A methodology to identify critical road sections by means of cyclist’s fatigue

This paper proposes a procedure for determining cyclists’ fatigue state along a specific road, as a function of some external variables related to the environmental context. When the physical fatigue reaches extreme levels, the cyclist’s ability to deal with an unexpected event or with an emergency condition is particularly limited; further, poor road pavement conditions may increase occurrence probability of critical events. In order to identify the potentially most dangerous road paths, the authors defined a methodology to build a model for cyclist’s fatigue evaluation in terms of Heart Rate class. The proposed procedure is based on the collection of simple data processed by means of Pattern Recognition techniques. The main result is to identify road segments causing a relevant fatigue state in cyclists and, thus, more risks for their safety. In the most critical spots, the road managers might mitigate risk for cyclists by means of specific actions, such as proper pavement maintenance, side-element renovation, separation from vehicular traffic, etc. The first results are very interesting, as proved by the low errors (less than 8%) obtained from the model. These outcomes may be used by road administrators for identifying potentially hazardous road sections and increasing the attention on cyclists with appropriate maintenance interventions that can reduce their safety risks.