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  • Smith, Brian L.  (2)
  • Mobility and traffic research  (2)
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  • Mobility and traffic research  (2)
  • 1
    Online Resource
    Online Resource
    SAGE Publications ; 2002
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 1804, No. 1 ( 2002-01), p. 162-167
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 1804, No. 1 ( 2002-01), p. 162-167
    Abstract: 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.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2002
    detail.hit.zdb_id: 2403378-9
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    SAGE Publications ; 2014
    In:  Transportation Research Record: Journal of the Transportation Research Board Vol. 2470, No. 1 ( 2014-01), p. 113-121
    In: Transportation Research Record: Journal of the Transportation Research Board, SAGE Publications, Vol. 2470, No. 1 ( 2014-01), p. 113-121
    Abstract: Highway congestion continues to be a major problem in urban transportation, and the search for feasible mitigation measures continues to evolve with the advancement in technology and a better understanding of traveler behavior. Integrated corridor management (ICM) has recently emerged as a potential mitigation measure; however, for this potential to be fully harnessed, research into the ways to identify ICM strategies that best fit the particular circumstances of a transportation corridor is necessary. This study proposed an ICM evaluation framework that was based on which strategies critical to congestion mitigation in a corridor could be identified. The proposed evaluation framework was demonstrated by using the I-95–I-395 ICM corridor in northern Virginia, where the effectiveness of selected ICM strategies was tested under both incident and nonincident conditions through a microscopic simulation model. An analysis of the simulation results identified variable speed limits, an increase in transit and parking capacities, high-occupancy vehicle–high-occupancy vehicle bypass lanes, and high-occupancy toll lanes as the most beneficial ICM strategies for both incident and nonincident traffic conditions. However, the benefits of ICM determined through the strategies modeled were confirmed to be more significant under incident conditions than nonincident conditions. As a result of the ICM strategies implemented, an average flow increment in the corridor of 6,860 persons per hour (+ 37.8%) was experienced during incident conditions compared with 3,286 persons per hour (+ 14.4%) for nonincident conditions. Improvements were also observed in average travel times and vehicle emissions.
    Type of Medium: Online Resource
    ISSN: 0361-1981 , 2169-4052
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2014
    detail.hit.zdb_id: 2403378-9
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
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