Automatic calculation of bicycle routes by combining meta-heuristics and GIS techniques within the framework of smart cities

The automation of a city's underlying dynamic system analysis is one of the most important tasks in a Smart City. A route selection system to avoid traffic congestion in which cycle tracks are integrated parts of the traffic design is an example of such a dynamic system. Ongoing traffic analysis is of vital importance for environmental and tourist reasons. Until recently, traffic data was analyzed by experts; today the huge amount of data gathered through the use of city sensors and other devices makes this a boundless analysis for the human brain. In this paper we propose a novel method to find a cycle route in an automatic way by making use of the vast traffic and environmental information gathered in a small area of Santander. We construct our model by using a combination of Soft Computing and GIS techniques. Then, we solve the resulting multi-objective NP-hard problem with a population-based bio-inspired meta-heuristics. Some experimental results show that our approach performs very well and that the presented methodology is promising for further application in other real scenarios, even for cases in which difficult additional constraints might be considered.