Silvio Memoli

The Network Signal Setting Problem: The Coordination Approach vs. the Synchronisation Approach

The network signal setting can be addressed through two approaches: coordination or synchronisation. In this context, this paper aims to further investigate the efficiency of the two approaches by considering different layouts of network complexity (three urban network configurations of the municipality of Avellino, in Campania Region). Moreover, two traffic models are compared- the platoon dispersion model vs. the cell transmission model -- by studying the effects of the variation of the distances between pairs of adjacent junctions. Finally, in this paper the results of the simulations obtained by two optimisation algorithms, the Hill Climbing vs. the Simulated Annealing, are also compared in order to analyse their efficiency with respect to the degree of network complexity.

Signal Setting Design at a Single Junction Through the Application of Genetic Algorithms

The purpose of this chapter is the application of Genetic Algorithms to solve the Signal Setting Design at a single junction. Two methods are compared: the monocriteria and the multicriteria optimisations. In the former case, three different objectives functions were considered: the capacity factor maximisation, the total delay minimisation and the total number of stops minimisation; in the latter case, two combinations of criteria were investigated: the total delay minimisation and the capacity factor maximisation, the total delay minimisation and the total number of stops minimisation. Furthermore, two multicriteria genetic algorithms were compared: the Goldberg’s Pareto Ranking (GPR) and the Non Dominated Sorting Genetic Algorithms (NSGA-II). Conclusions discuss the effectiveness of multicriteria optimisation with respect to monocriteria optimisation, and the effectiveness of NSGA-II with respect to the GPR.

Comparing Signal Setting Design Methods Through Emission and Fuel Consumption Performance Indicators

In order to address the Signal Setting Design at urban level two main approaches may be pursued: the coordination and the synchronisation approaches depending on the steps considered for the optimisation of decision variables (two steps vs. one step). Furthermore, in terms of objective functions mono-criterion or multi-criteria may be adopted. In this paper the coordination approach is implemented considering the multi-criteria optimisation at single junctions and mono-criterion optimisation at network level whereas the synchronisation is implemented considering the mono-criterion optimisation.

Matching macro- and micro-scopic approaches for the evaluation of traffic management impacts

The paper focuses on the evaluation of the combined effect of Traffic Signal Control Strategy (TSC) and Variable Message Sign (VMS). With reference to the TSC a dynamic selection strategy based on macroscopic flow variables was considered for off-line traffic signal plans design. The combination of two ITS solutions, TSC and VMS, was tested through microscopic approach by SUMO traffic simulator which allows to directly reproduce the pollutant emissions and fuel consumptions.

The use of the analytic hierarchy process method for supporting urban road regeneration actions: The case study of Naples

The paper focuses on the application of an AHP (Analytic Hierarchy Process) procedure for helping the decision maker in the identification of the road maintenance actions aiming to improve safety conditions and optimize the interchanges/interactions in terms of origin/destination flows among some strategic areas of the municipality of Naples.

Macroscopic vs. mesoscopic traffic flow models in signal setting design

The simulation of interactions among vehicles approaching signalised junctions, at urban level, is still an open issue. Based on this consideration, this paper aims at comparing the macroscopic and mesoscopic approaches for traffic flow simulation in signalised junctions. In terms of signal setting design, the considered decision variables are the green timings, the scheduling and the offsets thus the three steps optimisation (i.e. each step is referred to the optimisation of each decision variable) has been applied. In particular, the green timings and the scheduling are carried out at single junctions, by multicriteria optimisation, and the offsets are computed by monocriteria optimisation. Finally, the optimisation problems are solved through metaheuristics algorithms.