Traffic Management

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The efforts for the improvement of urban traffic face two major challenges: the concentration of population in urban areas and the lack of viability or profitability of traditional solutions, like the increase of infrastructures. Now is the time to investigate, experiment and implement innovative solutions. Nowadays we frequently hear about shared vehicles, urban tolls, bicing and very many other novelties. One of the key applications of Intelligent Transport Systems (ITS) are the Advanced Traffic Management Systems (ATMS), conceived as systems for decision making support in order to identify the most adequate traffic management strategy as a function of the traffic state and its forecasted short term evolution. Betterways comes into this area through the use of the Macro Fundamental Diagram theory (MFD) and with systems for the dynamic evaluation (KPIs) of control plans.

Betterways counts with a Decision Support System for ATMS that comes from investigating the new theory of the Macro Fundamental Diagram, that has extended to urban networks the concept of Traffic Fundamental Diagram, key to determine the traffic state for simple structures as, for instance, a highway, and identify the trend of its evolution and decide how to fix or ease any conflicts. The MFD is a method for the assessment of the global state of a complex network through the aggregation of data from a minimum number of sensors. This information allows, in a first stage, the design of strategies at metropolitan level and, on a second stage, a global management to avoid congestions. It allows to:

  • Estimate the network’s capacity, that is the maximum number of vehicles that can move about the network without collapsing it
  • Identify on real time the conditions of operation (free flow, trend to instability, congestion, ...) and its evolution
  • Helps to assess, depending on the present state and its evolution, which may be the most adequate management strategy

The most important local factors are traffic timings, combined with systems like access control, variable speed limits and information diffusion (VMS).

For the design of different control plans, in a first stage average traffic states may be identified according to the day-type. But the deviation of a particular day with respect to that average state can be very significant due to internal factors like demand fluctuations or external ones such as civil works, accidents, protests, congresses or other sort of events. The problem becomes increasingly complex as the number of profiles increases, as they must be, classified and a specific control plan has to be designed for each particular profile. On the other hand instead of establishing a link between the external factors (i.e. time slice, week day, season, weather conditions, events, incidents, ...) and control plans another option would be to establish a link between traffic conditions and control plans and so, the solution would hover over the capacity to establish that link rather than designing and endless number of control plans.

That is Betterways line of work, making use of state-identification techniques and/or mesoscopic simulation for the calculation of the KPIs that allow to identify, on real time and during all day long, alternatives to the default control plans, in order to avoid or ease congestions, maximize the network’s capacity and give support to decision making about local traffic control.