Traffic flow on an urban road network is temporal in nature. Knowledge of within-day traffic flow variation is important for evaluatingalternative measures oftraffic flow improvement on urbantransportation network. Traditionally, a within-day traffic flow variation is classified as peak and off-peak periods, and is typically interpreted from graphical representation of the traffic flow patterns. But,in case of an urban form, where land-use development of various opportunities is quiet spatially varied, the peak and off-peak periods of traffic flow are not found well-defined in variation profile. In such case, a more scientific approach is required to identifythese time periods. In the present work, an attempt has been taken to classify the within-day variation in traffic flow by considering inherent temporally continuous nature of traffic flow data. The classification has been carried out using K-means clustering technique. The work has been demonstrated by considering the multi-modal urban transportation network of Bhubaneswar city, India.
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Type
General Knowledge
Author
Sai Kiran Annam, Bhargab Maitra and Debasis Basu
Organization
Indian Institute of Technology
Published in
2017
Submitted by
IRF
Related theme(s)
General, Urban Mobility
Region
All Regions
Country
India