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Data–Driven Methodology for Signal Timing Plan Development: A Computational Approach
Author(s) -
Smith Brian L.,
Scherer William T.,
Hauser Trisha A.,
Park B. Brian
Publication year - 2002
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/1467-8667.00285
Subject(s) - computer science , plan (archaeology) , signal timing , identification (biology) , set (abstract data type) , interval (graph theory) , real time computing , duration (music) , signal (programming language) , data mining , traffic signal , art , botany , mathematics , literature , archaeology , combinatorics , biology , history , programming language
Traffic signal systems serve as one of the most powerful control tools available to improve the efficiency of surface transportation travel. A large number of signal systems currently operate using the time–of–day (TOD) approach. In TOD systems, a day is segmented into a number of intervals in which a different timing plan is used. Thus, the challenge in operating a TOD system effectively is to (1) identify appropriate TOD intervals, and (2) develop optimal timing plans for each interval. The existing procedures used by traffic engineers to address these challenges are time consuming and use relatively small sets of data. This research effort developed a new timing plan development methodology that takes advantage of the large sets of archived traffic data (volume and occupancy) that modern systems are equipped to compile. Based upon statistical cluster analysis, this methodology (1) automates the identification of TOD intervals using a high–resolution definition of system state, and (2) provides representative volumes for plan optimization based on the set of archived data. The results of a case study reported in this paper demonstrate that the methodology supports the development of a TOD system that provides benefits when considering performance measures such as delay, when compared to currently used techniques.