Bicycle is one of the most environmentally friendly means of transportation. How can we support cyclists and make their trips more enjoyable, healthy and safe?
This challenge consists in identifying factors that make a bike route attractive and developing a prototype estimating these factors to facilitate bike route planning and navigation.
The fastest route might not be the most attractive for a cyclist. Traffic, noise, air pollution, dangerous situations, ugly architecture, crime, bad weather might be significant factors for avoiding a route. At the same time, scenic views, green areas, lakes and rivers, cafes and restaurants, beautiful neighbourhoods might make a bike ride more enjoyable.
The first navigation prototype meinGrün generating pleasant routes and focusing on the greenness, sociability, and quietness factors was developed by the Heidelberg University’s GIScience Research Group and will be tested soon. The prototype is based on the Open Source routing system OpenRouteService.org using OpenStreetMap data.
Often, the required data is not directly available, but has to be approximated. For example, for estimating the noise level meinGrün uses categories of streets and the number of lanes. The sentiment analysis of Twitter and Flickr data helps to find pleasant locations.
In this challenge, identify attractiveness factors for cyclists. Develop a prototype solution to estimate these factors for a given route using any available data. Successful solutions can be then integrated into the meinGrün service.