Urban Traffic Control Optimization based on observed data using microsimulation experiments

Urban traffic management uses the available information to create efficient strategies and guarantee safe movements for vehicles along road infrastructures, resulting on an improvement in the quality of life. It is well-known that junctions and congestion can be the cause of many problems as air pollution and fuel consumption. This is why the present work focuses on the analysis of traffic control optimization techniques, to reduce delay caused by signalized intersections, and travel time along links through experiments performed in a microsimulation environment. To that end, AIMSUM tools have been used to integrate the information from the database provided for the study area, in the city of Bologna, which collects real traffic data from inductive loops and the traffic signal cycle lengths provided by Swarco Italia S.r.l through UTOPIA traffic control. Once created the network model of the study area and implemented the traffic controls, three simulated scenarios are designed considering firstly the current conditions of the city, and then the implementation of the green wave after introducing offsets along the intersections. A further scenario is introduced to mitigate the critical traffic conditions observed for the penalized approaches, with the aim to create a balance and provide improvements for all the sub paths. This methodology line is based on an integrated regulation, the latter carried out by the feedbacks of the microsimulation experiments, which enabled to compare and switch different solutions from a control viewpoint. Results after the implementation of the green wave indicate reductions in travel time from ten seconds to almost one minute along main sub paths, compared to base conditions, as well as the ‘balanced green wave’, which provides improvements spread across the entire network. A look is given also to public transport lines that interest the study area, evaluating the effects and changes provided by these strategies. Today there are different techniques that allow to make cooperative an urban network, also thanks to the day-by-day improvements reached on telematics and communications applied to a smart integration of traffic data, as data fusion (DF) and floating car data (FCD). A discussion about these techniques and main outcomes that can be reached with them is also provided in this thesis work.