Vittorio Marzano

Multi Regional Input-Output Models for Freight Demand Simulation at a National Level

This paper discusses the analysis of freight transport and economic effects of infrastructural investments in Southern Italy, through the application of a recently updated MRIO-based Italian freight DSS (Marzano and Papola 2004, Cascetta et al. 2005). First, the paper proposes an original state-of-the-art systematization of input-output models for freight demand simulation at a national level. Then, generalizations allowing for elasticity both in trade and in technical coefficients are discussed, together with further research perspectives. Finally, a modification of the RUBMRIO model (De La Barra 1989) is applied for infrastructural investments appraisal in Southern Italy, focusing also attention on the impacts on the overall national economy.

A Network Generalized Extreme Value Model for Route Choice Allowing Implicit Route Enumeration

Medium to large urban networks are normally characterized by a high number of origin-destination pairs that are connected by a large amount of strongly overlapping routes. This article introduces an adaptation of the Network Generalized Extreme Value (GEV) model for modelling joint choices, named Joint Network GEV (JNG), and its application to the route choice context, named Link-Based JNG (LB-JNG), and assumes the choice of a route as the joint choice of all links belonging to that route. The LB-JNG model aims at reproducing the effects of routes overlapping with a theoretical robust framework (since it belongs to the Network GEV, to date the most flexible closed-form model in reproducing covariances), allowing at the same time for easy application to real networks through a closed-form probability statement, a proper definition of its parameters and the availability of an implicit route enumeration algorithm for network loading. An overview of the theoretical properties of the JNG model is presented in this article. The LB-JNG adaptation to route choice is described, and the capability to reproduce the effects of routes overlapping is investigated using some test networks. The article compares the performances of the proposed model with those of other route choice models available in the literature. The article proposed and tested an implicit route enumeration algorithm for macroscopic static stochastic network loading on real size networks based on a double-step generalization of Dials STOCH algorithm.

Effects on speed and safety of point-to-point speed enforcement systems: Evaluation on the urban motorway A56 Tangenziale di Napoli

In this paper, we evaluated the effects on speed and safety of the point-to-point (P2P) speed enforcement system activated on the urban motorway A56 in Italy. The P2P speed enforcement is a relatively new approach to traffic law enforcement that involves the calculation of the average speed over a section. To evaluate the speed effects, we performed a before-after analysis of speed data investigating also effects on non-compliance to speed limits. To evaluate the safety effects, we carried out an empirical Bayes observational before-and-after study. The P2P system led to very positive effects on both speed and safety. As far as the effects on the section average travel speeds, the system yielded to a reduction in the mean speed, the 85th percentile speed, the standard deviation of speed, and the proportion of drivers exceeding the speed limits, exceeding the speed limits more than 10km/h, and exceeding the speed limits more than 20km/h. The best results were the decrease of the speed variability and the reduction of the excessive speeding behaviour. The decrease in the standard deviation of speed was 26% while the proportion of light and heavy vehicles exceeding the speed limits more than 20km/h was reduced respectively by 84 and 77%. As far as the safety effects, the P2P system yielded to a 32% reduction in the total crashes, with a lower 95% confidence limit of the estimate equal to 22%. The greatest crash reductions were in rainy weather (57%), on wet pavement (51%), on curves (49%), for single vehicle crashes (44%), and for injury crashes (37%). It is noteworthy that the system produced a statistically significant reduction of 21% in total crashes also in the part of the motorway where it was not activated, thus generating a significant spillover effect. The investigation of the effects of the P2P system on speed and safety over time allowed to develop crash modification functions where the relationship between crash modification factors and speed parameters (mean speed, 85th percentile speed, and standard deviation of speed) was expressed by a power function. Crash modification functions show that the effect of speed on safety is greater on curves and for injury crashes. Even though the study results show excellent outcomes, we must point out that the crash reduction effects decreased over time and speed, speed variability, and non-compliance to speed limits significantly increased over time. To maintain its effectiveness over time, P2P speed enforcement must be actively managed, i.e. constantly monitored and supported by appropriate sanctions.

Effectiveness of Origin–Destination Matrix Correction Procedure Using Traffic Counts

The estimation and correction of the origin-destination (O-D) matrix from traffic counts is a classical procedure usually adopted in transport engineering by practitioners to improve the overall reliability of transport models. Recently, Papola and Marzano showed through laboratory experiments that this procedure is generally not able to provide an effective correction of the O-D matrix. This result can be justified from a theoretical standpoint because of the lower number of stochastic equations (independent observed link flows) with respect to the unknowns (O-D flows). The current study confirms, first, that this circumstance represents the main reason for failure of the procedure by showing that good correction is generally obtained when the number of equations is greater than the number of unknowns. Then, since this circumstance does not occur in practice, in which the number of O-D pairs is usually much greater than the number of link counts, the study explores alternative assumptions and contexts that allow for a proper balance between unknowns and equations. In more detail, this balance can be achieved by moving to within-day dynamic contexts, in which a much larger number of equations is generally available. Obviously, to bound the corresponding increase in the number of unknowns, specific reasonable hypotheses in O-D flow variation across time slices must be introduced. In that respect, the effectiveness of the O-D matrix correction procedure in the usually adopted linear hypothesis on the dynamic process evolution of O-D flows and under the assumption of constant distribution shares is analyzed.

Free Trade Agreement Effects in the Mediterranean Region: An Analytic Approach Based on SURE Gravity Model

Free trade agreements (FTAs) are tools that have been widely implemented for enhancing trade between countries. As a result, various models have been developed in an effort to explain the effects of these agreements on trade. The objective of this study is to develop a model suitable for exploring FTA effects on trade flows in the Mediterranean region. For that purpose a model is developed for analyzing trade flows based on the family of gravity models; the model parameters are estimated by using the seemingly unrelated regression estimation approach, in an effort to account for cross-sectional heterogeneity, serial correlation, and heteroscedasticity in the data set used. Results of the derived models are discussed and indicate that FTA effects on trade flows do exist but remain relatively low compared with other factors such as transportation costs.

Empirical Comparison of Parametric and Nonparametric Trade Gravity Models

A systematic comparison is made of parametric (i.e., ordinary least-squares regressions and related generalizations) and nonparametric (i.e., kernel regressions and regression trees) log-linear gravity models for reproducing international trade. Experiments were conducted to estimate a log-linear gravity model reproducing import and export trade flows in quantity between Italy and 13 world economic zones, based on a panel estimation data set. The best parametric regression model was estimated to define a baseline reference model. Some specifications of nonparametric models, belonging to the categories of kernel regressions and regression trees, were also estimated. The performance of parametric and nonparametric models is contrasted through a comparison of goodness-of-fit measures (R2, mean absolute percentage error) both in estimation and in hold-out sample validation. To assess the differences in model elasticity and forecasts, both parametric and nonparametric models are applied to future scenarios and the corresponding results compared.

The importance of choosing appropriate random utility models in complex choice contexts

This research proposes a comparative analysis of the performance of various random utility models (RUM) — namely Multinomial Logit, Nested Logit, Cross Nested Logit, FinMix and CoNL-estimated on a synthetic dataset with variable sample size and correlation patterns. This experimental framework allows comparing model estimates in a fair, controlled environment wherein all relevant characteristics (coefficients, attributes, covariances, likelihood, elasticities) of the “true” underlying model are known. Models are validated especially by comparing true and estimated market share elasticities where the market share is the sum over all observations of the individual probabilities of a given alternative. Indeed, this indicator represents the real forecasting capability of a model, that is the main target for the analyst. Moreover, its true value can be computed when dealing with a synthetic database by evaluating the difference in the number of choices of a given alternative between future and current scenarios, due to a difference in some attributes value. Comparisons are carried out on several choice contexts, characterized by different correlation matrices and variable sample size.

Quantitative overview of efficiency and effectiveness of public transport in Italy: The importance of using ITS

This paper reports on a summary overview of a study aimed at assessing the health of the Italian Local Public Transport system. In close cooperation with the Italian Ministry of Infrastructures and Transport, more than 500 Italian local public transport operator, covering most of Italian cities, were analyzed, to investigate their efficiency and effectiveness. All relevant economic and operational (i.e. transport-related) characteristics of the companies have been quantified through a set of performance indicators. The paper illustrates some of them, aggregated at a regional level, showing a considerable heterogeneity amongst regions and providing preliminary policy recommendations. Concluding remarks are drawn based upon these indicators, showing in particular how diffusion of Intelligent Transportation Systems — especially for ticketing, monitoring and enforcement — is crucial to improve system performances.

Kinematic formulation of energy-efficient train speed profiles

This paper proposes a kinematic model for optimising train speed profiles along homogeneous sections with a view to minimising energy consumption. By using the proposed model a very parsimonious, computationally light energy-saving optimisation problem suitable for real-time applications can be formulated. The model is tested on several appropriate case studies.

Methodology for Locating Link Count Sensors That Accounts for Reliability of Prior Estimates from Origin-Destination Matrices

The paper proposes an innovative methodology for addressing the issue of the location of optimal link count sections on the basis of the proposition of a reliability measure in which the prior accuracy of the estimate of the origin–destination (O-D) matrix, that is, its statistical distribution rather than its prior punctual estimate, is explicitly considered, together with its posterior distribution conditioned on a given subset of link count locations. The proposed measure, under the mild assumptions of prior normal distribution and through appropriate algebraic rotations of the reference system, is proved not to depend on the unknown values of the counted flows; this is actually the key point that allows for effective implementation of a fast and operational procedure that is based on this mathematical framework. As an example, toy network and real network applications are presented to show how a heterogeneous level of knowledge across O-D pairs may lead to the choice of counting sections different from those resulting from the commonly adopted procedures. The proposed methodology allows for a more effective theoretical interpretation of the phenomenon and leads to an extremely efficient computational procedure—suitable also in real-size networks—whose results outperform those obtained with the methods currently available in the literature.