In this article, we argue that the term "sorting" (in MCDA), although established within a well-defined community, is unappropriate for linguistic, scientific and pragmatic reasons. We present and discuss such reasons and we suggest the use of the term "rating", since fitting better both the foundational part of this class of methods and the necessity to improve the visibility of our community.

Generating alternatives for decision problems is a critical activity regularly underestimated and underdeveloped in the decision analysis literature. We present a survey showing how little this topic has been studied in the last 50 years. We then introduce a general framework under which formalize the design of alternatives. Two examples help to understand our point of view: alternatives are generated through separation of attributes describing the value space of the client/decision maker.

This paper presents a general framework for the design of alternatives in decision problems. The paper addresses both the issue of how to design alternatives within “known decision spaces” and on how to perform the same action within “partially known or unknown decision spaces”. The paper aims at providing archetypes for the design of algorithms supporting the generation of alternatives.

The paper approaches the actual situation of carpooling, by reporting the most updated data divided by its different orms: private, corporate and urban carpooling. For this last kind some innovative experience are reported: instant carpooling, carpooling integrated with car sharing and with other transport modes. The potential of carpooling in the future scenario of disruptive technologies, such as the autonomous driving cars and the dynamic road charging is analyzed. Finally a proposal for some recommendations related to the user-centered approach and on the role of the different stakeholders.

This introductory chapter briefly outlines the main characteristics of car-sharing services and the main assumptions that authors of this book took into account for designing the innovative service that was the outcome of Green Move project. The second part of the chapter illustrates the overall organization of the book, and the main contents of the three sections: the service, focused on the Green Move service design, the technology, illustrating the technologic solutions realized for the project, and the simulation model, implemented for estimating the performances of different alternatives of car-sharing.

In this chapter, we summarise the main “lessons learned” that originated from the study and the onsite experimentation within the Green Move project. These are presented under the form of brief “guidelines” that may represent launching pads for a complete engineering of an advanced system of vehicle sharing. In the (relatively short, a little more than two years) duration of the project, the technologies and experiences of vehicle sharing underwent a noteworthy evolution which in any case appears to be in line with many of the points analysed. The remarks presented in this chapter represent a contribution for identifying the conditions, related to both the service model and the technology, for shifting from car ownership to vehicle sharing: providing this option to citizens is an essential aim that each city has to pursue as a first step for becoming a smart city.

Large-scale urban development projects featured over the past thirty years have shown some critical issues related to the implementation phase. Consequently, the current practice seems oriented toward minimal and widespread interventions meant as urban catalyst. This planning practice might solve the problem of limited reliability of large developments’ feasibility studies, but it rises an evaluation demand related to the selection of coalition of projects within a multidimensional and multi-stakeholders decision making context. This study aims to propose a framework for the generation of coalitions of elementary actions in the context of urban regeneration processes and for their evaluation using a Multi Criteria Decision Analysis approach. The proposed evaluation framework supports decision makers in exploring different combinations of actions in the context of urban interventions taking into account synergies, i.e. positive or negative effects on the overall performance of an alternative linked to the joint realization of specific pairs of actions. The proposed evaluation framework has been tested on a pilot case study dealing with urban regeneration processes in the city of Milan (Italy).

The paper presents the final results of the Italian pilots of Pro-E-Bike, a project funded under the Intelligent Energy Europe programme, started on April 2013 and ending on March 2016 (www.pro-e-bike.org). The project promotes clean and energy efficient vehicles, analyses the performance of electric bicycles and electric scooters for the delivering of goods in urban areas and tests the use of these vehicles in seven European countries with thirty-nine companies, both freight transport operators, companies that deliver their own products and services providers, in order to demonstrate that light electric vehicles can replace traditional combustion engine ones contributing on mitigating logistic impacts in urban areas. Pilots enabled the demonstration of measurable effects in terms of reduction of CO2 emissions and energy savings in urban transport: related data about environmental and social effects resulted by the introduction of e-bikes and e-scooters are shown, with a particular focus on the economic sustainability of these replacements. (C) 2016 The Authors. Published by Elsevier B.V.

Chapter 3 Cognitive Mapping and Multi-criteria Assessment for the Design of an Electric Car Sharing Service Alessandro Luè, Alessandro LuèSearch for more papers by this authorAlberto Colorni, Alberto ColorniSearch for more papers by this authorRoberto Nocerino, Roberto NocerinoSearch for more papers by this author Alessandro Luè, Alessandro LuèSearch for more papers by this authorAlberto Colorni, Alberto ColorniSearch for more papers by this authorRoberto Nocerino, Roberto NocerinoSearch for more papers by this author Book Editor(s):Michel André, Michel AndréSearch for more papers by this authorZissis Samaras, Zissis SamarasSearch for more papers by this author First published: 27 May 2016 https://doi.org/10.1002/9781119307761.ch3Citations: 1 AboutPDFPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShareShare a linkShare onFacebookTwitterLinked InRedditWechat Summary This chapter presents a model for the design of an electric car sharing service for the city of Milan. Several options of service configurations have been analyzed and evaluated according to indicators measuring the performance of such options in respect to relevant dimensions such as economic and financial costs and revenues, mobility, social benefits and environmental effects. Causal networks to estimate the effects of the options have been identified and instantiated by means of simulation techniques and other qualitative and quantitative models. The chapter focuses on the development and use of the causal maps and their integration with a multi-criteria assessment, based on the ELECTRE TRI rating method. The use of cognitive maps allows to capture the multiple values of the problem and the value trees of stakeholders' objectives. The proposed method can be useful for design of mobility services, especially at a strategic level. Citing Literature Energy and Environment, Volume 1 RelatedInformation

A significant role among soft mobility measures to influence people's mobility choices and to raise awareness is played by the provision of targeted information. The integration of user-centered design, social innovation, portable devices, and sensors may have a role in influencing people's choices and consumption patterns. The paper presents two ongoing works that investigate, design and develop tools for valuing people's positive behaviors and rewarding choices in the domain of mobility and energy. The objective of such tools is both to raise people's awareness and to engage it into a collaborative environment, in order to meet a common set of targets. The strategy adopted in both the cases is based on linking “bottom-up” with “top-down” approach, i.e. by making people to behave and to make choices coordinately with decision maker's (i.e. the Public Administration or the Administrator of the system) objectives. The first regards Opti-LOG, a project co-funded by Regione Lombardia under the Smart Cities and Communities program, which concerns last-mile delivery with low emission and zero emission vehicles. The second case regards Sharing Cities, a H2020 project that includes a pilot project in the Municipality of Milano, where the focus is on citizen engagement and behaviors in the domains of personal mobility and energy. The system, by enabling mechanisms of collaboration, sharing and human capital generation, tackles the objectives of lowering energy consumption and promoting sustainable mobility and contributes to the weaving of a more cohesive social tissue.

Research is a key factor for a successful reduction in greenhouse gas (GHG) emissions from transport. This article summarizes the main results of REACT, a project cofinanced by the European Commission, which aimed to develop a European Strategic Research Agenda for low GHG transport. A literature review and a multistage expert consultation process were used to map technological and nontechnological research areas and evaluate them according to different criteria (i.e., GHG emissions reduction, cost-efficiency, feasibility, time frame of research stages). We consulted the research agendas of the European Technologies Platforms on transport and current EU research programs. Expert opinions were collected through web forms, interviews, and participation in structured workshops. The REACT Research Agenda identified the following research priorities for a more climate-friendly transport system by 2030: (a) in the short term, cost-effective solutions consist of (1) more efficient, lighter vehicles with advanced internal combustion engines, (2) reducing road transport demand and (3) fostering GHG emission legislation; (b) in the medium/long term, the focus shifts toward (1) electric vehicles and hydrogen, (2) Intelligent Transport Systems, and (3) spatial planning and economic and social measures to reduce transport demand. In addition, one of the main findings identified strong links between technology research and planning, social sciences, and economy.

In recent years, the issue of vehicle road sharing has attracted growing attention from both researchers and operators, as a potential instrument to improve the sustainability of urban mobility or transport systems. Beside the general concept, different operational models, managerial and technological solutions have been developed, leading to a high diversification of possible vehicle sharing configurations. This heterogeneity entails a considerable complexity of the service design phase, though few academic contributions tackled this specific problem and most of the papers focused on the dynamics of adoption and use of the service itself. To fill such a gap, this paper aims to present the approach followed in the design phase of an electric vehicle sharing service for the city of Milano. The methodology adopted in this work is based on the idea that a vehicle sharing service needs to be configured to answer to specific mobility needs coherently with the characteristics of target customers. To explain this idea the methodology was articulated into four steps, which are reported in detail in this study: (i) mapping of mobility profiles and service performances, (ii) competitive analysis, (iii) development of the service configurations and (iv) development of the evaluation model.

Promoting the use of public transportation and Intelligent Transport Systems, as well as improving transit accessibility for all citizens, may help in decreasing traffic congestion and air pollution in urban areas. In general, poor information to customers is one of the main issues in public transportation services, which is an important reason for allocating substantial efforts to implement a powerful and easy to use and access information tool. This paper focuses on the design and development of a real time mobility information system for the management of unexpected events, delays and service disruptions concerning public transportation in the city of Milan. Exploiting the information on the status of urban mobility and on the location of citizens, commuters and tourists, the system is able to reschedule in real time their movements. The service proposed stems from the state of the art in the field of travel planners for public transportation, available for Milan. Peculiarly, we built a representation of the city transit based on a time-expanded graph that considers the interconnections among all the stops of the rides offered during the day. The structure distinguishes the physical stations and the get on/get off stops of each ride, representing them with two different types of nodes. Such structure allows, with regard to the main focus of the project, to model a wide range of service disruptions, much more meaningful than those possible with approaches currently proposed by transit agencies. One of the most interesting point lies in the expressive capability in describing the different disruptions: with our model it is possible, for instance, to selectively inhibit getting on and/or off at a particular station, avoid specific rides, and model temporary deviations.

The paper presents a conflict analysis in an environmental impact assessment. In order to cope with a problem of traffic congestion in a tourist area, alternative transportation services and measures of travel demand management are studied and compared using the multi-attribute value theory. The problem is characterized by the presence of different criteria and conflicting actors who have different interests (expressed by criteria weights) and different decision power, which have been elicited from the actors' representatives. A group viewpoint is generated through an aggregation of the different actors' viewpoints, in order to find a group compromise solution. A conflict analysis, conducted on the criteria weights, is performed to examine the level of agreement associated with the compromise solution.

The paper presents a model for the design of an electric car sharing service for the city of Milano. Several options of service configurations have been analysed and evaluated according to indicators, to measure the performance of such options in respect to relevant dimensions (i.e., economic and financial costs and revenues, mobility, social benefits, environmental effects). We set up a multicriteria decision analysis, structured by means of cognitive maps. Causal networks to estimate the effects of the options have been identified and instantiated by means of simulation techniques and other qualitative and quantitative models. The focus of the paper is on the development and use of the causal maps and their integration with a multicriteria method. The use of cognitive maps allowed to capture the multiple values of the problem and the value trees of stakeholders objectives. The proposed method can be useful in general for design and planning of mobility service, especially at a strategic level.

Traditional car-sharing services are based on the two-way scheme, where the user picks up and returns the vehicle at the same parking station. Some services allow also one-way trips, where the user can return the vehicle in another station. The one-way scheme is more attractive for the users, but may pose a problem for the distribution of the vehicles, due to a possible unbalancing between the user demand and the availability of vehicles or free slots at the stations. Such a problem is more complicated in the case of electric car sharing, where the travel range depends on the level of charge of the vehicles. In a previous work, we introduced a new approach to relocate the vehicles where cars are moved by personnel of the service operator to keep the system balanced. Such relocation method generates a new challenging pickup and delivery problem that we call the Electric Vehicle Relocation Problem (EVRP). In this work we focus on a method to forecast the unbalancing of a car-sharing system. We apply such method to the data yielded by the Milan transport agency taking into account the location and capacity of the present charging stations in Milan. In this way, using a Mixed Integer Linear Programming formulation of EVRP, we can estimate the advantages of our relocation approach on verisimilar instances.

The past decades have seen a great deal of research on algorithms for shortest path problems. However, real-world systems like route planners and mobile navigation systems require to take into account some additional conditions. Our work concerns a truck route planner for real-time navigation developed for an Italian firm and tested on real world data of Milano road network (about 61,000 nodes and 106,000 arcs). Given the vehicle GPS position and the destination, the route planner allows to find in a few seconds a path between them which minimizes simultaneously travel time, travel cost and risk. Beside the multi-objective optimization and the CPU efficiency, other challenging features faced by the algorithm that supports the route planner are the time-dependency of some attributes (e.g. the travel costs due to the congestion charge ruling the access to limited traffic zone in the Milano centre) and the presence of forbidden turns. Results on the real network of Milano are obtained and discussed.

The paper presents the first results of some tasks of Pro-E-Bike, an Intelligent Energy Europe (IEE) funded project, started on March 2013 ending in February 2016. Pro-E-Bike promotes clean and energy efficient vehicles, analyses the performance of electric bicycles and electric scooters (Light Electric Vehicle, LEV) for the delivering of goods in urban areas and tests the use of these vehicles in seven European countries with twenty five companies, both delivering ones and companies that deliver their own products. Pilots will enable the demonstration of measurable effects in terms of reduction of CO2 emissions and energy savings in urban transport: related data about environmental, economic and social effects resulted by the introduction of e-bikes and e-scooters in the pilot cities will be collected. The paper will give an overlooks of the Italian pilot, that will take place in Genova, describing the subjects involved and the expected results.

Traditional car sharing services have been based on the two-way scheme, where the user picks up and returns the vehicle at the same parking station. Some innovative services permit also one-way trips, that is, the user is allowed to return the vehicle in another station. The one-way scheme is more attractive for the users, but may lead to an unbalance between the user demand, and the availability of vehicles or free lots at the stations. In such cases, the service provider could reallocate the fleet and restore a better distribution of the vehicles among the stations. In the case of electric car sharing, such a problem is more complex because the travel range depends on the level of the battery charge. This article presents a new approach for the relocation of electric vehicles (EVs), carried out by the staff of the service provider to keep the system balanced. Such an approach generates a challenging Paired Pickup and Delivery Problem with Time Windows with new features that to the best of our knowledge have never been considered in the literature. We call such a problem the EV relocation problem (EVRP). We yield a mixed integer linear programming (MILP) formulation of the EVRP and some techniques to speedup its solution through a state-of-the-art solver (CPLEX). Moreover, we develop a simple but effective heuristic based on such a formulation and four upper bound generation methods. We test the performances of both the MILP formulation and the heuristic on instances built on the Milan road network. © 2014 Wiley Periodicals, Inc. NETWORKS, Vol. 64(4), 292–305 2014