Floating Car Data (FCD) is becoming a more and more popular technique for travel time measurements in road networks. Nevertheless, FCD is a sampling technique which requires controlling the statistical properties of link travel times to obtain accurate estimations. Based on microsimulation outputs, this paper shows which parameters play a key role in the travel time estimation accuracy, particularly in the case of urban networks. Among them, aggregation period and link definition are the most critical ones. They must be properly chosen according to the equipped vehicles ratio
The application domain of intelligent transportation is plagued by a shortage of data sources that a...
This paper presents a methodology for estimation of average travel time on signalized urban networks...
Real time data collection in traffic engineering is crucial for better traffic corridor control and ...
Floating Car Data (FCD) is becoming a more and more popular technique for travel time measurements i...
AbstractThe availability of floating car data (FCD) enables operators to use novel methods in travel...
Floating car data (FCD) meanwhile is a widely available and affordable data source. The given GPS da...
This project explores the use of machine learning techniques to accurately predict travel times in c...
Floating car data (FCD) meanwhile is a widely available and affordable data source. The given GPS da...
Travel times in urban road networks are highly stochastic. However, most existing travel time estima...
AbstractMany metropolitan cities are facing the problem of traffic congestion in large scale and hig...
The paper describes a couple of FCD based vehicular traffic applications and services. This new meth...
Abstract — Floating Car Data (FCD) fleets are a valuable data source to obtain travel times as basis...
The use of GPS probes in traffic management is growing rapidly as the required data collection infra...
AbstractTraffic management centers take advantage of various data collection systems ranging from st...
A model for average travel time estimation on signalized urban networks by integrating cumulative pl...
The application domain of intelligent transportation is plagued by a shortage of data sources that a...
This paper presents a methodology for estimation of average travel time on signalized urban networks...
Real time data collection in traffic engineering is crucial for better traffic corridor control and ...
Floating Car Data (FCD) is becoming a more and more popular technique for travel time measurements i...
AbstractThe availability of floating car data (FCD) enables operators to use novel methods in travel...
Floating car data (FCD) meanwhile is a widely available and affordable data source. The given GPS da...
This project explores the use of machine learning techniques to accurately predict travel times in c...
Floating car data (FCD) meanwhile is a widely available and affordable data source. The given GPS da...
Travel times in urban road networks are highly stochastic. However, most existing travel time estima...
AbstractMany metropolitan cities are facing the problem of traffic congestion in large scale and hig...
The paper describes a couple of FCD based vehicular traffic applications and services. This new meth...
Abstract — Floating Car Data (FCD) fleets are a valuable data source to obtain travel times as basis...
The use of GPS probes in traffic management is growing rapidly as the required data collection infra...
AbstractTraffic management centers take advantage of various data collection systems ranging from st...
A model for average travel time estimation on signalized urban networks by integrating cumulative pl...
The application domain of intelligent transportation is plagued by a shortage of data sources that a...
This paper presents a methodology for estimation of average travel time on signalized urban networks...
Real time data collection in traffic engineering is crucial for better traffic corridor control and ...