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In this paper, an integrated approach is proposed that incorporates the road network design problem and the vehicle routing problem, which are very often studied separately. This approach can be adopted when the routes to follow in a transport system have to be designed (e.g., for public transit with fixed and variable routes, or for freight distribution) jointly with the network topology and capacity. The goal is to minimise congestion and the impacts on the network from passengers and freight vehicles. The design (control) variables consist of the optimal vehicle routes and optimised road network; they are both discrete (link topology for passenger and freight, routes for passengers and freight vehicles, etc.) and continuous (link capacity in terms of reserved lanes, signal settings, etc.). The problem is modelled in congested transportation networks (e.g., in an urban centre). A heuristic algorithm is adopted to find the best network configuration and the best vehicle routes. The proposed model and the adopted algorithm are applied in a test system to analyse the limits of the methodology, to verify the advantage obtained from the joint method and its applicability. In the test system, the joint procedure gives good results in terms of cost decreases. The reported methods can help public and private stakeholders in making decisions regarding transportation policy, especially in the urban environment.

Sustainable mobility is one of the main challenges on a global level. In this context, the emerging Mobility as a Service (MaaS) plays an important role in the mobility of people. This paper investigates the main enabling factors for implementing the MaaS paradigm, with a specific focus on the level of acceptance of this new technology. To achieve this objective, the proposed methodology for measuring the potential MaaS acceptance is based on a set of pilot surveys. The methodology integrates motivational surveys with Stated and Revealed Preference (SP, RP) and Technology Acceptance Models (TAM). The collected data are processed to obtain indicators that measure the potential level of MaaS acceptance. The main results of the two pilot experiments are illustrated by referring to urban and extra-urban mobility with or without physical barriers. The results obtained show that the level of MaaS acceptance grows with the increase in generalized transport costs perceived by the users.

The reduction of urban congestion represents one of the main challenges for increasing sustainability. This implies the necessity to increase our knowledge of urban mobility and traffic. The fundamental diagram (FD) is a possible tool for analyzing the traffic conditions on an urban road link. FD is commonly associated with the links of a transport network, but it has recently been extended to the whole transport network and named the network macroscopic fundamental diagram (NMFD). When used at the link or network level, the FD is important for supporting the simulation, design, planning, and control of the transport system. Recently, floating car data (FCD), which are based on vehicles’ trajectories using GPS, are able to provide the trajectories of a number of vehicles circulating on the network. The objective of this paper is to integrate FCD with traffic data obtained from traditional loop-detector technology for building FDs. Its research contribution concerns the proposal of a methodology for the extraction of speed data from taxi FCD, corresponding to a specific link section, and the calibration of FDs from FCD and loop detector data. The methodology has been applied to a real case in the city of Santander. The first results presented are encouraging, supporting the paper’s thesis that FCD can be integrated with data obtained from loop detectors to build FD.

Mobility as a Service (MaaS) is the new approach in transportation systems that allows users to use different transport services as a single option, by using digital platforms and with integrated design. In MaaS many actors can be identified: MaaS operators, MaaS companies, MaaS users, citizens, system manager/planner. In order to be able to design the system in an integrated way, it is necessary to identify comprehensive methodologies that make it possible to reach sustainability targets in a context where the decisions to be taken are shared between several operators and affect users and citizens. In this paper, the methods to be adopted for the design of an integrated transport service system have been studied. The main aim of this paper concerns the specification of transport system models for estimating the effects of decision-makers’ actions on MaaS. The consolidated design methodologies of transport networks have been extended in the context of the MaaS. The paper reports a methodology that can be used and describes the main models to be used, which derive from consolidated specifications in the field of transport systems engineering. The methodologies have to be integrated into Intelligent and Communication Technology systems to build the Intelligent Transport System in the MaaS environment.

In transport demand analysis, the calibration of a model means estimation of its (endogenous) parameters from observed data with an inference statistical estimator. Indeed, these considerations apply to any choice behaviour model, such as those derived from Random Utility Theory or any other choice modelling theory. Calibration of choice models can be carried out from disaggregate vs. aggregate data, while inference statistical estimators can be specified through Bayesian vs. Classic (or Frequentist) approaches. In this paper, the resulting Bayesian or Classic disaggregate or aggregate calibration methods are discussed, analysed in detail, and compared from the mathematical point of view. These methods are applied to calibrate Logit choice models for describing path choice behaviour at national scale on a small sample. The Logit choice model can be derived from Random Utility Theory (or be considered an instance of the Bradley–Terry model). Path choice set definition is also discussed, and specialised indicators are used for result comparison. The main contributions of this study concern the use of two different estimation approaches, Bayesian vs. Classic, adopting and introducing some indicators of goodness of estimation. The results of this work, relating to the sample of users adopted, show that the Bayesian approach provides a better estimate than the Classic approach because the calibrated parameters are more stable, the specific constants of the alternatives decrease, and the resulting models show better values of clearly right indicator.

The paper deals with the interaction between freight flows, land use, and economy of a suburban area. In urban freight distribution, the process of freight acquisition of commercial establishments represents a crucial element. Therefore, it is necessary to plan city logistics in order to reduce the negative externalities generated by freight transport without depressing the economic and social vitality. In order to estimate and evaluate the performance and impacts generated by urban freight distribution, Transport System Models (TSMs) play an important role in reproducing and forecasting the process of distribution of final products to retailers and consumers. In recent years, Information and Communication Technologies (ICTs) have made new sources of data in great amounts available at lower costs than data provided from traditional surveys. Among the different data sources, Floating Car Data (FCD), obtained through GPS trackers installed on board the vehicles, offer partial insights into the examined process with lower cost and provide continuous information in space and time. In order to obtain reliable results, it is necessary to combine TSMs and ICTs as observed data could feed Transport System Models and could allow their calibration and therefore their application in real cases. In the above context, the paper deals with TSMs related to estimating urban freight demand flows. The work carried out concerns the specification-calibration-validation of a freight zonal acquisition model by means of FCD related to interzonal trips of commercial vehicles inside the Locride area (Reggio Calabria, Italy). The obtained models, estimated from FCD, could support the a priori evaluation of city logistics measures. The results are more important considering that they are obtained in an area with a lack of transport monitoring technologies. They could be adopted in other similar areas and confirm that adequate planning of city logistics determines advantages for environmental, social, and economic sustainability.

Social media data is an important source of information that can also be used for the study of the passenger mobility sector. In transport systems, user choice is studied through demand models that define how user behavior is affected by the performance of the supply system. Demand models are typically calibrated through data observed in the transport system. The observed data includes the choices actually made by users. This paper investigates how sentiment analysis of data available in social media can be adopted to specify, calibrate, and validate demand models in certain choice levels. In this work a model based on the Bayesian approach is specified, calibrated, and validated in the case of bike preference in some Italian metropolitan cities. The model takes into account the discrete choice approach. Specification, calibration, and validation made it possible to identify the relevant variables that influence sentiments and obtain the posterior distribution probability of the parameters. The prior and the posterior conditional probabilities are compared, and some indications are obtained on the elasticity and weight of the sentiments that influence the choice.

Given two pick-up and delivery points, the best path chosen does not necessarily follow the criteria of minimum travel time or generalized minimum cost evaluated with a deterministic approach. Given a criterion, the perceived cost is not deterministic for many reasons (congestion, incomplete information on the state of the system, inexact prediction of the system state, etc.). The same consideration applies to the best-chosen route, assuming that the route is an ordered list of network nodes to visit. The paths and routes perceived and chosen (drivers or companies) could follow different criteria (i.e., minizmum congested travel time for the path and minimum monetary cost for the route). In this context, the paths chosen between two pick-up and delivery points, studied with the path choice problem (PCP), influence the best route, studied with the vehicle routing problem (VRP). This paper reports some considerations on the importance of modelling the path choice behavior in the VRP; the influence of the PCP on the VRP is studied. The considerations are supported by a numerical example in a small network in which the results obtained by adopting the deterministic or probabilistic models for the PCP are compared. To validate the reported thesis, the models are applied in a small test system, and it allows the reader to follow the numerical results step by step.

Passenger mobility plays an important role in today’s society and optimized transport services are a priority. In recent years, MaaS (Mobility as a Service) has been studied and tested as new integrated services for users. In this paper, MaaS is studied considering the sustainability objectives and goals to be achieved with particular reference to the consolidated methodologies adopted in the transport systems engineering for design, management, and monitoring of transport services; it is defined as Sustainable MaaS (S-MaaS). This paper considers the technological and communication platform essential and assumed to be a given considering that it has been proposed in many papers and it has been tested in some areas together with MaaS. Starting from the MaaS platform, the additional components and models necessary for the implementation of an S-MaaS are analyses in relation to: a Decision Support System (DSS) that supports MaaS public administrations and MaaS companies for the design of the service and demand management; a system for the evaluation of intervention policies; and also considers smart planning for a priori and a posteriori evaluation of sustainability objectives and targets.

This research concerns the topic of Land Use and Transport Interaction (LUTI) models. In particular, the patterns between residential households’ location and mobility choices are analyzed and simulated. The attributes that influence household residential location choices belong to four categories: socioeconomic and mobility attributes of households and/or of their components; land use; real-estate market; transport system. The paper presents the results of a pilot study on households’ location and mobility patterns in the metropolitan area of Reggio Calabria (Southern Italy). The pilot study is divided into two stages. In the first stage, a survey allowed to collect information and identify existing patterns about residential and mobility choices of a sample of households. In the second stage, a residential location model is proposed and some preliminary calibrations are presented in a prototypal way. The pilot study could be extended and improved in terms of spatial extension and sample dimension in order to allow a complete specification-calibration-validation process of the model. The model development can support the land use-transport planning process in the Metropolitan City of Reggio Calabria.

This paper focuses on the estimation of energy consumption of Electric Vehicles (EVs) by means of models derived from traffic flow theory and vehicle locomotion laws. In particular, it proposes a bi-level procedure with the aim to calibrate (or update) the whole parameters of traffic flow models and energy consumption laws by means of Floating Car Data (FCD) and probe vehicle data. The reported models may be part of a procedure for designing and planning transport and energy systems. This aim is to verify if, and in what amount, the existing parameters of the resistances/energy consumptions model calibrated in the literature for Internal Combustion Engines Vehicles (ICEVs) change for EVs, considering the above circular dependency between supply, demand, and supply–demand interaction. The final results concern updated parameters to be used for eco-driving and eco-routing applications for design and a planning transport system adopting a multidisciplinary approach. The focus of this manuscript is on the transport area. Experimental data concern vehicular data extracted from traffic (floating car data and probe vehicle data) and energy consumption data measured for equipped EVs performing trips inside a sub-regional area, located in the Città Metropolitana of Reggio Calabria (Italy). The results of the calibration process are encouraging, as they allow for updating parameters related to energy consumption and energy recovered in terms of EVs obtained from data observed in real conditions. The latter term is relevant in EVs, particularly on urban routes where drivers experience unstable traffic conditions.

The paper deals with the integration of data provided from traditional transport surveys (small data) with big data, provided from Information and Communication Technology (ICT), in building Transport System Models (TSMs). Big data are used to observe historical mobility patterns and transport facilities and services, but they are not able to assess ex-ante effects of planned interventions and policies. To overcome these limitations, TSMs can be specified, calibrated and validated with small data, but they are expensive to obtain. The paper proposes a procedure to increase the benefits of TSMs’ building in forecasting capabilities, on one side; and limiting the costs connected to traditional surveys thanks to the availability of big data, on the other side. Small data (e.g., census data) are enriched with Floating Car Data (FCD). At the current stage, the procedure focuses on two specific elements of TSMs: zoning and graph building. These processes are both executed considering the estimated values of an intensity function of FCDs, consistently with traditional methods based on small data. The data-fusion of small and big data, operated with a Geographic Information System (GIS) tool, in a real extra-urban context is presented in order to validate the proposed procedure.