“Guidance on Quantifying Benefits of Traffic Incident Management Strategies (NCHRP 03-108) “
Final report not published yet!!
We sifted through nearly 5 million incident records and data from hundreds of traffic monitoring stations in multiple states (including Maryland, Virginia, Texas, Florida, California, and Washington) to identify those incidents that resulted in capacity loss. The data is archived in the Regional Integrated Transportation Information System (RITIS). A novel speed-based bottleneck identification algorithm is proposed. Besides, to estimate capacity, cumulative counts at the upstream of the incident site is used in conjunction with a piecewise-linear fitting algorithm. Capacity estimates under different incident scenarios are compared and contrasted with default values reported in the 2010 Highway Capacity Manual (HCM). Further analysis is performed (using real-world traffic data and existing models) to quantify mobility and safety benefits of implementing TIM strategies.
TABLE 1. Estimated Proportion of Freeway Segment Capacity Available Under Incident Conditions.
Number of Lanes (One Direction) | Shoulder Disablement |
Shoulder Accident |
One Lane Blocked | Two Lanes Blocked | Three Lanes Blocked |
2 | N/A | ||||
3 | 0.79*** (0.03) | 0.76* (0.04) | 0.55** (0.08) | 0.24*** (0.07) | |
4 | 0.91*** (0.04) | 0.87 (0.06) | 0.69** (0.06) | 0.30*** (0.07) | 0.18*** (0.08) |
5 | 0.76** (0.07) | 0.60*** (0.09) | 0.32 (0.22) | ||
6 | |||||
7 |