1,720,993 research outputs found
TIS Roma 2019 Conference Proceedings. Transport Infrastructure and systems in a changing world. Towards a more sustainable, reliable and smarter mobility.
No full textEditorial of TIS Conference Proceedings, Transport Infrastructure and Systems in a changing world, ACI - Automobile Club d'Italia Building, Rome, Italy - September 23-24, 201
Addressing the public transport ridership/coverage dilemma in small cities: A spatial approach
No full textThis paper presents a spatial approach to support the design of new on-demand flexible transport services in urban areas, characterized by inefficient public transport and modal imbalance in favour of private cars. These services, enabled by new technologies and inspired by the shared mobility paradigm, can complement and improve conventional public transport and reduce car use. The methodology was applied to Acireale, a small town in Southern Italy. A redesign of the existing bus network and its integration with a flexible service was formulated. A scenario analysis was carried out by the evaluation of a simple accessibility measure; the computation of the Gini coefficient was performed to measure the social equity of different scenarios. Results show an increase in equity with a lower coverage of traditional lines and the introduction of the on-demand service. This approach based on easy-to-understand indicators can help the strategic planning of such services, which have the potential to find a trade-off between ridership and coverage as both desirable and conflicting goals in public transport planning
Designing microtransit services in suburban areas: A case study in Palermo, Italy
Full text linkPoor quality of Public Transport (PT) services is one of the main causes of social exclusion for people living in the suburbs. Public transport companies usually allocate few financial resources to these areas, providing transport services with low frequency, poor accessibility, poor reliability, and high waiting times at stops. Recently, microtransit has emerged as an effective solution to improve the travel experience in suburban areas, particularly for non-commuting trips during off-peak hours. This paper presents an integrated methodological approach for designing microtransit services to meet the mobility needs of people living in low-density suburbs. By conducting a Reveled Preference (RP) and Stated Preference (SP) survey and developing a travel demand model, the demand was estimated and used as input to simulate and size the service. Combining GIS and simulation models, Key Performance Indicators (KPIs) were assessed; fleet size to meet the trip requests was identified and the fare was selected using a sensitivity analysis. The method was applied to a real case study to design a new microtransit service with flexible routes and on-demand stops in a suburban area in Palermo, Italy. The results highlight how introducing a microtransit service with 30 nine-seater vans could change the mobility habits of people living in the suburban area, being attractive and financially sustainable if costing 2 €, or just a little more than the existing fixed-route bus service. It could improve the travel experience by reducing the average waiting time at stops to around 5 min and improve access to amenities and PT hubs by guaranteeing a walking time of maximum about 8 min
Transforming travel experience in low density areas: evidence from a DRT pilot study and simulation model
Full text linkIn low density areas, due to limited economic resources, public transport (PT) companies usually operate services with low frequency, poor accessibility and reliability and high waiting times at stops. Several studies highlighted that introducing Demand Responsive Transport Services (DRTs) can improve PT performance in these areas. In Italy, several DRTs have been launched, characterized by flexible schedules with different operational configurations: fixed route, with and without detours and flexible route. Considering the importance of sharing lessons from pilots, the paper presents a DRT pilot study, conducted in Palermo (Italy) within the WEAKI TRANSIT project, identifying strategies for planning and designing on-demand shared systems. The pilot was conducted in a suburban area in the north of Palermo, covering about 10.5 km2 with the neighbourhoods of Partanna Mondello and Tommaso Natale. This area is poorly served by PT companies with low-frequency and low-reliability bus lines, thus a stop-based DRT service with two fixed routes and detours was hypothesized. The pilot was conducted during November and December 2022, with four cars, operating from 3 to 7 p.m., except Sunday. The service, free of charge, was addressed to students and teaching staff by University of Palermo. Through SP surveys, simulation model and pilot, we evaluate operational performance of the services (i.e. travel distance, waiting and in-vehicle times). We found the introduction of DRTs lead to increasing accessibility to main transit hubs and facilities, and a decrease in waiting times at stops and travel times. Nevertheless, considerations about financial feasibility and legal framework are highlighted
Exploring the impact of mobility restrictions on the COVID-19 spreading through an agent-based approach
Full text linkBackground: The recent health emergency caused by the COVID-19 pandemic forced people to change their mobility habits, with the reduction of non-essential travels and the promotion online activities. During the first phase of the emergency in 2020, governments considered several mobility restrictions to avoid the pandemic diffusion. However, it is difficult to quantify the actual effects of these restrictions on the virus spreading, especially due to the biased data available. Notwithstanding the big role of data analysis to understand the pandemic phenomenon, it is also important to have more general models capable of predicting the impact of different policy scenarios, including territorial parameters, independently from the available infection data. In this respect, this paper proposes an agent-based model to simulate the impact of mobility restrictions on the spreading of the COVID-19 at a large scale level, by considering different factors that can be attributed to the diffusion and lethality of the virus and population mobility patterns. Methods: The first step of the method includes a zonation of the study area, according to administrative boundaries. A risk index is calculated for each zone considering indicators which can influence the virus spreading and people lethality: mean winter temperature, housing concentration, healthcare density, population mobility, air pollution and the percentage of population over 60 years old. The agent-based model associates the risk index to the agents and determines their “status” (“susceptible”, “infected”, “isolated”, “recovered” or “dead”) by combining the risk index with the mean infection duration, using a SIR-based approach (i.e. susceptible–infective-removed). Results: The study is applied to Italy. Several scenarios based on different mobility restrictions have been simulated, including the one based on the official data (status quo). The main results show that characterizing zones with a risk index allows to adopt local policies with almost the same effectiveness as in the case of restrictions extended to the full study area; scenario simulations return an increase in terms of infected (+20%) and deaths (+25%) with respect to the status quo. These results underline the importance of finding a trade-off between socio-economic benefits and health impact. Conclusions: The reproducibility of the proposed methodology and its scalability allow to apply it to different contexts and at a different administrative level, from the urban scale to a national one. Moreover, the model is able to provide a decision-support tool for the design of strategic plans to contrast pandemics based on respiratory diseases
Participatory decision-support tools for stakeholder engagement in urban freight transport policy making
No full textDesigning demand responsive transport services in small-sized cities using an agent-based model
Full text linkThis paper presents an agent-based model (ABM) to simulate and compare two different operation strategies of a public transport service in small-sized cities, namely a fixed-route transit (FRT) and a demand-responsive transport (DRT) service, under varying demand rates and supply configurations. The ABM builds upon a previous work by the Authors, where flexible and feeder services of a Mass Rapid Transit system were simulated. In this paper, instead of a many-to-one pattern typical of a feeder service, we considered a many-to-many one. The objective is to investigate the conditions that make a DRT more attractive than a FRT in small-sized cities and guide its design considering the demand fluctuation, land-use pattern, service constraints and passenger preferences. A dispatching algorithm for the DRT allows to assign each new trip request to a vehicle, and a couple of origin and destination stops, updating the vehicle schedule in real time. The service includes fixed and virtual stops, allowing request consolidation and balancing operator-related (cost of the service) and user-related (quality of service) needs. The model is applied to Vittoria (Italy), a small city with 60,000 residents in Southern Italy where most trips are made by car, also due to the absence of an urban public transport service. First results highlight the benefits of providing a flexible service compared to a fixed one to minimize detours, waiting times and walking distances experienced by passengers while allowing for a higher shareability and efficiency of the service.Transport and Plannin
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