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Sensing and computing capabilities of modern traffic intersections have greatly improved in recent years, but current control policies do not fully utilize these capabilities. In this paper, we present a novel intersection control algorithm based on an objective function that accounts for drivers' time preferences. In particular, the intersection places greater importance on a vehicle which has been...
We present a model and a hypothesis testing based framework for determining genuinely good service providers from the ratings given to them by customers, allowing ratings to be imperfect representations of the service provided. The problem is complicated because the nature of the customer that rates the service provider affects the reliability of the rating, but this nature is not known a priori and...
As a response to rapidly increasing costs due to congestion in urban traffic environments, the development of Intelligent Transport Systems (ITS) has paved the way towards new and innovative mobility concepts. With most of these concepts offering benefits in travel time and congestion relief, they also come with requirements of a fully participating vehicle network and a centralized routing architecture...
Traffic sign detection and recognition systems are essential components of Advanced Driver Assistance Systems and self-driving vehicles. In this contribution we present a vision-based framework which detects and recognizes traffic signs inside the attentional visual field of drivers. This technique takes advantage of the driver 3D absolute gaze point obtained through the combined use of a front-view...
A primary-side output current estimator with process compensator for the flyback control circuits is designed and analyzed in this investigation. Flyback control circuits play a key role of smart lighting systems, where LED drivers require a compensator to keep the system stable. The process sensor is in charge of the detection of the chip process corner. Then, the process compensator correspondingly...
Drivers fatigue is the major cause of traffic accidents all over the world. Advanced image processing technology processing the stream obtained from infrared cameras is able to supervise blinking rate and at the same time drowsiness of the vehicle driver. Such a system may warn not only the tired person, but also the passengers, whom the driver takes responsibility for. In this article we present...
This paper proposed a blind spot detection & warning system (BSDWS) for daytime and nighttime conditions. The proposed BSDWS included system architecture, radar system structure and algorithms, Intermediate frequency (IF) signal processor, motive target detector and blind spot area calibration method and system control strategy. Line frequency modulated continuous wave (LFMCW) millimeter-wave...
Accidents have become one of the usual occurrences on roads throughout the world. Thousands of people lose their lives or become disabled every day. Speed limits are enforced to control the movement of vehicles along traffic lanes. As per the research statistics, violation of speed limits by the drivers is one of the significant reasons for the road accidents. Detecting the drivers who violate speed...
Face detection is a vital step in the process of extracting semantic information about the driver's state, such as distraction and fatigue, from pixel values in images looking at the driver. Therefore, in the context of time and safety critical situation like driving, efficient use of time and reliable detection of faces is essential. While challenges like lighting and occlusion are prevalent in the...
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...
In this paper we explore some fundamental differences between control strategies modeled based on economic theory principles as opposed to more traditional control theory principles. More specifically, we explored differences between our bid-based control model and various actuated control models. The comparisons include situations where maximum greens are imposed in actuated control, and situations...
Automatic Vehicle Location (AVL) is becoming an important tool in Intelligent Transportation Systems (ITS) in the past few years, as it is an effective way of collecting and transmitting data regarding the vehicle's trip for real-time or future use. A methodology for analyzing the state of the art regarding the application of these systems is proposed in a form of a systematic literature review, by...
Searching through and selecting data sets from large traffic databases with sensor information is often a cumbersome manual process. In this paper we present an idea that may dramatically fasten and streamline this process. The idea is to build a fast search index (COSI: COngestion Search engIne) based on meta data in combination with features from the traffic patterns along routes. Instead of ploughing...
This paper presents an agile approach to facilitate the rapid development of traffic sign classification algorithms in heavy vehicles under a wide range of visibility conditions. A vision-based traffic sign recognition system makes a significant contribution to improving the transportation safety by enhancing the driver's awareness on important road signs in an automotive cockpit environment. It has...
Hand detection is an important issue in the analysis of drivers activities, assessment of drivers alertness, and subsequent development of driver safety monitoring system. In this work, the hand detection problem is addressed in the deep Convolutional Neural Network (CNN) framework. Hypothesis of hand regions are first generated with high recall rate by AdaBoost detector associated with Aggregated...
We consider the problem of estimating queue-lengths at an intersection from a pair of advance and stop bar detectors that count vehicles, when these measurements are noisy and biased. The key assumption is that we know weather the queue is empty or not. We propose a real-time queue estimation algorithm based on stochastic gradient descent. The algorithm provably learns the detector bias, and efficiently...
Congestion on freeways restrains its ability to provide smooth traffic flow. Normally congestion occurs when traffic volumes are considerably greater than the link capacity especially in the peak hours or in case of incidents that disturb the traffic flow, which either are denoted as recurrent and nonrecurrent congestion respectively. As a consequence, the freeway network performance is adversely...
Intelligent and automatic detection of pavement distress is a necessary mean to guarantee the safety and the comfort of road freight vehicles, which plays an important role on the pavement maintenance and the freight transportation. Based on analyzing neighboring gray difference, local minimum gray analysis and the sub-block label, a joint automatic detection method of the pavement distress is proposed...
Performance measures and adaptive control methodologies for traffic signal systems currently require intersections to be instrumented with vehicle detectors and communication equipment, which can require substantial engineering resources to deploy and maintain. Recent studies have explored the use of Connected Vehicle (CV) data for signal performance measures at various levels of market penetration,...
Vehicle detection is an essential task in an intelligent vehicle. Despite being a well-studied vision problem, it is unclear how well vehicle detectors generalize to new settings. Specifically, this paper studies the generalization capability of vehicle detectors on a U.S. highway dataset. Two types of models are employed in the experimental analysis, a subcategory aggregate channel features model...
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