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The paper focuses on the calibration of the hybrid multi-scale modelling approach that incorporates multiple levels of traffic flow representation. This paper refers to a model already developed in the literature, the Hybrid Cellular Automata (CA) and Cell Transmission Model (CTM). We use vehicle trajectory data collected from a car-following field experiment on a circular road track to explore the calibration of the CA model concerning various cell lengths through two distinct approaches: simulating all vehicles within the closed loop and simulating each vehicle using data obtained from its respective follower. We also evaluate different methods for the CTM calibration with respect to the CA model. The major findings are: (1) the calibrated parameters obtained using the simulated leader approach display greater regularity across different cell lengths; (2) the Constrained Squared Error [CsqE] method for macroscopic calibrations yielded promising results, showcasing the lowest sum of squared errors between fundamental diagrams. [ABSTRACT FROM AUTHOR]

Using a macro-panel data set from 20 Italian regions, this study explores the relationship between unemployment and fertility in Italy between 2006 and 2018. It contributes to recent literature on this subject by considering gender-specific unemployment measures and examining the influence of two important compositional factors on fertility responses, namely the presence of foreign women and daily childcare coverage, and the influence of both of these on the link between unemployment and fertility. The study reveals a procyclical relationship between unemployment rates, used as a proxy of variations in business cycles, and fertility. Positive influences of foreign women's contribution and daily childcare coverage on fertility are uncovered, suggesting a potential mitigation effect on declining fertility trends during the period under observation. [ABSTRACT FROM AUTHOR]

The Russia–Ukrainian war, which began in 2014 and exploded with the invasion of the Russian army on 24 February 2022, has profoundly destabilized the political, economic and financial balance of Europe and beyond. To the humanitarian emergency associated with every war has been added the deep crisis generated by the strong energy and food dependence that many European countries, and not only European, have developed over decades on Ukraine (especially for wheat) and Russia (especially for natural gas). The aim of this article is to verify the existence of a link between the performance of the Eurostoxx index and the price of wheat futures and TTF natural gas, from 25 February 2019 to 28 September 2023. Through a quantile VAR analysis, a link is sought between the Eurostoxx 50 index, and wheat and TTF gas futures prices. Furthermore, the analysis intends to understand whether the presence of such relationship only manifested itself following the war events, or whether it was already present in the market. The analysis carried out also shows that the relationship between the stock market and raw material prices was present even before the conflict. [ABSTRACT FROM AUTHOR]

It is common opinion that traditional approaches used to interpret and model users' choice behaviour in innovative contexts may lead to neglecting numerous nonquantitative factors that may affect users' perceptions and behaviours. Indeed, psychological factors, such as attitudes, concerns, and perceptions may play a significant role which should be explicitly modelled. By contrast, collecting psychological factors could be a time and cost consuming activity, and furthermore, real-world applications must rely on theoretical paradigms which are able to easily predict choice/market fractions. The present paper aims to investigate the above-mentioned issues with respect to an innovative automotive technology based on the after-market hybridization of internal combustion engine vehicles. In particular, three main research questions are addressed: (i) whether and how users' characteristics and attitudes may affect users' behaviour with respect to new technological (automotive) scenarios (e.g., after-market hybridization kit); (ii) how to better 'grasp' users' attitudes/concerns/perceptions and, in particular, which is the most effective surveying approach to observe users' attitudes; (iii) to what extent the probability of choosing a new automotive technology is sensitive to attitudes/concerns changes. The choice to install/not install the innovative technology was modelled through a hybrid choice model with latent variables (HCMs), starting from a stated preferences survey in which attitudes were investigated using different types of questioning approaches: direct questioning, indirect questioning, or both approaches. Finally, a comparison with a traditional binomial logit model and a sensitivity analysis was carried out with respect to the instrumental attributes and the attitudes. Obtained results indicate that attitudes are significant in interpreting and predicting users' behaviour towards the investigated technology and the HCM makes it possible to easily embed psychological factors into a random utility model/framework. Moreover, the explicit simulation of the attitudes allows for a better prediction of users' choice with respect to the Logit formulation and points out that users' behaviour may be significantly affected by acting on users' attitudes., 1. Introduction and Motivations The diffusion and market penetration of new technologies is becoming a crucial factor for transport system analysts and decision-makers. Among the several new technologies aiming to [...]

The paper proposes a traffic responsive control framework based on a Model Predictive Control (MPC) approach. The framework focuses on a centralized method, which can simultaneously compute the network decision variables (i.e., the green timings at each junction and the offset of the traffic light plans of the network). Furthermore, the framework is based on a hybrid traffic flow model operating as a prediction model and plant model in the control procedure. The hybrid traffic flow model combines two sub-models: an aggregate model (i.e., the Cell Transmission Model; CTM) and a disaggregate model (i.e., the Cellular Automata model; CA), using a transition cell to connect them. The whole framework is tested on a signalized arterial, performing several analyses to calibrate the MPC strategy and evaluate the traffic control approach using fixed and adaptive control strategies. All analyses are made in terms of total time spent, network total delay, queue lengths and degree of saturation. [ABSTRACT FROM AUTHOR]