Are Incident Durations and Secondary Incidents Interdependent?
Asad Jan Khattak, Xin Wang, Hongbing Zhang
Abstract
Asad Jan Khattak, Xin Wang, Hongbing Zhang
Abstract
Incidents impose substantial social and personal costs on drivers. Some of the larger incidents that cause delays are also associated with secondary incidents. However, the nature of interdependence between primary and secondary incidents is not fully known. The objective of this study is to understand how primary incident duration and secondary incident occurrence are related. Specifically, secondary incidents are more likely to occur if the primary incident lasts a long time; at the same time, the durations of primary incidents are expected to be longer if secondary incidents occur. After traffic incident and road inventory data in the Hampton Roads, Virginia, area were obtained, secondary incidents were then identified. Secondary incidents were defined as incidents occurring on the same roadway segment (which average 1 mi in length) as the primary incident and within the actual duration of the primary incident. If the primary incident blocked lanes, then the actual duration plus 15 min was used as the threshold. Models for primary incident durations and whether a secondary incident occurs are estimated. The interdependence is modeled by considering incident duration as endogenous in the secondary incident occurrence models. Results show statistical evidence for interdependence, but when it is taken into account, no substantial differences in the magnitudes and statistical significance for the estimated independent variables are found (compared with when the interdependence is not accounted for). Statistically significant correlations found between secondary incident occurrence and other variables allow the recommendation of specific operational strategies.
OpenAlex reports 84 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Incidents impose substantial social and personal costs on drivers. Some of the larger incidents that cause delays are also associated with secondary incidents. However, the nature of interdependence between primary and secondary incidents is not fully known. The objective of this study is to understand how primary incident duration and secondary incident occurrence are related. Specifically, secondary incidents are more likely to occur if the primary incident lasts a long time; at the same time, the durations of primary incidents are expected to be longer if secondary incidents occur. After traffic incident and road inventory data in the Hampton Roads, Virginia, area were obtained, secondary incidents were then identified. Secondary incidents were defined as incidents occurring on the same roadway segment (which average 1 mi in length) as the primary incident and within the actual duration of the primary incident. If the primary incident blocked lanes, then the actual duration plus 15 min was used as the threshold. Models for primary incident durations and whether a secondary incident occurs are estimated. The interdependence is modeled by considering incident duration as endogenous in the secondary incident occurrence models. Results show statistical evidence for interdependence, but when it is taken into account, no substantial differences in the magnitudes and statistical significance for the estimated independent variables are found (compared with when the interdependence is not accounted for). Statistically significant correlations found between secondary incident occurrence and other variables allow the recommendation of specific operational strategies.
Key concepts: Incident report, Duration (music), Incident management, Primary (astronomy), Statistics, Engineering, Mathematics, Computer science