Time Series Analysis and Models of Freeway Performance

• Published in: Journal of transportation engineering 2012-08, Vol.138 (8), p.1030-1039
• Main Authors: Ossenbruggen, Paul J, Laflamme, Eric M
• Format: Article
• Language: English
• Subjects: Applied sciences; Buildings. Public works; Congestion; Exact sciences and technology; Freeways; Ground, air and sea transportation, marine construction; Mathematical models; Parameter estimation; Road transportation and traffic; Road types (roads, freeways, express ways, etc.); Roads & highways; Technical Papers; Time series; Time series analysis; Traffic congestion; Traffic flow; Traffic models; Transportation infrastructure; Transportation models
• ISSN: 0733-947X; 1943-5436
• DOI: 10.1061/(ASCE)TE.1943-5436.0000403

AbstractThis paper describes a study whose primary purpose is to better understand the relationship between freeway traffic flow and speed. Incidents of recurrent and nonrecurrent congestion were encountered at six radar collection northbound locations on New Hampshire interstate I-93 in July 2010. The root cause for the onset of the recurrent congestion is explained with exploratory data analyses and a time series modeling approach. A complex combination of present and past values of traffic flow, speed, and congestion state, a congestion history of lingering effect variables, can explain the triggering and mitigation of congestion events for a highly volatile traffic environment. The approach includes two mathematical models: (1) a generalized additive binomial model to forecast the probability of congestion and (2) state-space models of speed and flow. The state-space models use a dynamic linear model (DLM) with switching structures to describe the bimodal distribution of speed and flow in the free-flow and congested states. Model selection, parameter estimation and checking are presented.