Imperial College London


Faculty of EngineeringDepartment of Electrical and Electronic Engineering




+44 (0)20 7594 6275j.barria Website




1012Electrical EngineeringSouth Kensington Campus






BibTex format

author = {Thajchayapong, S and Barria, JA},
title = {Anomaly Detection using Microscopic TrafficVariables on Freeway Segments},
url = {},
year = {2010}

RIS format (EndNote, RefMan)

AB - This paper proposes and assesses the effectiveness of monitoring vehicular traffic anomalies usingmicroscopic traffic variables, namely relative speed and inter-vehicle spacing. We present analgorithm that detects transient changes in traffic patterns using microscopic traffic variables. Inparticular, we show that when applied to real-world scenarios, our algorithm can use the varianceof statistics of relative speed to detect traffic anomalies and precursors to non-recurring traffic congestion.The performance of the proposed algorithm is also assessed using a microscopic trafficsimulation environment, where we show that with minimum prior knowledge, the proposed algorithmhas comparable performance to an ideally placed loop detector monitoring the standarddeviation of speed. The algorithm also performs very well even when the microscopic traffic variablesare available only from a fraction of the complete population of vehicles.
AU - Thajchayapong,S
AU - Barria,JA
PY - 2010///
TI - Anomaly Detection using Microscopic TrafficVariables on Freeway Segments
UR -
UR -
ER -