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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...
Extracting hand regions and their grasp information from images robustly in real-time is critical for occupants' safety and in-vehicular infotainment applications. It must however, be noted that naturalistic driving scenes suffer from rapidly changing illumination and occlusion. This is aggravated by the fact that hands are highly deformable objects, and change in appearance frequently. This work...
The driver's face is key to a less intrusive method to monitoring the driver to derive information such as distraction, drowsiness, intent, and where they are looking. A vital step in extracting these higher level information is to find the driver's face and individual components such as eyes, nose and mouth, along with the direction they are facing towards. In the context of safety critical situation...
We proposed a Bayesian farmework with the goal to enhance the performance of region proposals generated by Edgeboxes for vehicles. We proposed an innovative objectness measure that combines several geometrical characteristics of proposals into a Bayesian framework. Our method exploits Bayesian to respectively integrate the initial score, aspect ratio and several 3D features related to depth information...
The goal of region proposal approaches is to decrease the hunting zone for classifiers. An innovative objectness measure that combines several characteristics of proposals in a Bayesian framework is explicitly presented in this paper. We try to use Bayesian to respectively integrate four different features of proposals, and employ the posterior probability of positive samples as new score to guide...
Docking an autonomous underwater vehicle (AUV) is a critical part of many current and envisioned Navy, commercial, and scientific missions. Many missions require an AUV to dock with a subsea node that is not restrained through attachment to the seafloor or to a surface platform significantly larger than the system that is docking into it. Space and Naval Warfare Systems Center Pacific (SSC Pacific)...
In the current day and age, traffic in urban areas is becoming more and more complex leading to congested roads and intersections. Hence, the need for sophisticated traffic control system to reduce the congestion and provide better flow management. In this paper, we present briefly the basic notions and the most important parameters that affects the traffic control. Then, we provide a survey on the...
Detecting large animals on roadways using automated systems such as robots or vehicles is a vital task. This can be achieved using conventional tools such as ultrasonic sensors, or with innovative technology based on smart cameras. In this paper, we investigate a vision-based solution. We begin the paper by performing a comparative study between three detectors: 1) Haar-AdaBoost; 2) histogram of oriented...
Fully autonomous navigation of unmanned vehicles, without relying on pre-installed tags or markers, still remains a challenge for GPS-denied areas and complex indoor environments. Doors are important for navigation as the entry/exit points. A novel approach is proposed to autonomously detect™ doorways by using the Project Tango platform. We first detect the candidate door openings from the 3D point...
Nowadays railway vehicle speed sensors suffer from insufficient measurement accuracy. E. g. the Doppler radar is prone to adverse weather conditions while wheel speed sensors are not sufficiently robust against wheel slip and wheel wear. However, since velocity sensors are safety relevant components, it becomes clear that conventional sensors are not able to cover all the requirements for an everyday...
As an advancement vehicular traffic in urban areas, traffic congestion mitigation is a serious problem. In order to reduce traffic congestion at intersections intelligent signaling mechanisms required. This work proposes the design of a system that utilizes and efficiently manages traffic light controllers according to the congestion predicted at each line using real time data. At each signal change,...
In this article, an approach on the LIDAR signal processing to detect low SNR target for the intelligent vehicle is presented. It focuses on the raw data processing of the intensity observations and aims to produce the improved point measurements. The algorithm employs two types of elemental detectors, which are respectively based on the CFAR coherent integration and the Bayesian Track-Before-Detect...
In this paper the concept of Bayesian Networks (BN) is applied to the problem of traffic data acquisition by data fusion. Two wireless communication based sensors are used as data sources: IEEE 802.15.1 Bluetooth and IEEE 802.11p V2X (vehicle to vehicle and vehicle to infrastructure). Via V2X so called cooperative awareness messages (CAM) are received, which provide information on vehicle location...
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