Traffic incidents have negative impacts on traffic flow and the gross domestic product of most
countries. In addition, they may result in fatalities and injuries. Thus, efficient incident …

This paper presents the applications of a recently developed pattern classifier called support
vector machine (SVM) in incident detection. Support vector machine is constructed from a …

Traffic incidents are nonrecurrent and pseudorandom events that disrupt the normal flow of
traffic and create a bottleneck in the road network. The probability of incidents is higher …

To eliminate false alarms, an effective traffic incident detection algorithm must be able to
extract incident‐related features from the traffic patterns. A robust feature‐extraction …

Incident detection is fundamental for freeway management to reduce non-recurrent
congestions and secondary incidents. Recently, machine learning technologies have made …

This paper presents an application of the wavelet technique to freeway incident detection
because wavelet techniques have demonstrated superior performance in detecting changes …

The structure and performance of existing freeway incident detection methods are reviewed
and a new method is proposed. The new method reduces the likelihood of false incident …

This paper presents a wavelet-based novel freeway automated incident detection algorithm
with varying threshold parameters considering the level of traffic flow. In this approach, new …

Detecting incidents on urban streets or arterials using loop detector data is quite
challenging. The pattern of the incident could be quite similar to non-incident cases as …

To date, efforts to manage freeway congestion have been seriously impeded by the inability
to promptly and reliably detect the presence of traffic incidents. Traditional incident-detection …