The base scenario assumes the freeway is operating at full capacity with no traffic incidents or closures. However, the impacts of a traffic incident on freeway operations can vary depending on the severity of the incident and the extent of the resulting closure. Incidents typically cause shoulder or lane closures, as disabled vehicles block the roadway, and vehicles passing incidents tend to drive slower, reducing the capacity of the freeway segment.

Traffic incidents are generated for this analysis based on their expected frequency of occurrence on the facility within the analysis hours of a day in a given month. The incident frequency is the average number of incidents experienced on the facility and varies each month.

For scenarios with an incident, the incident details (including number of lanes impacted and incident duration) are modeled using a normal probability distribution.

Table 15-6

provides parameters for normal distributions of the impacts an incident may have, depending on the severity of the resulting closure. These parameters are used to randomly generate and assign the characteristics of an incident to use for an analysis scenario.

Table 15-7

displays the CAFs associated with each incident severity type, and these factors are applied based on the incident with characteristics generated from the parameters shown in

Table 15-6

. For example, if an analysis segment has a 50 percent chance of experiencing an incident, then for half of the scenarios generated for a month, each scenario is modeled with a unique incident.

The incident severity and duration parameters are randomly generated from the normal distribution referenced in

Table 15-6

. Additionally,

Table 15-7

shows that a three-lane closure incident on a four-lane directional facility results in a loss of three full-lane capacities and maintaining only 52 percent of the capacity in the remaining lane. The CAFs in

Table 15-7

are applied to each scenario for that scenario’s randomly generated incident duration and according to that scenario’s randomly generated incident severity. The CAFs are applied to the capacity results to determine the impacts of incidents on roadway capacity based on the scenario being analyzed.