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Implementation and Evaluation of Weather Responsive Traffic Estimation and Prediction System
Implementation and Evaluation of Weather Responsive Traffic Estimation and Prediction System
Knygos.lt klubas Knygos.lt nariams
28,41 €
-30%
Įprastai
40,59 €
  • Išsiųsime per 12–18 d.d.
The objective of the project is to develop a framework and procedures for implementing and evaluating weather-responsive traffic management (WRTM) strategies using Traffic Estimation and Prediction System (TrEPS) methodologies. In a previous FHWA funded project, a methodology was developed and tested for incorporating weather impacts in off-line TrEPS. This capability is now included in on-line TrEPS, which interacts with multiple sources of local real-time information, to provide operators wit…

Implementation and Evaluation of Weather Responsive Traffic Estimation and Prediction System (el. knyga) (skaityta knyga) | knygos.lt

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The objective of the project is to develop a framework and procedures for implementing and evaluating weather-responsive traffic management (WRTM) strategies using Traffic Estimation and Prediction System (TrEPS) methodologies. In a previous FHWA funded project, a methodology was developed and tested for incorporating weather impacts in off-line TrEPS. This capability is now included in on-line TrEPS, which interacts with multiple sources of local real-time information, to provide operators with predicted traffic states under the current and future weather conditions. The main goal is to support the decision making process for addressing the disruptive effect of inclement weather on the traffic system.

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The objective of the project is to develop a framework and procedures for implementing and evaluating weather-responsive traffic management (WRTM) strategies using Traffic Estimation and Prediction System (TrEPS) methodologies. In a previous FHWA funded project, a methodology was developed and tested for incorporating weather impacts in off-line TrEPS. This capability is now included in on-line TrEPS, which interacts with multiple sources of local real-time information, to provide operators with predicted traffic states under the current and future weather conditions. The main goal is to support the decision making process for addressing the disruptive effect of inclement weather on the traffic system.

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