Detailing DRT users in Europe over the last twenty years: a literature overview

Travel choices in terms of means of transport and frequencies have changed during the recent pandemic period due to mobility restrictions, the growing fear of contagion and, especially in some months, the reduction of public transport capacity during the phases of the pandemic (especially for low demand areas). These trends must be analysed in order to optimize the implementation of possible complementary solutions to fill the deficit of local public transport (TPL) by introducing for example the Demand Responsive Transport services (DRT). A preliminary analysis is useful to identify the most efficient, effective and sustainable solutions in the various contexts, taking into account users and their motivation to travel. A growing need for "on-demand" mobility is linked to the increase in the number of elderly and disabled people. With a lack of alternative services and a reluctance to bear the burden and cost of ownership of vehicles, transport infrastructure will be particularly important to this aging population. Therefore, the improvement of transport services must consider some main characteristics of this modal choice are: being user-oriented;guarantee the accessibility of the service via the web, on specific platforms available on fixed and mobile devices and also enjoy the versatility of use with reference to the areas and users to be served. The present work, therefore, focuses on an evaluation of the literature, defining the main characteristics of DRT in Europe over the last twenty years. The results lay the foundations for a better planning of the service in the post-pandemic phase and a diffusion of bottom-up approaches for the calibration of the service itself through the dissemination of survey campaigns. © 2023 The Authors. Published by ELSEVIER B.V.

Detailing DRT users in Europe over the last twenty years: a literature overview

Travel choices in terms of means of transport and frequencies have changed during the recent pandemic period due to mobility restrictions, the growing fear of contagion and, especially in some months, the reduction of public transport capacity during the phases of the pandemic (especially for low demand areas). These trends must be analysed in order to optimize the implementation of possible complementary solutions to fill the deficit of local public transport (TPL) by introducing for example the Demand Responsive Transport services (DRT). A preliminary analysis is useful to identify the most efficient, effective and sustainable solutions in the various contexts, taking into account users and their motivation to travel. A growing need for "on-demand" mobility is linked to the increase in the number of elderly and disabled people. With a lack of alternative services and a reluctance to bear the burden and cost of ownership of vehicles, transport infrastructure will be particularly important to this aging population. Therefore, the improvement of transport services must consider some main characteristics of this modal choice are: being user-oriented;guarantee the accessibility of the service via the web, on specific platforms available on fixed and mobile devices and also enjoy the versatility of use with reference to the areas and users to be served. The present work, therefore, focuses on an evaluation of the literature, defining the main characteristics of DRT in Europe over the last twenty years. The results lay the foundations for a better planning of the service in the post-pandemic phase and a diffusion of bottom-up approaches for the calibration of the service itself through the dissemination of survey campaigns. © 2023 The Authors. Published by ELSEVIER B.V.

The microsimulation modeling as a tool for transport policies assessment: An application to a real case study

Nowadays, alongside the traditional statistical and semi-probabilistic methods, through which it is possible to obtain an estimate of the road network performances whatever its geometric-functional configuration, the use of microscopic traffic simulation techniques is widespread, allowing a "dynamic"approach to the problem (e.g. evaluation of infrastructural interventions, traffic management, etc.). The traffic micro-simulation models are able to analyze and process, instant by instant, the movement of single vehicles on the network, on the basis of laws related to the vehicle movement and the driving behavior. Based on this premise, this study proposes an overview of traffic simulation models, with a focus on the advantages of microsimulation. In this direction, the paper presents an application to a real case study in the city of Catania (Italy), in order to evaluate the impact of different traffic regulation strategies in terms of level of service (LoS), road emissions and fuel consuption through scenario evaluations. First results demonstrates that traffic modeling and the implementation of microsimulation tools represent a valid support for the transport policies assessment, providing a basis for future research steps that will address the simulation of larger areas, through before and after analysis and the evaluation of different key performance indicators. © 2022 Author(s).

Simulating pandemic emergency scenarios considering mobility patterns through an agent-based model

One of the main policies to contain a pandemic spreading is to reduce people mobility. However, it is not easy to predict its actual impact, and this is a limitation for policy-makers who need to act effectively and timely to limit virus spreading. Data are fundamental for monitoring purposes;however, models are needed to predict the impact of different scenarios at a granular scale. Based on this premise, this paper presents the first results of an agent-based model (ABM) able to dynamically simulate a pandemic spreading under mobility restriction scenarios. The model is here used to reproduce the first wave of COVID-19 pandemic in Italy and considers factors that can be attributed to the diffusion and lethality of the virus and population mobility patterns. The model is calibrated with real data (considering the first wave), and it is based on a combination of static and dynamic parameters. First results show the ability of the model to reproduce the pandemic spreading considering the lockdown strategy adopted by the Italian Government and pave the way for scenario analysis of different mobility restrictions. This could be helpful to support policy-making by providing a strategic decision-tool to contrast pandemics. © 2021 Copyright for this paper by its authors.

A New Vision on Smart and Resilient Urban Mobility in the Aftermath of the Pandemic: Key Factors on European Transport Policies

Recent events related to the COVID-19 pandemic event highlighted some criticalities of transport systems, especially the public sector. The respect for social distancing and a widespread fear of contagion have reduced travel on public transport. In addition, the new trend to reduce daily long-range mobility needs due to the increase in teleworking is present. Following the pandemic, there has been a paradigm shift, from smart cities to smart and sustainable cities (SSCs) in which a new concept of

Exploring the Factors that Encourage the Spread of EV-DRT into the Sustainable Urban Mobility Plans

The development of sustainable mobility is linked to technological developments and different forms of vehicle power supply. Despite all the difficulties brought by the COVID-19 pandemic, therefore, it is necessary to provide road users with an adequate network of public recharging infrastructures and to facilitate the setting-up of private recharging stations through shared and participatory development plans between the stakeholders and all the institutions involved. The present work introduces an analysis of some of the European Sustainable Urban Mobility Plans (SUMPs) and the transport supply connected to several cities. After an evaluation of the macro areas of intervention, factors and criteria for the deployment of the electric vehicle linked to the demand responsive transport choice (EV-DRTs) have been defined in terms of user classification and environmental factors, but also considering the services and infrastructures for electric charging. The identification of these factors and criteria allows an exemplification in the development and adaptation of the planning and design concept. © 2021, Springer Nature Switzerland AG.

A novel methodology for epidemic risk assessment of COVID-19 outbreak.

We propose a novel data-driven framework for assessing the a-priori epidemic risk of a geographical area and for identifying high-risk areas within a country. Our risk index is evaluated as a function of three different components: the hazard of the disease, the exposure of the area and the vulnerability of its inhabitants. As an application, we discuss the case of COVID-19 outbreak in Italy. We characterize each of the twenty Italian regions by using available historical data on air pollution, human mobility, winter temperature, housing concentration, health care density, population size and age. We find that the epidemic risk is higher in some of the Northern regions with respect to Central and Southern Italy. The corresponding risk index shows correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can help explaining why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto have suffered much more than the rest of the country. Although the COVID-19 outbreak started in both North (Lombardia) and Central Italy (Lazio) almost at the same time, when the first cases were officially certified at the beginning of 2020, the disease has spread faster and with heavier consequences in regions with higher epidemic risk. Our framework can be extended and tested on other epidemic data, such as those on seasonal flu, and applied to other countries. We also present a policy model connected with our methodology, which might help policy-makers to take informed decisions.