1,720,993 research outputs found
An integrated bus transit service for demand-responsive urban public transport
Full text linkRecent mobility reports have highlighted the need of integrating Information and Communication Technologies (ICT) as an essential element in the development of intermodal and on-demand services to enhance transport flexibility. In this context, this paper investigates the improvements that could be obtained by integrating Dial-a-Ride into a bus transit service. We model the problem as a dynamic Dial-a-Ride problem with both fixed and dynamic requests. We extend an integer linear programming (ILP) model for its application to the dynamic case. To reduce computational effort, the problem is decomposed at the single vehicle level, where each best route is computed using an exact solver and new dynamic requests are assigned using a greedy insertion heuristic. We have developed the optimization model as a GIS-based tool and applied it to a realistic case of a bus transit service in the city of Benevento (Italy). The results show the benefits that could be obtained with the proposed integrated service when also compared to fixed routes and micro-mobility
A novel mathematical formulation for solving the dynamic and discrete berth allocation problem by using the Bee Colony Optimisation algorithm
Full text linkBerth allocation is one of the crucial points for efficient management of ports. This problem is complex due to all possible
combinations for assigning ships to available compatible berths. This paper focuses on solving the Berth Allocation Problem
(BAP) by optimising port operations using an innovative model. The problem analysed in this work deals with the Discrete and
Dynamic Berth Allocation Problem (DDBAP). We propose a novel mathematical formulation expressed as a Mixed Integer
Linear Programming (MILP) for solving the DDBAP. Furthermore, we adapted a metaheuristic solution approach based on the
Bee Colony Optimisation (BCO) for solving large-sized combinatorial BAPs. In order to assess the solution performance and
efficiency of the proposed model, we introduce a new set of instances based on real data of the Livorno port (Italy), and a
comparison between the BCO algorithm and CPLEX in solving the DDBAP is performed. Additionally, the application of the
proposed model to a real berth scheduling (Livorno port data) and a comparison with the Ant Colony Optimisation (ACO)
metaheuristic are carried out. Results highlight the feasibility of the proposed model and the effectiveness of BCO when
compared to both CPLEX and ACO, achieving computation times that ensure a real-time application of the method
Managing the Uncertainty of Data Fusion from Different Sources in Modelling Route Choice Behaviour
No full textIn this paper, a method for fusing data relevant both to drivers’ experience and provided information about travel time is presented. The method takes into account the “compatibility” of data originating from different sources, and provides information about acceptability of results. The influence of uncertainty on drivers’ compliance with provided information is examined in detail, according to the Uncertainty-based Information Theory. The data fusion results then in an updating of the expected travel time. Finally, the travelers compare the updated travel times of alternatives and choose, among them, the best one from their point of view. The proposed model has been applied to a test network where two different information sources have been considered. Results highlight the effectiveness of the model in quantifying and simulating drivers’ compliance with information
Towards the electrification of freight transport: A network design model for assessing the adoption of eHighways
Full text linkThe development of new technological innovations for eco-friendly vehicles combined with the usage of renewable energy sources is essential for mitigating the environmental impact of freight transport. In this context, this paper investigates the opportunities for implementing the eHighway system, a novel recent technology designed to supply new hybrid trucks. This technology uses overhead catenary heavy-duty vehicles that are supplied with electric energy from overhead power lines through a pantograph that is positioned at the top of the truck. A novel bi-level multi-objective network electrification design (BM-NED) model is proposed to assess the environmental benefits and opportunities of adopting eHighways, considering the limited budgetary resources for road infrastructure electrification. Still, the implementation of eHighways requires collaboration between public and private stakeholder interests. The upper level considers multiple objectives aiming at minimizing the total travel cost, infrastructure, and environmental costs and maximizing the average traffic density of OC hybrid trucks on electrified arcs, whereas the lower level is the traffic assignment model. The Elitist multi-objective Genetic Algorithms are used as a solution approach for the multi-objective optimization and the Pareto front of the non-dominated solutions have been generated. Results of the model, tested on a part of a motorway network in the Veneto region in Italy, show that the implementation of the eHighway system can lead to an average emission reduction of about 66%, considering all Pareto-optimal solutions. Furthermore, a sensitivity analysis has been carried out by giving different weights to the objective functions that can be a basis for decision-makers regarding the adoption of this new technology
A multi-objective network design model for road freight transportation using the eHighway system
Full text linkNew technological innovations of eco-friendly vehicles for freight transport combined with the usage of renewable energy sources showed significant results in mitigating transport-related carbon footprint. Therefore, in this paper, we present a multi-objective network design model considering a novel technology, the eHighway system, based on electrified roads to supply new Overhead
Catenary (OC) hybrid trucks. This work investigates the opportunities of adopting eHighways and evaluates its environmental benefits considering limited budget resources for infrastructure electrification. We propose an optimization problem formulation including three objectives: the minimization of infrastructure and environmental costs, and the maximization of the total number
of OC hybrid trucks served on electrified arcs. The Pareto optimization approach is considered for a comprehensive analysis of all possible solutions according to different criteria weights. The proposed model has been evaluated on a test network and the numerical results of Pareto optimization show the environmental improvement we can obtain by using the eHighway system up to
about 99% according to the assumed available budget and assigned criteria weights. As a result, the model can be considered as a useful tool for decision-makers in the eHighway network design
Bee Colony Optimization for innovative travel time estimation, based on a mesoscopic traffic assignment model
Full text linkIn this article, we propose a framework for travel time prediction based on a time-discrete, mesoscopic traffic flow model, in which the measure of travel time is obtained as a link performance resulting from a dynamic network loading process. The spatiotemporal flow propagation on the road network is simulated incorporating the mesoscopic model and a linear link performance model, based on a travel time function. Acceleration levels are calculated explicitly, as a result of a fixed point problem. The traffic assignment to the network has been carried out through a completely new model, based on the Bee Colony Optimization (BCO) metaheuristics. In comparison with results of simulations carried out by using another mesoscopic model (DYNASMART), the travel times obtained with the proposed method appear more realistic
Optimal location of vertiports in urban areas: the case study of Bari (Italy)
No full textNew emerging mobility technologies are seen as an adequate solution in urban areas for reducing traffic congestion and emissions, as well as enhancing better connectivity and accessibility of significant zones in urban areas. For instance, recent advancements in Urban Air Mobility (UAM) have opened the possibility of improving transportation services, especially in zones that require higher accessibility or faster inter-city connections. In this context, the design and location of UAM ground infrastructures, namely vertiports, are perceived as one of the main aspects of this novel service. Thus, this work proposes a model based on the Maximum Coverage Location Problem (MCLP) for determining optimal locations for vertiports in urban areas for parcel delivery. The model aims at maximizing the demand coverage of each vertiport within a predefined service/distance range. As a case study, the urban area of the city of Bari was considered to evaluate the outcomes of the proposed model. Moreover, a sensitivity analysis has been carried out by constructing different scenarios associated to different demand attributes and number of vertiports. The obtained results highlight the importance of considering the main practical recommendations and aspects that influence vertiports' location and potential UAM demand growth in Bari
Sustainable Mobility: A Review of Possible Actions and Policies
Full text linkIn this paper, a review of the main actions and policies that can be implemented to promote sustainable mobility is proposed. The work aims to provide a broad, albeit necessarily not exhaustive, analysis of the main studies and research that from different points of view have focused on sustainable mobility. The structure of the paper enables the reader to easily identify the topics covered and the studies related to them, so as to guide him/her to the related in-depth studies. In the first part of the paper, there is a preliminary analysis of the concept of sustainable mobility, the main transport policies implemented by the European Union and the USA, and the main statistical data useful to analyze the problem. Next, the main policies that can promote sustainable mobility are examined, classifying them into three topics: Environmental, socio-economic, and technological. Many of the policies and actions examined could be classified into more than one of the three categories used; for each of them, there is a description and the main literature work on which the topic can be analyzed in more detail. The paper concludes with a discussion on the results obtained and the prospects for research
The Use of Hydrogen for Traction in Freight Transport: Estimating the Reduction in Fuel Consumption and Emissions in a Regional Context
Full text linkThe Italian National Recovery and Resilience Plan (NRRP) includes, among other measures, investments in hydrogen vehicle refuelling stations, intending to promote the use of fuel cell electric vehicles (FCEVs) for long-haul freight transport. This paper evaluates the impact that this action could have on CO2 emissions and fuel consumption, focusing on a case study of the Campania region. The proposed approach, which can also be transferred to other geographical contexts, requires the implementation of a freight road transport simulation model; this model is based on the construction of a supply model, the estimation of road freight demand, and an assignment procedure for computing traffic flows. This study covers the period from 2025 to 2040, according to the forecasts of the NRRP and some assumptions on the action effects; moreover, it is assumed that hydrogen is entirely produced from renewable sources (green hydrogen). The key findings from three different scenarios show that savings between 423,832 and 778,538 tonnes of CO2, and between 144 and 264 million litres of diesel could be obtained
Modeling the dynamic effect of information on drivers’ choice behavior in the context of an Advanced Traveler Information System
Full text linkIn this paper, we present a modeling approach, based on Fuzzy Data Fusion, to reproduce drivers’ dynamic choice behavior under an Advanced Traveler Information System (ATIS). The proposed model uses the Possibility Theory to model Uncertainty embedded in human perception of information. We have introduced a time-dependent Possibility Distribution of Information to model the users’ changing perception of travel time also based on current network conditions. Drivers’ choice models are often developed and calibrated by using Stated Preference (SP) surveys,
amongst others. In this work, we present an experiment to set up an SP-tool based on a driving simulator developed at the Polytechnic University of Bari. The results obtained by the proposed model are analyzed and compared with the driver dynamic behavior observed in the experimen
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