AbstractTraffic management centers take advantage of various data collection systems ranging from stationary sensors e.g. automated vehicle identification systems to mobile sensors e.g. fleet management systems. Each type of data collection system has its own advantages and disadvantages. Stationary sensors has less measurement noise than mobile sensors but their network coverage is limited. On the other hand, mobile sensors cover expand areas of road networks but they have less penetration rate and frequency of reports. Traffic state estimation can benefit from fusion of data from various sources as they complement each other. This paper introduces a route travel time estimation method that aggregates data from two traffic data sources, au...
This paper studies the joint reconstruction of traffic speeds and travel times by fusing sparse sens...
AbstractThere is an increasing availability of floating car data both historic, in the form of traje...
This monograph presents a simple, innovative approach for the measurement and short-term prediction ...
AbstractTraffic management centers take advantage of various data collection systems ranging from st...
The use of GPS probes in traffic management is growing rapidly as the required data collection infra...
Estimated travel time is a key input for many intelligent transport systems (ITS) applications and t...
Floating Car Data (FCD) is becoming a more and more popular technique for travel time measurements i...
Traditional traffic monitoring systems are mostly based on road side equipment (RSE) measuring traff...
This project explores the use of machine learning techniques to accurately predict travel times in c...
Floating Car Data (FCD) is becoming a more and more popular technique for travel time measurements i...
<div><p>On urban arterials, travel time estimation is challenging especially from various data sourc...
The importance of travel time estimation has increased due to the central role it plays in a number ...
The paper describes a couple of FCD based vehicular traffic applications and services. This new meth...
Existing methods of estimating travel time from GPS data are not able to simultaneously take account...
Underlying all attempts to manage urban traffic congestion is the need for a comprehensive knowledge...
This paper studies the joint reconstruction of traffic speeds and travel times by fusing sparse sens...
AbstractThere is an increasing availability of floating car data both historic, in the form of traje...
This monograph presents a simple, innovative approach for the measurement and short-term prediction ...
AbstractTraffic management centers take advantage of various data collection systems ranging from st...
The use of GPS probes in traffic management is growing rapidly as the required data collection infra...
Estimated travel time is a key input for many intelligent transport systems (ITS) applications and t...
Floating Car Data (FCD) is becoming a more and more popular technique for travel time measurements i...
Traditional traffic monitoring systems are mostly based on road side equipment (RSE) measuring traff...
This project explores the use of machine learning techniques to accurately predict travel times in c...
Floating Car Data (FCD) is becoming a more and more popular technique for travel time measurements i...
<div><p>On urban arterials, travel time estimation is challenging especially from various data sourc...
The importance of travel time estimation has increased due to the central role it plays in a number ...
The paper describes a couple of FCD based vehicular traffic applications and services. This new meth...
Existing methods of estimating travel time from GPS data are not able to simultaneously take account...
Underlying all attempts to manage urban traffic congestion is the need for a comprehensive knowledge...
This paper studies the joint reconstruction of traffic speeds and travel times by fusing sparse sens...
AbstractThere is an increasing availability of floating car data both historic, in the form of traje...
This monograph presents a simple, innovative approach for the measurement and short-term prediction ...