In the last few years, traffic congestion has become a growing concern due to increasing vehicle ownerships in urban areas. Intersections are one of the major bottlenecks that contribute to urban traffic congestion. Traditional traffic signal control systems cannot adjust the timing pattern depending on road traffic demand. This results in excessive delays for road users. Adaptive traffic signa...

Overtaking a slow lead vehicle is a complex maneuver because of the variety of overtaking conditions and driver behavior. In this study, two novel prediction models for overtaking behavior are proposed. These models are derived based on multi-input multi-output adaptive neuro-fuzzy inference system (MANFIS). They are validated at microscopic level and are able to simulate and predict the fut...

Traffic information estimation and forecasting methods based on cellular floating vehicle data (CFVD) are proposed to analyze the signals (e.g., handovers (HOs), call arrivals (CAs), normal location updates (NLUs) and periodic location updates (PLUs)) from cellular networks. For traffic information estimation, analytic models are proposed to estimate the traffic flow in accordance with the amou...

TSR (Traffic sign recognition) is an important problem in ITS (intelligent traffic system), which is being paid more and more attention for realizing drivers assisting system and unmanned vehicle etc. TSR consists of two steps: detection and recognition, and this paper describe a new traffic sign detection method. The design principle of the traffic sign is comply with the visual attention mech...

Currently, vehicles use safety systems like airbags or seat belts to increase the traffic safety of passengers during traffic accidents. In the near future, most new vehicles will be equipped with other type of traffic safety applications, which could prevent vehicles from e.g., traffic accident crashing. The purpose of this paper is to provide an overview of these future traffic safety applica...

While the existing applied length-based vehicle classification model has been to estimate vehicle lengths accurately with dual-loop traffic monitoring station data under free traffic condition, it produces considerable errors against congested traffic. In this study, both ground-truth vehicle trajectory and simultaneous loop event data are used to characterize the impact of congested traffic on...

It is important to know the road traffic density real time especially in mega cities for signal control and effective traffic management. In recent years, video monitoring and surveillance systems have been widely used in traffic management. Hence, traffic density estimation and vehicle classification can be achieved using video monitoring systems. In most vehicle detection methods in the liter...

This paper presents a method for increasing fuel economy using traffic data and a model predictive controller. Using knowledge of the traffic ahead, a vehicle can react to changes in traffic density or speed before they happen, increasing the efficiency of a trip and providing valuable information to the driver. In particular, the traffic information is used to determine a time-varying velocity...

Traffic scenes in road network needs to be monitored in different dimensional perspective to address the issues generated at various time instances. One of the major challenges observed in traffic scenes in road network is to address the vehicle tracking at different dimensional perspective for various time instances. One such application that has received greater significance is the mechanism ...

As the traffic problems in urban areas are going to increase traffic surveillance systems based on video are attracted over past decades. These systems are very much useful to monitor and manage various traffic conditions such as traffic management, prevention of accident, also secure transportation .Within this vehicle speed determination on the road is one of the aim. So the vehicle speed det...