An expert judgment model applied to estimating the safety effect of a bicycle facility

This paper presents a risk index model that can be used for assessing the s afety effect of countermeasures. The model estimates risk in a multiplicati ve way, which makes it possible to analyze the impact of different factors separately. Expert judgments are incorporated through a Bayesian error mode l. The variance of the risk estimate is determined by Monte-Carlo simulatio n. The model was applied to assess the safety effect of a new design of a b icycle crossing. The intent was to gain safety by raising the crossings to reduce vehicle speeds and by making the crossings more visible by painting them in a bright color. Before the implementations, bicyclists were riding on bicycle crossings of conventional Swedish type, i.e. similar to crosswal ks but delineated by white squares rather than solid lines or zebra marking s. Automobile speeds were reduced as anticipated. However, it seems as if t he positive effect of this was more or less canceled out by increased bicyc le speeds. The safety per bicyclist was still improved by approximately 20% . This improvement was primarily caused by an increase in bicycle flow, sin ce the data show that more bicyclists at a given location seem to benefit t heir safety. The increase in bicycle flow was probably caused by the new la yout of the crossings since bicyclists perceived them as safer and causing less delay. Some future development work is suggested. Pros and cons with t he used methodology are discussed. The most crucial parameter to be added i s probably a model describing the interaction between motorists and bicycli sts, for example, how risk is influenced by the lateral position of the bic yclist in relation to the motorist. It is concluded that the interaction se ems to be optimal when both groups share the roadway. (C) 2000 Elsevier Sci ence Ltd. All rights reserved.