2001•IEEE SpectrumRequires access

Forecasting traffic flow

W.D. Jones

Open publisher page 18 citations

Abstract

Predicting what traffic would be like along a particular route an hour into the future is the ambition motivating the design of intelligent transportation systems (ITS). ITS is an infrastructure being developed-along highways and city streets, and in cars and trucks-that can use information about traffic to speed up travel and make it safer. Several research groups have begun generating reliable information about what will occur on a road using predictive traffic modeling. The status of a stretch of road-based on a number of variables measured by devices such as loop detectors embedded in the roadway and digital image acquisition and processing systems-is compared to a group of days when similar events occurred. One way of aiding traffic prediction and management is to track mobile phones which many drivers have in their cars. The tracking data would come from mobile phones equipped with global positioning system receivers or through triangulation from nearby cell base station towers. This method will cost only a fraction of the cost of buried loop detectors.

About this research paper

What this paper is about

Predicting what traffic would be like along a particular route an hour into the future is the ambition motivating the design of intelligent transportation systems (ITS). ITS is an infrastructure being developed-along highways and city streets, and in cars and trucks-that can use information about traffic to speed up travel and make it safer. Several research groups have begun generating reliable information about what will occur on a road using predictive traffic modeling. The status of a stretch of road-based on a number of variables measured by devices such as loop detectors embedded in the roadway and digital image acquisition and processing systems-is compared to a group of days when similar events occurred. One way of aiding traffic prediction and management is to track mobile phones which many drivers have in their cars. The tracking data would come from mobile phones equipped with global positioning system receivers or through triangulation from nearby cell base station towers. This method will cost only a fraction of the cost of buried loop detectors.

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OpenAlex reports 18 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Predicting what traffic would be like along a particular route an hour into the future is the ambition motivating the design of intelligent transportation systems (ITS). ITS is an infrastructure being developed-along highways and city streets, and in cars and trucks-that can use information about traffic to speed up travel and make it safer. Several research groups have begun generating reliable information about what will occur on a road using predictive traffic modeling. The status of a stretch of road-based on a number of variables measured by devices such as loop detectors embedded in the roadway and digital image acquisition and processing systems-is compared to a group of days when similar events occurred. One way of aiding traffic prediction and management is to track mobile phones which many drivers have in their cars. The tracking data would come from mobile phones equipped with global positioning system receivers or through triangulation from nearby cell base station towers. This method will cost only a fraction of the cost of buried loop detectors.

Key concepts: SAFER, Traffic flow (computer networking), Computer science, Floating car data, Real-time computing, Track (disk drive), Truck, Triangulation

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