The objective of this study was to identify how physiological measures relate to self-reported vehicle seating discomfort. Twelve subjects of varied anthropometric characteristics were enrolled in the study. Subjects sat in two seats over a 2-h period and were evaluated via three physiological measures (near-infrared spectroscopy, electromyography and pressure mapping) yielding six testing sess...

The motivation of this research is the need for short-term data collection about freight traffic movement in urban areas. We seek to develop automated vehicle classification systems based on networks of small, battery-powered and wireless, intelligent sensors that can be easily deployed with brief setup time (tens of minutes), with accurate vehicle information (as good as or better than human o...

The task of classifying the types of moving vehicles in a distributed, wireless sensor network is investigated. Specifically, based on an extensive real world experiment, we have compiled a dataset that consists of 820 MByte raw time series data, 70 MByte of pre-processed, extracted spectral feature vectors, and baseline classification results using the maximum likelihood classifier. The purpos...

The Federal Highway Administration (FHWA) Office of Highway Planning requires states to furnish vehicle classification data as part of the Highway Performance Monitoring Systems (HPMS). To comply with this requirement, most states use the “F-Scheme” to classify vehicles. This scheme classifies vehicles in 13 classes depending on a number of factors, primarily the number of axles and the axle sp...

Vehicle Class is an important parameter in road traffic management. With the help of vehicle classification the computation of percentage of state-aid streets, highways becomes simpler and it is also used in automated toll bridges. In this paper we classify the vehicles into three main broad categories: A) Light vehicle B) Medium Vehicle C) Heavy Vehicle. Firstly, the image pre-processing is do...

We present a system to detect and track moving vehicles based on the pixelwise classification approach. In this approach escapes some of the existing frameworks for detection vehicles in traffic monitoring systems. So many researchers and intelligent minds are introduces so many technique but not provided the accurate results. Proposed technique uses designed pixel wise classification method, c...

Automatic vehicle classification has expanded into a momentous topic of study due to its importance in autonomous navigation, traffic analysis, surveillance security systems, and transportation management. This paper presents multiclass image based classification of vehicles like bikes and cars using soft computing algorithms like artificial neural network decision tree and support vector machi...

Automatic vehicle classification (AVC) systems provide information about classes of vehicle that can be used for many purposes. This paper describes a axle count and axle spacing using wireless accelerometers sensors and magnetometers sensors. The vehicle axles are detected by accelerometer sensors, and the vehicles arrivals, departures and speed are estimated by magnetometers. The prototype sy...

In the mobile computing era, smartphones have become instrumental tools to develop innovative mobile context-aware systems. In that sense, their usage in the vehicular domain eases the development of novel and personal transportation solutions. In this frame, the present work introduces an innovative mechanism to perceive the current kinematic state of a vehicle on the basis of the acceleromete...

This proposed research work describes a system that is used for recognition and classification of vehicles from low vision video footage captured by surveillance cameras. It's an important step for many applications in intelligent transportation systems and video surveillance. For carrying out the above said process, first step is detection of the vehicles present in the enhanced video frame & ...