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Traffic noise is a significant externality in urban areas that reduces the quality of life and may produce non-negligible effects on human health. The main factor responsible for traffic noise is individual transportation (cars and motorcycles) and the more congested the urban network, the higher the average level of traffic noise. An Urban Traffic Plan (UTP) is a tool for managing the urban mobility; in Italy the UTP is provided for under national laws and one of its objectives is noise abatement. The UTP manages the network (road directions, signal settings, etc.) without providing new infrastructures. In this paper, the authors test the effectiveness of UTPs in terms of noise abatement on a real case: the Urban Traffic Plan of Benevento. In this paper, the authors compare the estimated equivalent noise levels in several points of the town for the current scenario and for the (final) design scenario. Initial results show that, in order to evaluate the actual effectiveness of the UTP vis-a-vis traffic noise, some more comprehensive indicators have to be proposed: evaluating traffic noise reduction only in some points of the network cannot yield clear-cut results

In railway systems, the evaluation of specific operating conditions and their impact on travel demand plays a key role both in planning and managing rail services. In this paper, the authors focus on the implementation of some energy saving strategies (ESSs) through the definition of energy-efficient speed profiles and estimate their effects on travel demand. In particular, speed profiles for ESSs need extra time for their implementation and hence entail a reduction in line performance. The definition of optimal speed profiles requires the use of optimisation procedures which can be formulated by considering motion parameters as control variables and energy consumption as the performance to be optimised (minimised), with respect to the available time. The proposed methodology is applied in the case of a real metro line, showing differences in user generalised costs, in order to provide additional information for rail operators which may allow evaluation of the best strategies to be adopted.

This paper describes the first results of a research project where the main focus is to implement a Decision Support System (DSS) to optimise energy consumption of rail systems. In order to achieve this objective, the authors implement an optimisation module for the design of energy-efficient driving strategies, in terms of speed profiles, that requires a railway simulation model as a subroutine. Here the authors focus on the general framework of the optimisation module and on the calibration of the railway simulation model. All elaborations are implemented in a MatLab environment, aiming at defining possible energy-efficient speed profiles, in accordance with energy-saving strategies, through optimised speed profile parameters, in terms of acceleration, target speed, deceleration, coasting phase, and driving behaviour, represented by the jerk. The model is calibrated on real data recorded on a double track section of a railway line in the city of Naples (Italy). Initial results show that consumption is very variable with the speed profile and with driver behaviour, but the model is able to reproduce the average consumption of each driving strategy and should be able, within the DSS, to suggest the best driving strategies for each rail section.

In this paper, the authors propose a model framework for providing optimal driving strategies and related speed profiles which minimise the energy consumption of rail convoys. Previous models were extended and applied to evaluate the effects of different signalling systems upon rail operating costs. The proposed method was tested on a real rail network, the Cumana suburban railway (Italy).