PLANNING BICYCLE INFRASTRUCTURE BASED ON THE QUICKEST OR EASIEST ROUTE METHOD

Current bicycle models assume average speed along the route and among routes and that travel time is proportional to distance. There is no method that determines realistic cycling time based on change in speed due to topography. My research proposes a model for the development of bicycle infrastructure based on reducing travel time and level of difficulty. I identified that topography, human power, and riding speed have strong relationship and developed a bicycle travel time model where speed is a function of human power and topography. I solved the shortest route problem with time impedance where time was computed based on (1) a power model and (2) a constant speed assumption. I compared the route locations for two scenarios and proposed a location of bicycle ways based on the power model to calculate the quickest or easiest routes locations. There is no significant difference in location with very short routes (about 1 mile) or in areas with insignificant uphill slopes. However, in the areas with steep slopes the power model allows to predict more realistic travel time based on decreased speed due to topography. Test rides on actual network have shown that model produce accurate values of travel time. A power-based quickest route approach allows for more precise estimates of bicycling time that can be used for bicycle infrastructure planning, for bicycle travel demand models or as an individual trip planning tool. Consolidation of all routes into one map has shown that there are some segments of the road network that are more suitable for bicycling than others