O.R. Applications A sequential detection approach to real-time freeway incident detection and characterization Jiuh-Biing Sheu * Institute of Traffic and Transportation, National Chiao Tung University, 4F, 114 Chung Hsiao W. Rd., Sec. 1, Taipei, 10012 Taiwan, ROC Received 27 June 2002; accepted 12 February 2003 Abstract In this paper, a new methodology is presented for real-time detection and characterization of freeway incidents. The proposed technology is capable of detecting freeway incidents in real time as well as characterizing incidents in terms of time-varying lane-changing fractions and queue lengths in blocked lanes, the lanes blocked due to incidents, and du- ration of incident, etc. The architecture of the proposed incident detection approach consists of three sequential pro- cedures: (1) symptom identification for identification of anomalous changes in traffic characteristics probably caused by incidents, (2) signal processing for stochastic estimation of incident-related lane traffic characteristics, and (3) pattern recognition for incident detection. Lane traffic count and occupancy are two major types of input data, which can be readily collected from point detectors. The primary techniques utilized to develop the proposed method include: (1) discrete-time, nonlinear, stochastic system modeling used in the signal processing procedure, and (2) modified se- quential probability ratio tests employed in the pattern recognition procedure. Off-line tests were conducted to sub- stantiate the performance of the proposed incident detection algorithm based on simulated data generated employing the calibrated INTRAS simulation model and on real incident data collected on the I-880 freeway in Oakland, Cali- fornia. The test results indicate the feasibility of achieving real-time incident detection and characterization utilizing the proposed method. Ó 2003 Elsevier B.V. All rights reserved. Keywords: Transportation; Markov–Gaussian processes; Discrete-time nonlinear stochastic system; Real-time incident detection 1. Introduction Real-time freeway incident detection and char- acterization is an important function for freeway traffic management in urban areas. Studies have shown that 60% of the urban freeway delay may be caused by freeway incidents (Lindley, 1987). This may increase approximately to 70% by year 2005. Incidents on freeways interrupt traffic flows unex- pectedly, and thus, they can be the major cause of such unusual events as bottlenecks and secondary accidents. It has been suggested that the risk of secondary accidents can be significantly reduced by earlier detection and warning (Busch, 1991). Clearly, earlier detection and warning are two important factors in decreasing the impact of * Tel.: +886-2-2349-4963; fax: +886-2-2349-4953. E-mail address: jbsheu@mail.nctu.edu.tw (J.-B. Sheu). 0377-2217/$ - see front matter Ó 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0377-2217(03)00209-1 European Journal of Operational Research 157 (2004) 471–485 www.elsevier.com/locate/dsw