Vehicle inspection

About: Vehicle inspection is a research topic. Over the lifetime, 871 publications have been published within this topic receiving 6891 citations. The topic is also known as: roadworthiness test.

The Handbook of Road Safety Measures

Abstract: Contains summaries of the knowledge regarding the effects of 128 road safety measures This title covers various areas of road safety including: traffic control; vehicle inspection; driver training; publicity campaigns; police enforcement; and, general policy instruments It also covers topics such as post-accident care, and speed cameras

Method and system for facilitating vehicle inspection to detect previous damage and repairs

Abstract: Computer-based methods and systems for facilitating the inspection of a vehicle to detect the presence of prior damage and problems with previous repair are provided. Exemplary embodiments provide an inspection facilitator, which includes an inspection engine and an inspection interface. The inspection engine and inspection interface are implemented as an expert system, which directs a technician or apparatus to perform a uniform inspection process. The inspection facilitator, after receiving vehicle specific information, first directs and guides an inspection of the underbody of the vehicle to detect gross level damage or repair. The inspection facilitator then dynamically directs and guides an inspection of the outerbody of the vehicle based upon the nonconformities indicated in response to each directed inspection task. The areas to be inspected and inspection tasks are determined dynamically by comparing nonconformity input to facts and rules programmed into the inference engine of the inspection facilitator in combination with retrieved manufacturing specifications and industry standard repair procedures.

A critical review of macro models for road accidents . proceedings international conference on new ways and means for improved safety, tel aviv, israel, february 20-23, 1989

Abstract: A critical review of the state-of-the-art of macro models for road accidents is presented. Such a review is meant to identify and establish the significance of policy and socio-economic variables affecting the level of road accidents. The aim is to identify those variables associated with effective policies and interventions, in order to enable decision makers to improve the level of road safety. The variables that appear to affect the number of fatalities or injuries were found to be vehicle miles travelled (VMT); vehicle numbers; income in its various forms; the percentage of young drivers on the one hand and, on the other hand, intervention policies such as speed limits, periodic vehicle inspection, and minimum alcohol drinking age. Viewed critically, the state-of-the-art concerning the models being used to explain and predict the phenomenon of road accidents is still deficient. One possible approach to correct this deficiency is based on consumer utility theory, using analytical models built on a newly constructed theoretical framework. Success in estimating such models may improve predictions of road accidents, thus directly demonstrating the comparative cost-effectiveness of alternative intervention policies. (TRRL)

Intelligent Monitoring and Inspection of Power Line Components Powered by UAVs and Deep Learning

Abstract: In this paper, we present a novel automatic autonomous vision-based power line inspection system that uses unmanned aerial vehicle inspection as the main inspection method, optical images as the primary data source, and deep learning as the backbone of the data analysis. To facilitate the implementation of the system, we address three main challenges of deep learning in vision-based power line inspection: (i) the lack of training data; (ii) class imbalance; and (iii) the detection of small components and faults. First, we create four medium-sized datasets for training component detection and classification models. Furthermore, we apply a series of effective data augmentation techniques to balance out the imbalanced classes. Finally, we propose the multi-stage component detection and classification based on the Single Shot Multibox detector and deep Residual Networks to detect small components and faults. The results show that the proposed system is fast and accurate in detecting common faults on power line components, including missing top caps, cracks in poles and cross arms, woodpecker damage on poles, and rot damage on cross arms. The field tests suggest that our system has a promising role in the intelligent monitoring and inspection of power line components and as a valuable addition to smart grids.