In this paper, a stochastic approach for freeway performance estimation is presented. The macroscopic model delivers performance indicators like the sum of delays, the delay per driver, the total duration of congestion and the percentage of trips under congested flow conditions. The methodologyis based on a comparison of estimated annual patterns of traffic demand and capacity within a Monte Carlo simulation. The performance indicators are calculated based on a queuing model. The estimation of demand patterns considers both periodic and random components of traffic demand. The estimation of capacity patterns is based on distribution functions that represent freeway capacity for specific roadway, traffic, and control conditions. Variable influences like weather conditions and the share of heavy vehicles are considered by varying the parameters of the capacity distribution function. The whole concept is applied to frequently congested freeway sections in Germany. Based on the estimation results, the empirical relationship between different performance indicators is analyzed. The findings are used to derive appropriate target indicator values for freeway traffic management. For the covering abstract see ITRD E139491.
Samenvatting