Name
Abstract | ||
|---|---|---|
GPS navigators are now present in most vehicles and smartphones. The usual goal of these navigators is to take the user in less time or distance to a destination. However, the global use of navigators in a given city could lead to traffic jams as they have a highly biased preference for some streets. From a general point of view, spreading the traffic throughout the city could be a way of preventing jams and making a better use of public resources. We propose a way of calculating alternative routes to be assigned by these devices in order to foster a better use of the streets. Our experimentation involves maps from OpenStreetMap, real road traffic, and the microsimulator SUMO. We contribute to reducing travel times, greenhouse gas emissions, and fuel consumption. To analyze the sociological aspect of any innovation, we analyze the penetration (acceptance) rate which shows that our proposal is competitive even when just 10% of the drivers are using it. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3071178.3071193 | GECCO |
Keywords | Field | DocType |
Application, evolutionary algorithm, road traffic, smart city, real world, smart mobility | Evolutionary algorithm,Simulation,Computer science,Transport engineering,Road traffic,Artificial intelligence,Global Positioning System,Smart city,Fuel efficiency,Machine learning,Greenhouse gas | Conference |
Citations | PageRank | References |
1 | 0.35 | 3 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel H. Stolfi | 1 | 24 | 7.24 |
| Enrique Alba | 2 | 3796 | 242.34 |