Risk assessment and route optimization for life and health self-keeping during e-cycling

The paper presents the creation of a general mathematical model of a two-step optimization problem which finds the most-safer route of an electric-bicycle cyclist. The first step is a multi-criteria problem which finds the average risk in the different segments which forms the complete route. To solve the problem, a scalarization method is used (also known as weighted sum method). In the second step, the safer route is found by applying a network optimization model. To find the solution a method for dynamic optimization is applied (Bellman’s Principle). The generation of data is based on the a priori known information as well as on information which is periodic and stochastic in the time and space.