Smart Traffic Load Balancing by Balancity

Header image: Smart Traffic Load Balancing by Balancity

Balancity is a research project regarding smart traffic load balancing in Amsterdam. Managing motorized traffic flows is an important issue in every major metropolitan area, especially in Amsterdam. The city should take into account economic productivity loss due to traffic congestion. Also, noise and air pollution aspects should be included. We propose a route planning system. This system considers multiple, collective and concurrent objectives. These objectives concern congestion and pollution on various roads. The system balances traffic over the road network in a highly effective way. The project will produce a technological proof-of-concept. This embodies a demonstrator website of such a load balancing system. The project uses techniques from artificial intelligence, traffic science, and multi-agent systems, as well as open map, traffic, and pollution data.

Problem statement

Managing motorized traffic flows is an important issue in every major metropolitan area. This is true in particular for Amsterdam due to its high population density, congestion, noise, and air pollution problems. Traffic management aims to reduce these problems but cannot normally influence routes chosen by individual vehicles. On the other hand, many modern individual route planning and navigation systems take into account real-time congestion information. But they do not take into account collective interests such as limited capacity or pollution constraints of alternative routes. When more and more individuals use such individual systems a situation may arise where large numbers of vehicles are simultaneously choosing the ‘fastest’ alternative route. Individual systems schedule this route often through limited capacity and densely populated urban areas when a motorway is congested. This pollutes and congests roads where it harms most. Ironically, this even possibly slows routes for the individual users.

Approach

We propose a smart traffic approach where individual route planning and navigation systems and collective considerations are not completely independent. Even at times, they can be regarded as counteractive processes. In contrast, route planning and navigation systems should be able to take into account multiple collective objectives. The objectives concern congestion and pollution on various roads in the complete road network. Also, they help in balancing traffic over the network in a highly effective way. For example, heavy goods diesel truck may automatically be assigned a route avoiding a certain road in a densely populated area which already receives a large amount of traffic, even though its quickest route would use that road.

Objective

The project aims to develop and demonstrate the first version of a smart traffic route planning system. This system should take into account multiple, collective objectives concerning congestion and pollution on various roads in the complete road network of Amsterdam. It should balance traffic over the network in a principled way based on those objectives.

Project duration: December 2015 – September 2016

Partners: Delft University of Technology, Cygnify BV

This project is an AMS Stimulus Project. The aim of Stimulus Projects is to give to new and existing AMS partners support to innovative research that has a strong upscaling potential. The projects should realize short-term research output, which acts as a catalyst of a new solution direction, concept or approach.

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