Luca D'Acierno

A meta-heuristic approach for solving the Urban Network Design Problem

This paper proposes an optimisation model and a meta-heuristic algorithm for solving the urban network design problem. The problem consists in optimising the layout of an urban road network by designing directions of existing roads and signal settings at intersections. A non-linear constrained optimisation model for solving this problem is formulated, adopting a bi-level approach in order to reduce the complexity of solution methods and the computation times. A Scatter Search algorithm based on a random descent method is proposed and tested on a real dimension network. Initial results show that the proposed approach allows local optimal solutions to be obtained in reasonable computation times.

Estimation of urban traffic conditions using an Automatic Vehicle Location (AVL) System

The aim of this paper is to develop an Information Extension Model (IEM) which uses location data of bus fleets (AVL data) to estimate road traffic conditions and provide input for implementing control strategies. The IEM consists of three sub-models: the Link Traffic Condition Model (LTCM), the AVL Adaptation Model (AVLAM) and the Network Traffic Condition Model (NTCM). The first provides road traffic conditions as a function of mass-transit traffic conditions in the case of shared lanes, the second provides mass-transit traffic conditions as a function of AVL data, and the last provides road traffic conditions over the whole road network as a function of mass-transit traffic conditions. The IEM (and its sub-models) were developed and calibrated in the case of real dimension networks and some tests were performed on a trial network. Numerical results show the effectiveness of the proposed method since it allows a reduction in travel demand estimation errors.

A simulation framework for supporting design and real-time decisional phases in railway systems

Actors of railway systems are more and more required to achieve certain levels of system performances and acceptable standards of service quality offered to passengers. To reach this aim, effects on both supply and demand-side induced by different solutions, need to be assessed within design and real-time operation phases, especially when failures occur during service. To this purpose, in this paper an integrated framework is introduced to simulate railway operation considering also interactions with passengers demand. A practical application to a MRT line has been realized, analyzing impacts of two recovery strategies for different failure scenarios. Results underline the necessity of assessing both service availability and quality of service to identify the most effective intervention solution, and highlight the relevance of the proposed framework to support decisional processes.

An integrated approach for availability and QoS evaluation in railway systems

Prediction of service availability in railway systems requires an increasing attention by designers and operators in order to satisfy acceptable service quality levels offered to passengers. For this reason it is necessary to reach high availability standards, relying on high-dependable system components or identifying effective operational strategies addressed to mitigate failure effects. To this purpose, in this paper an innovative architecture is proposed to simulate railway operation in order to conduct different kinds of analysis. This architecture encompasses a set of components considering, in an integrated way, several system features. Finally an application to a first case study demonstrates the impact on quality of service and service availability of different recovery strategies. Complexity of a railway system requires a heterogeneous working group composed of experts in transport and in computer science areas, with the support of industry.

Defining economic and environmental feasibility thresholds in the case of rail signalling systems based on satellite technology

A rail system represents a useful tool for reducing flows (cars and trucks) on a road system in high density contexts (such as urban and metropolitan areas) with a view to abating greenhouse gas emissions. In particular, since rail passengers maximise their own utility, variations in mobility choices can be induced only by significantly improving the level-of-service of public transport. By defining feasibility thresholds, our proposal is to analyse the economic and environmental feasibility of a new signalling system which would increase service frequencies of a rail system, thereby reducing passenger waiting times. This approach was applied to a regional rail line in southern Italy to show the usefulness of the proposed methodology.

An analytical approach for determining reserve times on metro systems

In recent years the growing interest in environmental issues has prompted researchers to investigate two main areas in the field of rail systems: how to improve performance in order to attract users from other transport modes with greater environmental impacts (such as private cars) and how to reduce energy consumption. On the latter issue, some procedures have been developed for determining suitable ‘green’ driving profiles which are, however, subject to greater travel times. Since precise quantification is critically important, in this paper we propose an approach to determining all operational times analytically, including reserve times. Finally, the methodology is applied in the case of a real metro line for validating the proposal.

Defining Robust Recovery Solutions for Preserving Service Quality during Rail/Metro Systems Failure

This paper proposes a sensitivity analysis for evaluating the effectiveness of recovery solutions in the case of disturbed rail operations. Indeed, when failures or breakdowns occur during daily service, new strategies have to be implemented so as to react appropriately and re-establish ordinary conditions as rapidly as possible. In this context, the use of rail simulation is vital: for each intervention strategy, it provides the evaluation of interactions and performance analysis prior to actually implementing the corrective action. However, in most cases, simulation tasks are deterministic and fail to allow for the stochastic distribution of train performance and delays. Hence, the strategies adopted might not be robust enough to ensure effectiveness of the intervention. We therefore propose an off-line procedure for disruption management based on a microscopic and stochastic rail simulation which considers both service operation and travel demand. An application in the case of a real metro line in Naples (Italy) shows the benefits of the proposed approach in terms of service quality.

A Decision Support System for Analysing Conflicts Related to Pricing Policies Implementation

Negli ultimi anni molte citta europee hanno introdotto politiche di tariffazione come strumento di gestione della domanda di trasporto, in particolare per ridurre la congestione e riequilibrare la ripartizione modale tra trasporto individuale e collettivo. Infatti, il comportamento degli utenti conduce il sistema ad una condizione di Equilibrio dell’Utente ( User Equilibrium ) che non corrisponde alla massimizzazione dell’utilita globale e non prende in considerazione i costi esterni. Pertanto, al fine di raggiungere una configurazione efficiente nell’utilizzo dei sistemi di trasporto (indicata in letteratura come Equilibrio del Sistema – System Equilibrium ), e necessario imporre una tariffazione sulle strade urbane in modo da massimizzare il surplus sociale. Per numerose ragioni (teoriche, politiche, sociali) e impossibile applicare “tariffe efficienti” (indicate in letteratura come first-best solutions ); percio sulle reti reali bisogna applicare tariffe sub-ottimali ( second-best solutions ). Inoltre, una delle problematiche principali dell’applicazione delle politiche di pricing e la loro “accettazione” da parte della comunita e/o di sue componenti (commercianti, residenti, pendolari, ecc.) che conduce a conflitti ed opposizioni. In questa nota, si analizza il problema del progetto delle tariffe ottimali nel caso in cui i ricavi siano investiti totalmente o parzialmente per migliorare il trasporto collettivo. In particolare, si formula un modello che sia multimodale e multiutente, in cui gli aspetti relativi alla scelta modale siano calcolati in maniera esplicita su rete in corrispondenza di ciascuna configurazione tariffaria. Il modello e applicato ad una rete test (costruita con differenti valori di accessibilita relativa tra le differenti zone), analizzando alcune strategie “second-best” con particolare riferimento al reinvestimento dei ricavi.