Brief description

Freight delivery within the city has a great impact on traffic flow and is responsible for traffic congestion to a high extent. Central areas of the city face a number of situations every day:

  • Misuse of parking areas by private vehicles, so that they are not free for freight delivery vehicles as they should.
  • Not enough load and unload areas to cover current needs.
  • Not enough control and surveillance to ensure an adequate use of load and unload areas

In most cities urban freight activity in the city centre is regulated by the Mobility Area in City Council and, to manage freight delivery daily operations, some of these local administrations have specific regulations. However, in some cases, new regulations that ensure an efficient operation of last mile delivery, that does not hinder the city traffic flow, are required. Furthermore, for traffic managers and planners to analyse in advance the impact of future regulations that ensure an efficient operation of last mile delivery is essential.

In order to come up with adequate recommendations that can lead to such regulations, a thorough analysis of current traffic and urban freight delivery activities must be performed, so that all the knowledge extracted from data can be used by the traffic simulation models to be developed.

Generate these traffic models for particular areas in the city where freight transport has more impact and analyse different freight delivery scenarios to support decision making process are the main feature on this service “Traffic micro-simulation model in city centres”.  As main results, different traffic micro-simulation models will be developed, as well as a dashboard to show valuable insights from Data Analytics tasks.

Currently these solutions have been implemented in Valladolid, a city in the north-central of Spain. CARTIF, that has defined the data analytics framework, performed the traffic micro-simulation model and develop the dashboard, is able to offer all these services to any other city. Of course, have real data about the traffic and load/unload activities in the city is mandatory.

Main Features

Generate traffic models for particular areas in the city where freight transport has more impact and analyse different freight delivery scenarios to support decision making process is the focus of this service.

In detail, the service include following tasks that can be carried out jointly or individually:

  • Data Analytics through a Knowledge Discovery from Data (KDD) process using real data and expert knowledge to discover behaviour/patterns in the traffic within the city and in the routes of logistic vehicles.
  • Traffic micro-simulation models for the city centre will be implemented. The model included all the knowledge extracted from real (traffic and logistic) data, as well as expert knowledge.
  • Dashboard to show valuable insights focused on: showing result of current and simulated traffic models, allowing access to planning tool for logistic operators, discovering patterns in the traffic, discovering behaviour in the routes, and calculating different KPIs to assess logistic operations.
Areas of Application

Urban Mobility: mobility manager and/or logistic operator.

Customer Benefits

For traffic managers and planners, having these type of models lets them analyse and simulate in advance changes in the places reserved for loading/unloading activities, the extension of these zones or the type of zone, etc.  Also, for traffic managers and planners, these models are crucial to show politicians that decision-making process is backed up in real data and objective criteria.

Technological novelty

A common framework of how generate traffic micro-simulation model based on data analytics, and including loading/unloading activities, have been defined and can be applied in other cities. Specifically:

  • Knowledge Discovery from Data (KDD) process applied to real traffic and logistic data.
  • Traffic micro-simulation models, developed through a proprietary event-discrete based software, reflecting reality as faithfully as possible.