1,720,966 research outputs found
A novel technology in freight transportation for improvement of the environmental impact
Full text linkNew technological innovations of eco-friendly vehicles combined with the usage of renewable energy sources showed significant results in mitigating emissions. In this thesis, we consider the eHighway system, a recent technology based on electrified roads. It is designed to supply new hybrid trucks, i.e. electric overhead catenary (OC) trucks, which are connected to overhead power lines through a pantograph positioned at the top of the vehicle. The eHighway implementation can result in lower emission vehicles’ rate since the vehicles are operating with electric mode. Therefore, in this thesis, we present a single-level multi-objective network design model and a bi-level multi-objective network design model considering a novel technology, the eHighway system. The proposed models investigate the opportunities of adopting eHighways and evaluating its environmental benefits considering limited budget resources for infrastructure electrification. Additionally, the models could be considered as useful tools for decision-makers in eHighway network planning and design.
For developing both models, a simulation model presented in the literature was used to calculate the number of traction substations needed for arc electrification according to hybrid trucks flows. As a first approach, in the case of the single-level multi-objective network design model, we propose a formulation including three objectives: minimisation of infrastructure and environmental costs, maximisation of average traffic density of OC hybrid trucks on electrified arcs. The Pareto optimisation approach is considered for a comprehensive analysis of all possible solutions according to different criteria weights. This model served as a basis to construct a bi-level multi-objective network design model that also considers the possibility of increasing the capacity of electrified arcs to improve overall network performances. Thus, in the case of the bi-level network design model we considered four objectives in the upper level related to the minimisation of the total Overhead Catenary (OC) hybrid trucks’ travel time, infrastructure and environmental costs and maximisation of average traffic density of OC hybrid trucks on electrified arcs. The decision of the upper level depends on the output of the lower level which is formulated as a Stochastic Users Equilibrium traffic assignment based on a fixed-point problem. Moreover, the proposed bi-level network design model deals not only with finding the set of the arcs to be electrified but also with the capacity expansion of the electrified arcs for improving the performance of the overall system. Additionally, genetic algorithms were used as a solution approach, which demonstrated the effectiveness in finding the near-optimal results in a reasonable computation time. The proposed models have been tested on a medium-sized network and the Sioux-Falls network. In particular, we analysed the Pareto front obtained from the single-level model, where non-dominant solutions are identified according to the three considered criteria. Moreover, a sensitivity analysis is carried out for the bi-level problem in terms of criteria weights and the percentage of hybrid vehicles using the eHighway system. Numerical results quantified the environmental improvement we can obtain by using the eHighway system in both models, which can be a basis for making decisions regarding the adoption of this new technology
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
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
A multi-objective model to design shared e-kick scooters parking spaces in large urban areas
Full text linkIn recent years, the micromobility and the usage of shared electric kick scooters (e-kscooters) have been constantly growing, especially for systematic and recreational trips in large urban areas. Micromobility might be seen as a well-suited last-mile solution by providing a flexible travel service connection with public transport and MaaS (Mobility as a Service), in general. However, there is a need for implementing adequate regulations regarding safety aspects and shared e-kscooter parking locations, but also for meeting the user requirements. The choice of optimal shared e-kscooter parking locations could help decision-makers to regulate unmanaged dock-less shared e-kscooter parking spots that could generate issues for other road users. To this end, in this paper, a novel multi-objective Micromobility Maximal Coverage Parking Location model (M-MCPL) is developed. The model has been solved by applying an elitist Genetic Algorithm that returns the optimal shared e-kscooter parking locations based on the following objective functions: i) the maximization of the population coverage; ii) the maximization of multimodal accessibility coverage (i.e., bus, railway, and metro modes); iii) the maximization of the attraction coverage considering the most relevant points of interest for each corresponding zone in large urban areas. The proposed M-MCPL model has been applied to the case of Rome (Italy) and results suggest priorities for the shared e-kscooter parking locations design. Furthermore, the proposed model is flexible and can be considered as a decision support tool for decision-makers when planning dedicated services in different large urban areas. For that purpose, we conducted the sensitivity analysis by focusing on the single-objective model in which decision-makers might be interested in providing only high accessibility to transport services or maximizing potential demand
A green logistics solution for last-mile deliveries considering e-vans and e-cargo bikes
Full text linkThe environmental challenges and the initiatives for sustainable development in urban areas are mainly focused on eco-friendly transportation systems. Therefore, we introduce a new green logistics solution for last-mile deliveries considering synchronization between e-vans and e-cargo bikes, developed as a Two-Echelon Electric Vehicle Routing Problem with Time Windows and Partial Recharging (2E-EVRPTW-PR). The first echelon represents an urban zone, and the second echelon represents a restricted traffic zone (e.g., historical center) in which e-vans in the first and e-cargo bikes in the second echelon are used for customers’ deliveries. The proposed 2E-EVRPTW-PR model aims to minimize the total costs in terms of travel costs, initial vehicles’ investment costs, drivers’ salary costs, and micro-depot cost. The effectiveness of the proposed solution has been demonstrated comparing two different cases, i.e., the EVRPTW-PR considering e-vans for the first case, and the 2E-EVRPTW-PR considering e-vans and e-cargo bikes for the second case. The comparison has been carried out on existing EVRPTW-PR instances for the first case, and on novel 2E-EVRPTW-PR instances for the second case, in which customers of initial EVRPTW-PR instances have been divided into two zones (urban and restricted traffic zones) by using Fuzzy C-mean clustering. Moreover, results encourage logistics companies to adopt zero-emission strategies for last-mile deliveries, especially in restricted traffic zones
Zero-emission vehicle adoption towards sustainable e-grocery last-mile delivery
Full text linkIn recent years, sustainable eco-friendly vehicles have been demonstrated as an adequate solution for urban deliveries and restricted areas facing traffic congestion and traffic zone limitation. Therefore, in this paper, a novel Decision Support System has been proposed for evaluating the efficiency of e-grocery home delivery through eco-friendly vehicle adoption. A mathematical model, formulated as Electric Vehicle Routing Problem with Time Windows and Partial Recharging (EVRPTW-PR), has been applied for selecting the best zero-emission vehicle for e-grocery home delivery. The comparison of the most emerging electric light-duty vehicles (e-cargo bikes, e-mopeds, and e-vans) has been carried out through key performance indicators related to the drivers’ salary, the total delivery time, the fuel (energy) costs, the vehicle investment costs, and the average payload capacity utilization. The overall evaluation encourages the adoption of zero-emission strategies and helps e-grocery commerce to adopt the best option that fits with the environmental as well as the economic aspects
An equality-based model for bike-sharing stations location in bicycle-public transport multimodal mobility
No full textBike-sharing systems can be implemented to complete the coverage of public transport networks which could be insufficient to serve an entire urban area. Some methodologies that maximise coverage or accessibility are suggested in the literature. In this paper, we propose a bike-sharing stations location model that includes not only these issues but also equality aspects. The model aims to minimise inequalities in bicycle-public transport mobility among observed population groups trying to maintain specified levels of accessibility and coverage at the same time. We evaluated the performance of the model on a test network and carried out a sensitivity analysis according to the available budget. The results showed that maximising accessibility or coverage alone, without considering equality, may lead to an unequal distribution of accessibility among the population, producing discrimination between different groups. The outcomes of the application revealed the significance of the model in evaluating equality in the network design phase for achieving not only a satisfactory bike-sharing system and public transport multimodal accessibility of each zone but also a high equality measure among the considered population groups. Budget availability also played an essential role since a minimum budget value is needed to achieve higher levels of equality. The proposed approach could serve transport and public authorities as a decision support system in planning future investment as well as promoting multimodal mobility because it links bike-sharing stations with stops/stations of the public transport lines networks
An efficiency indicator for micromobility safety assessment
No full textMicromobility has been revealed as one of the effective solutions in urban areas for mitigating emissions as well as private car usage. However, the choice to travel by micromobility has been often limited due to safety risks. For this reason, we proposed an indicator that evaluates the safety-based efficiency of urban areas zones, related to micromobility and based on a Data Envelopment Analysis model. An efficiency value between zero and one is associated with each zone of the studied area. This value is calculated as a function of micromobility accident-related factors such as road intersections, vehicles speed, and the presence of cycleways. Based on this efficiency indicator and a proposed decision support system, local public authorities can take actions to mitigate the risk of accidents with infrastructure improvements or by enforcing reduced speed limits, for example through the use of geofencing in shared micromobility systems. The proposed indicator and the decision support system have been applied to the city of Bari, Italy, also performing sensitivity analyses on the methodology parameters. The obtained results show how our proposal can help decision-makers to set up necessary actions for improving micromobility safety for specific cities zones
An eco-friendly Decision Support System for last-mile delivery using e-cargo bikes
No full textReal-time information and software support systems are crucial points for performing efficient logistics operations. Recently, most of the logistics companies have been using green-logistics solutions that encourage the use of eco-friendly vehicles, especially cargo bikes. However, for evaluating logistics' business performance, driver's exposure to emissions has often been neglected. Therefore, we proposed a Decision Support System (DSS) that considers, on the one hand, the efficiency of logistics performance and, on the other, the possibility of e-cargo bike drivers to choose the optimal route path considering two options, such as minimum travel time and minimum emission exposure. We applied the proposed DSS in a numerical application that evaluates the customer's assignment to an e-cargo bike according to the hourly traffic flows and emissions. We developed a dynamic algorithm that evaluates the path choice comparison between two route options. The choice of the minimum emission path compared with the shortest travel time path leads to a slight increase in the total travel time. The final path choice, according to the driver's opinion, was obtained using the Fuzzy Inference System (FIS). Moreover, the proposed DSS serves as a general framework for a decision-making process that could be applied to various two-wheels light-duty vehicles for last-mile delivery
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