Daniel B. Fambro Student Paper Award: A Stochastic Delay Prediction Model for Real-Time Incident Management

摘要

In the Institute of Transportation Engineers' 2007 Daniel B. Fambro Student Paper, the authors demonstrate that failing to account for the uncertainty that exists in predicting incident severity consistently and systematically underestimates the impact of incidents, potentially to a large enough degree that faulty incident management decisions are made. (Simulation results indicate underestimation on the order of 20 to 50 percent.) The authors develop a new delay prediction model that explicitly provides predictions in the context of uncertain incident duration and eliminates this source of error. Analytical incident delay formulae are extended to account for uncertain incident duration, and simulation with Monte Carlo sampling is undertaken to study scenarios that are too complicated fir exact analysis. These indicate that different demand profiles also play a large role in determining the impact of an incident and should be taken into account in any delay prediction model applied in practice.