As congestion problems are growing more severe in urban regions, problemswith delays and travel time variability are receiving more attention. Since travel time unreliability, risk for delays and the tendency to avoid driving in queues affect people's utility and their travel behaviour, it seems natural to try to include these phenomena in cost-benefit analyses. There is also a growing interest in introducing travel time variability in forecasting models, in more or less the same way ordinary costs and times are used. For both these purposes, we need methods to evaluate how differentproposed measures or investments will affect delay risks and travel time variability. Neglecting travel time variability will introduce a bias in the CBA calculations, which will most likely underestimate the utility of investments aiming to reduce urban congestion, thus in general favouring e.g. rural or inter-urban investments. Travel time variability, i.e. the random variation in travel time that is due to (among other things) unpredictable day-to-day variation in traffic volumes. We use travel time data on individual vehicles, obtained from traffic cameras. Using this data, we estimate travel time variability as a function of among other things travel time, congestion and average traffic volume. Preliminary results from this work were presented at the ETC 2005, but at that time estimation of traveltime variability as a function of different variables (such as level of congeitons) had barely begun. Since then, we have finalised estimation results, and have also applied the results. The methodology is implemented in an Emme/2 macro and is currently being applied in a cost-benefit analysis for a large outer ring road outside Stockholm. It is already apparent thatthe value of the reduction of travle time variability is substantial. Forthe covering abstract see ITRD E135582.
Samenvatting