causes of traffic accidents. At present, many driving fatigue detection methods are based on the image processing technology, while these methods are easy to be affected by the driving environment, which limits the accuracy and reliability and accuracy of the detection. For this limitation, this paper introduces the multi-source information detection and...
Crash hotspot detection is important to reduce traffic crashes by allowing effective deployment of countermeasures in those locations. However, current hotspot detection methods rely mostly on crash occurrences and, therefore, countermeasures can be implemented only after a number of crashes have been occurred. To prevent crashes prior to their actual occurrences, crash precedents, also known as surrogate...
Drivers use some combination of head, eye and hand movements to perform varying number of tasks from driving related to non-driving secondary tasks. Furthermore, the combinations may vary depending on the task performed. It is important to model and understand these variations in order to build predictive systems, explore driving styles, detect activities, etc. This study, therefore, introduces a...
The problems of hand detection have been widely addressed in many areas, e.g. human computer interaction environment, driver behaviors monitoring, etc. However, the detection accuracy in recent hand detection systems are still far away from the demands in practice due to a number of challenges, e.g. hand variations, highly occlusions, low-resolution and strong lighting conditions. This paper presents...
It is widely known that many traffic accidents occur every year not only in Japan but also throughout the world. Sleepiness or drowsiness, which is the cause of dozing at the wheel, happens regardless of the physical condition of the driver at the time such as after having had meals or at midnight. This indicates that it is too difficult to expect the driver to avoid sleepiness or drowsiness by themselves...
This article describes the detection of the characters of the license plate through of computer vision techniques: such as cascade of classifiers based in sobel algorithm, analysis of peaks and valleys, and support vector machines; the search for the region of the plate begins by detecting vehicles, then character segmentation and concludes with the recognition of these. The system was tested in different...
The applications of computer vision are widely used in traffic monitoring and surveillance. In traffic monitoring, detection of vehicles plays a significant role. Different attributes such as shape, color, size, pose, illumination, shadows, occlusion, background clutter, camera viewing angle, speed of vehicles and environmental conditions pose immense and varying challenges in the detection phase...
Lane departure and forward collision detection plays an important role in autonomous driving and commercial driver-assistance systems. This paper presents an integrative approach to vision-based lane departure detection which aims to be as simple as possible to enable the real-time computation while being able to adapt to a variety of highway and urban scenarios on different weather conditions. In...
In most of the traffic safety studies, both the identification of high-risk locations and the assessment of safety improvement solutions are done through the use of historical crash data. This study proposes an alternative approach that makes use of traffic conflicts extracted from traffic video recordings for safety assessment. State-of-the-art computer vision techniques are used to extract vehicle...
Naturalistic driving recordings are important for understanding the driver behavior. Driver behavior events of interest in these recordings, such as driver confusion and stress, are important for studying driver behavior and develop the next generation advanced driver assistant systems (ADASs). Unfortunately, such events are rare cases in the naturalistic driving data. Manual annotation is usually...
This paper proposed a new Vehicle Make Recognition (VMR) method using the PCANet features extracted from vehicle front view images. The PCANet architecture processes every input vehicle image through only three very simple data processing components: cascaded principle component analysis (PCA), binary hashing, and block-wise histograms, and generates a sparse vector as the feature representation....
In this work we explore Hidden Markov models as an approach for modeling and recognizing dynamic hand gestures for the interface of in-vehicle infotainment systems. We train the HMMs on more complex shape descriptors such as HOG and CNN features, unlike typical HMM based approaches. An analysis of the optimal hyperparameters of the HMM for the task has been carried out. Also, dimensionality reduction...
Automated driving functions are under intensified development by industry and academia since the last decade. Due to the large operation space and various complex scenarios automated driving functions have to cope with, assessment efforts are expected to rise dramatically. In order to quantify benefits and risks of these functions in an efficient way, this paper describes a holistic approach for the...
Several vehicle detection methods in urban traffic scenes, such as vehicle detection method based on symmetrical features, vehicle detection method based on license plate, vehicle detection method based on Gabor features and Support Vector Machines (SVM), and vehicle detection method based on Haar-like features and AdaBoost classifier, are comparatively used in this paper. The theoretical analysis...
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