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Target classification is one of the applications of wireless sensor networks that aims to recognize the type of mobile targets that navigate within a sensing field. This paper presents a fuzzy-based controller module using MaxMin and MinMax Distributed K-Nearest Neighbors (DKNN) algorithms for ground vehicle classification in order to achieve efficient energy usage and better classification accuracy...
The driving support is one of the most important research areas in intelligent transport system (ITS). Moreover, obstacle extraction system is one of most important system. Here, baseline length of our stereovision system is shorter than general one so that the room mirror can cover it. Accordingly, it can be placed unobtrusively and never be unsighted for the driver. Therefore, our stereovision system...
Ant Colony Optimization (ACO) is a metaheuristic method that inspired by the behavior of real ant colonies. In this paper, we propose a hybrid ACO algorithm for solving vehicle routing problem (VRP) heuristically in combination with an exact algorithm to improve both the performance of the algorithm and the quality of solutions. In the basic VRP, geographically scattered customers of known demand...
We present a method for extracting ground and other planes from a single non rotating laser mounted on a slow moving car used for on-road driving. A laser scan is decomposed into linear clusters. Corresponding clusters from subsequent scans are merged to form planes. The ground plane is identified based on the current vehicle height and the variance in height of the planes. Once these seed planes...
In semi-supervised clustering, domain knowledge can be converted to constraints and used to guide the clustering. In this paper we propose a feature selection algorithm for semi-supervised clustering. In our method, features are conditionally independent. Feature saliency is first computed in unsupervised clustering using the expectation maximization model. Then, it is refined in the tuning step to...
This paper improves the mathematical model for the vehicle routing problem with time windows where a limited number of vehicles is given, which not only reflects the feature of the limited number of vehicles in the depot, but also is compatible with VRPTW; redefines the distance between the customers used in the customer clustering, designs the customer clustering assignment algorithm, which can help...
Time and location data play a very significant role in a variety of factory automation scenarios, such as automated vehicles and robots, their navigation, tracking, and monitoring, to services of optimization and security. Pervasive wireless capabilities combined with time and location information are enabling new applications in areas such as transportation systems, health care, elder care, military,...
Pedestrian safety is a primary traffic issue in urban environment. This article deals with the detection of pedestrians by means of a laser sensor. This sensor, placed on the front of a vehicle collects information about distance distributed according to 4 laser planes. Like a vehicle, a pedestrian constitutes in the vehicle environment an obstacle which must be detected, located, then identified...
In this article we study the capacitated location routing problem (CLRP) which is defined as a combination of two problems: the facility location problem (FLP) and the vehicle routing problem (VRP). The CLRP is not just a purely academic construct; it has many applications in the practice. We propose a hybrid approach based on a tabu search algorithm combined with an improved ant colony system to...
Vehicle tracking is a challenging problem in Intelligent Transport System. This paper presents a vehicle tracking approach combining blob based tracking and feature based tracking. First objects are detected as blobs using codebook(CB) algorithm and scale invariant feature transform(SIFT) features are extracted from the blobs. Then vehicles are tracked by using SIFT to match the vehicles frame-by-frame...
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