This paper describes the remote automatic incident detection algorithm designed to detect abnormal periods of traffic congestion existing over single inductive loop detectors (typically 2 3 1.5 m). This algorithm identifies those detectors which show a critical increase in average loop-occupancy time per vehicle coinciding with a critical decrease in average time-gap between vehicles according to a set of rules previously defined by the operator. The rules define the maximum and minimum values of loop occupancy and time gap respectively for each detector, which when exceeded for a given duration, trigger a report of a potential traffic flow ‘abnormality’ for that time of day at that particular location on the network. Initial rules are developed by studying the 85th percentile values of loop occupancy returned by the urban traffic control system every 30 s. A real-time trial took place between 07:00 and 19:00 over 167 consecutive days involving 74 detectors situated along two sections of the A33 Bassett Avenue and A35 Winchester Road in Southampton. Over this period, 181and 334 triggers were recorded on the A33 and A35, respectively. An independent operator log showed that over the same period, 32 incidents were recorded on the A33 and 49 on the A35. The remote automatic incident detection system detected 69% and 92% of the verified incidents on the A33 and A35, respectively; the low detection rate on the A33 being mainly due to five incidents which occurred during off-peak periods causing no congestion and were therefore not detected
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