In order to be deployed in driving environments, Intelligent transport system (ITS) must be able to recognize and respond to exceptional road conditions such as traffic signs, highway work zones and imminent road works automatically. Recognition of traffic sign is playing a vital role in the intelligent transport system, it enhances traffic safety by providing drivers with safety and precaution...

This paper describes the environment perception system designed for intelligent vehicle SmartV-II, which won the 2010 Future Challenge. This system utilizes the cooperation of multiple lasers and cameras to realize several necessary functions of autonomous navigation: road curb detection, lane detection and traffic sign recognition. Multiple single scan lasers are integrated to detect the road ...

Smart Cities is a vision driven by the availability of governmental data that fosters many challenging applications. One of them is the management of inconsistent traffic regulations, i.e., the handling of inconsistent traffic signs and measures in urban areas such as wrong sign posting, or errors in data acquisition in traffic sign administration software. We investigate such inconsistent traf...

Traffic sign recognition (TSR), taken as an important component of an intelligent vehicle system, has been an emerging research topic in recent years. In this paper, a traffic sign detection system based on color segmentation, speeded-up robust features (SURF) detection and the k-nearest neighbor classifier is introduced. The proposed system benefits from the SURF detection algorithm, which ach...

A biologically plausible model of traffic sign detection and recognition invariantly with respect to variable viewing conditions is presented. The model simulates several key mechanisms of biological vision, such as space-variant representation of information (reduction in resolution from the fovea to retinal periphery), orientation selectivity in the cortical neuron responses, and context enco...

In this paper, we investigate the robustness of traffic sign recognition algorithms under challenging conditions. Existing datasets are limited in terms of their size and challenging condition coverage, which motivated us to generate the Challenging Unreal and Real Environments for Traffic Sign Recognition (CURE-TSR) dataset. It includes more than two million traffic sign images that are based ...

In this work we developed a novel and fast traffic sign recognition system, a very important part for advanced driver assistance system and for autonomous driving. Traffic signs play a very vital role in safe driving and avoiding accident. We have used image processing and topic discovery model pLSA to tackle this challenging multiclass classification problem. Our algorithm is consist of two pa...

in recent years due to improvements of technology within automobile industry, design process of advanced driver assistance systems for collision avoidance and traffic management has been investigated in both academics and industrial levels. detection of traffic signs is an effective method to reach the mentioned aims. in this paper a new intelligent driver assistance system based on traffic sig...

The behavior of 643 pedestrians and 1749 motorists at two signal-controlled intersections was observed over a 2-mo. period of observation in March and November. One intersection had a coffin-shaped traffic sign with the wording "Fatality" erected during the first month of observation (March). The second intersection was identical in traffic and pedestrian volume but lacked a "Fatality" sign in ...

This paper reviews the popular traffic sign detection methods which are prevalent in the recent literature. The methods are divided into three categories: color-based, shapebased and learning-based. The color-based detection methods from eleven different works are studied and summarized in a table for easy reference. The three shape-based detection methods are presented, and a recent method whi...