TY - JOUR
T1 - Fine-tuning time-of-day partitions for signal timing plan development
T2 - revisiting clustering approaches
AU - Chen, Peng
AU - Zheng, Nan
AU - Sun, Weili
AU - Wang, Yunpeng
PY - 2019
Y1 - 2019
N2 - Time of day (TOD) control, i.e. applying different signal timings during specified time of day to accommodate temporal traffic patterns, is widely used in the operation of most signalized intersections. In the current practice of TOD partitions, clustering approach has been a popular choice for determining TOD breakpoints given its strength in identifying dissimilarity. However, there still exists an unsolved challenge where the outliers (e.g. rare traffic flow disturbance) may lead to frequent and sometimes drastic changes of TOD plans. Such TOD control can result in unstable traffic states and inefficient operations of signal control systems. This study investigated this issue by revisiting several classical clustering approaches, i.e. K-means, hierarchical and Fisher ordinal clustering. We examined the following factors that may have large impact on the partition results of TOD, namely data collection duration, multi-day and multi-phase choices, and time-dimension in the dataset. The performances of three clustering approaches were systematically compared via an experimental study using field data collected at one intersection in Shanghai, China. This study hopes to offer practical insights through a comprehensive analysis on TOD partitions and assist traffic engineers to fine-tune signal control for signalized intersections, which would remain as a dominant and mainstream traffic control tool for the current urban road networks.
AB - Time of day (TOD) control, i.e. applying different signal timings during specified time of day to accommodate temporal traffic patterns, is widely used in the operation of most signalized intersections. In the current practice of TOD partitions, clustering approach has been a popular choice for determining TOD breakpoints given its strength in identifying dissimilarity. However, there still exists an unsolved challenge where the outliers (e.g. rare traffic flow disturbance) may lead to frequent and sometimes drastic changes of TOD plans. Such TOD control can result in unstable traffic states and inefficient operations of signal control systems. This study investigated this issue by revisiting several classical clustering approaches, i.e. K-means, hierarchical and Fisher ordinal clustering. We examined the following factors that may have large impact on the partition results of TOD, namely data collection duration, multi-day and multi-phase choices, and time-dimension in the dataset. The performances of three clustering approaches were systematically compared via an experimental study using field data collected at one intersection in Shanghai, China. This study hopes to offer practical insights through a comprehensive analysis on TOD partitions and assist traffic engineers to fine-tune signal control for signalized intersections, which would remain as a dominant and mainstream traffic control tool for the current urban road networks.
KW - clustering approach
KW - Signal control
KW - signal timing optimization
KW - simulation analysis
KW - time-of-day partition
UR - http://www.scopus.com/inward/record.url?scp=85061056093&partnerID=8YFLogxK
U2 - 10.1080/23249935.2019.1571536
DO - 10.1080/23249935.2019.1571536
M3 - Article
AN - SCOPUS:85061056093
VL - 15
SP - 1195
EP - 1213
JO - Transportmetrica A: Transport Science
JF - Transportmetrica A: Transport Science
SN - 2324-9935
IS - 2
ER -