Advanced traffic control systems, such as traffic signal systems, include large numbers of sensors intended to support the monitoring of traffic conditions. In addition, transportation agencies frequently archive data collected by these detectors, on the assumption that important information can be extracted from the archives with the proper tools. The development of a data mining tool intended to support the maintenance of traffic signal systems that operate in the time-of-day (TOD) mode by identifying when traffic conditions have changed significantly in a corridor is described. The data mining approach used is classification. A case study was conducted to demonstrate that accurate classification models can be developed by using archived data to map between a set of traffic conditions and the associated TOD interval or timing plan for which the conditions are best suited. The 92.4% classification rate achieved in the case study indicates that this data mining tool has the potential to effectively support TOD signal operations.
Prototype Classification Tool for Supporting Maintenance of Traffic Signal Timing Plans
Transportation Research Record
Transportation Research Record: Journal of the Transportation Research Board ; 1804 , 1 ; 162-167
2002-01-01
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Prototype Classification Tool for Supporting Maintenance of Traffic Signal Timing Plans
British Library Conference Proceedings | 2002
|Prototype Classification Tool for Supporting Maintenance of Traffic Signal Timing Plans
Online Contents | 2002
|Generating More Equitable Traffic Signal Timing Plans
Transportation Research Record | 2010
|Generating More Equitable Traffic Signal Timing Plans
Online Contents | 2010
|DERIVING TRAFFIC SIGNAL TIMING PLANS FROM CONNECTED VEHICLE TRAJECTORY DATA
Europäisches Patentamt | 2021
|