This paper describes a virtual prototype of a PEMFC based Hybrid Electrical Military Vehicle developed within the Virtual Test Bed (VTB) environment. The VTB is software for modeling, simulation, and virtual prototyping of multi-disciplinary systems. Several of the main models used in the vehicle system especially the fuel cell model are described, and then a system-level model of a High Mobili...

In this paper, we propose speeded-up algorithm for human/vehicle classification in real-time surveillance system. We have approached this problem using silhouette-based template matching. The silhouette of the object is extracted, and then it is compared with representative template models. Template models are previously stored in the database. Our algorithm is similar to previous pixel-based t...

Semi-supervised learning attracts much concern because it can improve classification performance by using unlabeled examples. A novel semi-supervised classification algorithm SsL-ARC is proposed for real-time vehicle recognition. It makes use of the prior information of object vehicle moving trajectory as constraints to bootstrap the classifier in each iteration. Approximate region interval of ...

With technology of digital image recognition, the data frames include vehicle’s digital image can be detected automatically from an Audio Video Interleaved (AVI) File, and vehicle type will be recognized automatically. The system consists of four modules: Reading AVI file and decomposing it into digital image frames; Motion detection; Vehicle’s digital image processing; Module of vehicle type c...

OBJECTIVE The increase in the number of fatalities caused by road accidents involving heavy vehicles every year has raised the level of concern and awareness on road safety in developing countries like Malaysia. Changes in the vehicle dynamic characteristics such as gross vehicle weight, travel speed, and vehicle classification will affect a heavy vehicle's braking performance and its ability t...

This paper presents a review on design and control of automated guided vehicle systems. We address most key related issues including guide-path design, estimating the number of vehicles, vehicle scheduling, idle-vehicle positioning, battery management, vehicle routing, and conflict resolution. We discuss and classify important models and results from key publications in literature on automated ...

This paper describes a vision-based vehicle detection system for a blind spot warning function. This detection system has been designed to provide ample performance as a driving safety support system, while streamlining the image processing algorithm so that it can be processed using the computational power of an existing ECU. The procedure used by the system to detect a vehicle in a blind spot...

Vehicle detection in traffic scenes is an important issue in driver assistance systems and self-guided vehicles that includes two stages of Hypothesis Generation (HG) and Hypothesis Verification (HV). The both stages are important and challenging. In the first stage, potential vehicles are hypothesized and in the second stage, all hypotheses are verified and classified into vehicle and non-vehi...

To improve the accuracy of real time vehicle surveillance, utilize the advances in wireless sensor networks to develop a magnetic signature and length estimation based vehicle classification methodology with binary proximity magnetic sensor networks and intelligent neuron classifier. In this algorithm, we use the low cost and high sensitive magnetic sensors to measure the magnetic field distort...

This paper proposes a lightweight model combined with data augmentation for vehicle detection in an intelligent sensor system. Vehicle can be considered as binary classification problem, or non-vehicle. Deep neural networks have shown high accuracy audio classification, and convolution are widely used feature extraction classification. However, the performance of deep is highly dependent on ava...