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The vehicular mobility models will seriously affect the simulation results of the key technologies for Vehicular Delay Tolerant Networks. Most of the existing vehicular mobility models are synthetic mobility models which cannot properly reflect the real environment. This paper proposed vehicular mobility model based on real traces, which has considered the road topology, the vehicle speed control...
Taxi is an indispensable component of urban transportation system, which aims to provide a convenient and efficient means of transport. However, unlike bus service that has fixed station and schedule, to most taxi-seekers, the formula for catching a taxi at the nearest place with the shortest waiting time is experience plus luck, especially in peak hour or adverse weather conditions. In this demo...
In this paper, we propose a probabilistic method to model the dynamic traffic flow across non-overlapping camera views. By assuming the transition time of object movement follows a certain global model, we may infer the time-varying traffic status in the unseen region without performing explicit object correspondence between camera views. In this paper, we model object correspondence and parameter...
In order to ensure the accuracy of vehicle tracking in the situation of similar background, the SIFT algorithm is proposed. Meanwhile, the PCA algorithm is used to reduce the dimensionality of SIFT descriptors to improve the system's real-time and a SIFT-Kalman information fusion tracking algorithm based on PCA is set up. The results of experiments showed the proposed algorithm performs well when...
In this paper, we propose a zoom-based approach for parking space availability. The main idea of our scheme lies on the fact that drivers near the queried locations are interested in detail (zoomed-in) parking space information, while drivers in a distant place are interested in rough (zoomed-out) information about free parking spaces. Our zooming technique is based on discrete cosine transform. Besides,...
This paper presents a novel approach to describe traffic accident events at intersections in human-understandable way using automated video processing techniques. The research mainly proposes a new technique for video-based traffic accident analysis by extracting abnormal event characteristics at intersections. The approach relies on learning normal traffic flow using trajectory clustering techniques,...
In this paper we present a dynamic version of vehicle routing problem. Dynamic customer arrives dynamically and the vehicle dispatching system must adjust routing that vehicle is executing to meet dynamic customer. The goal of optimization is to provide the dynamic customer required transportation and minimize the service cost subject to various constraints. A model based on multiple agent system...
One of the fundamental requirements of a traffic management system is the ability to determine when an incident has occurred so that proper responses can be initiated. Most of the existing automatic incident detection techniques suffer from many limitations including their inability to detect incidents under non dense traffic conditions and generation of many false positive alarms. In this paper,...
License plate detection and recognition system (LPDR) is applicable to wide range of uses such as highway toll collection, traffic management, and many more. One of the problems of this application is finding the position of license plate from cars because many cars have difference in uncertain positions of license plates and unclean license plates. The purpose of this project is to assess the efficiency...
Automatic mining of vehicle behaviors from raw data collected by multiple sensors provides meaningful qualitative descriptions of the vehicle status. These qualitative behavior descriptions can be used in scenario parsing and have further applications in vehicle surveillance and frontal collision warning systems. In current approaches, the number of behavior categories is supposed to be known, or...
To improve the classification accuracy, a new algorithm is developed with binary proximity magnetic sensors and back propagation neural networks. In this scheme, we use the low cost and high sensitive magnetic sensors that detect the magnetic field distortion when vehicle pass by it and estimate vehicle length with the geometrical characteristics of binary proximity networks, and finally classify...
Precise traffic lane boundary identification is the precondition for a good performance of the side-looking traffic flow detection radar. Some approaches have been proposed and developed for this specific purpose. However, these methods either require onerous measurements and prior knowledge, or large amounts of statistics and a long learning duration which cause great difficulties on the practical...
The use of IEEE 802.11p for supporting intelligent transportation systems (ITS) enables enhancing the drive experience to provide vehicle users with useful information related to road efficiency and public safety. Safety services, such as collision or sudden hard braking warning, are used to improve passenger safety and reduce fatalities. Along with the delay-critical nature of those services, the...
In this paper, we proposed an intelligent visual surveillance in specific sea-area based on video processing. We apply the technology of computer vision and video processing to implement the automatic system. At the first, we separate background and foreground in videos, and set a weight to update the new background. To extract the moving ships in videos, we apply the techniques including the change...
With this enormous speed in generating and collecting images, there is an extreme need in extracting interesting and useful knowledge from image archives. In our previous works, we have proposed an image mining framework to extract knowledge from a sequence of images. The framework is composed of two main modules: image analysis and knowledge processing. In this paper, we successfully customized the...
The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Here we employ machine learning techniques to detect driver drowsiness. The system obtained 98% performance in predicting driver drowsiness. This is the highest prediction rate reported to date for detecting...
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