Impact of Navigation Systems on Urban Sustainability
Study of emergent collective phenomena at metropolitan level in personal navigation assistance systems with different recommendation policies, with respect to different collective optimization criteria, such as traffic load balance, safety risks and environmental sustainability.
Satellite Navigation systems like TomTom, Google Maps and OpenStreetMap-based services are pervasively used in our cities to facilitate and speed up reaching the desired destination. They are typically optimized to minimize an individual driver's travel time without considering their impact on traffic, whether a street can absorb the traffic, or if some routes compromise drivers' safety.
When dealing with socio-technical systems, the aggregation of selfish optimal individual suggestions may negatively impact the collective level, worsening the wellness of society as a whole and leading to discomfort, particularly when individuals share a resource with a limited capacity, as in the case of road networks.
For instance, if the navigation system recommends all vehicles to travel on the same road to reach a destination, congestion may emerge on that road.
The adverse traffic effects unintentionally exacerbated by navigation systems can impact the environment. Indeed, vehicular traffic represents a critical hazard to urban sustainability, contributing to one of the most severe problems affecting conurbations, air pollution, which negatively impacts human health and the environment.
This study aims to assess and quantify the impact of navigation systems on traffic and the urban environment through realistic simulations and what-if analysis. In particular, we consider CO2 emissions to measure the effect of traffic on the environment. Furthermore, we will assess how much the percentage of vehicles that follow different types of indications impacts on the CO2 emissions and their concentration on the roads of the network.
We set up precise and realistic traffic simulations using SUMO (Simulation of Urban MObility) within different scenarios in which various proportions of the vehicles follow the recommendations of satellite navigators to assess the impact of routing strategies concerning individual and collective dimensions.
Results
From the simulations, we find that the extreme settings where no vehicle follows any particular router and where all the cars folow one particular router are the worst in terms of their impact on sustainability. On the opposite side, a balanced mix of vehicles following a navigation system and vehicles that do not follow their instructions appear to have a lighter impact on the city's roads and the environment, making vehicles' emissions more sustainable. In the balanced setting composed of 40% of cars following the suggestion of satellite navigators we observed the lowest number of CO2 emissions, and the pollution is distributed more evenly on the road network.
Tangible output
- A bundle to replicate a simulation with SUMO over Milano with 15k vehicles and 40% routed ones: https://kdd.isti.cnr.it/~nanni/Simulation_bundle_40percent_routed.zip
This Humane-AI-Net micro-project was carried out by Giuliano Cornacchia (PhD UniPi), Giovanni Mauro (PhD IMT-UniPi), Matteo Bohm (PhD UniRome), Mirco Nanni (CNR), Dino Pedreschi (UniPi) and Luca Pappalardo (CNR)