A.E. Kitali, P. Alluri, T. Sando
Accurate estimation of the primary incident spatiotemporal impact area is essential and imperative for mitigating secondary crashes. This study used prevailing traffic data to automatically estimate the primary incidents’ impact area and identify secondary crashes within the affected area—the proposed approach considered how the queue caused by the incident grows and dissipates upstream of the incident. The effectiveness of the proposed approach was compared with the approach that assumed the incident’s impact along all the impacted segments is the same, referred to as the base approach. Most secondary crashes occurred under congested traffic conditions. Incidents with severe impacts on traffic were the primary contributors to secondary crashes. The base approach identified 54% more secondary crashes than the improved approach. These additional crashes were found to occur mostly under less traffic congestion. Although the improved approach identified fewer secondary crashes, it is more precise because it considers segment-based traffic conditions. The developed method more accurately identifies secondary crashes since it better reflects the changes in traffic characteristics caused by the primary incident.
Keywords: real-time traffic data; prevailing traffic conditions; incident spatiotemporal impact area; secondary crashes