Article

Location Optimization for Multiple Types of Charging Stations for Electric Scooters

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Abstract

The difference between traditional scooters and electric scooters is the convenience of refueling and charging process. Designing a complete infrastructure system is a necessary step if efforts to promote e-scooters are to meet with success. This study discusses the optimal location problem of locating charging stations—which is generally considered a location-allocation problem. There are two types of charging stations: charge stations and battery-exchange stations. The only one model in determining the location of either type of station tends to decrease the traditional utility compared to compound model traditional as this method tends not to set stations where they would serve the greatest number of customers. In addition, population density and land cost should be taken into account in determining where stations are set. We, therefore, propose a method that accounts for differences in population density and land cost in order to solve a multi-objective problem with maximum utility at minimum cost. A mathematical model is developed in which constraints pertaining to capacity and distance are considered. To find an optimal parameter for Multi-Objective Particle Swarm Optimization (MOPSO), generational distance (GD), maximum spread, spacing, and diversity metrics are applied. Finally, we research an angle-based focus method and determine the extent to which stations would be used in order to determine the optimal proportions of charging stations and battery-exchange stations. Moreover, according to the analysis we found that the installed ratio model of BES/BCS (Battery-exchange stations/Battery charging stations) is 6:5 in the downtown area and 1:6 in the outskirts of high population density areas. Besides, the BES/BCS ratio model is 1:13 in the downtown and only BCSs are installed in the outskirts of the low population density area.

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... As micromobility services have expanded across cities, studies done to investigate the impact of dockless e-scooter services on transportation infrastructure and other existing municipal services have been limited (McKenzie, 2019). Given the limited number of studies, this rapid growth imposes challenges on cities regarding how to manage and implement such services (Caspi et al., 2020). If micromobility services are managed and deployed effectively, improved time savings, reduced travel costs, and better travel experiences for users are to be expected. ...
... These studies have examined travel behavior Jiao and Bai, 2020;Hall, 2017;McKenzie, 2019;Noland, 2019;Orr et al., 2019), social impacts (Petersen, 2019), equity and accessibility , environmental impacts (Hollingsworth et al., 2019), and rider satisfaction factors . Other studies have focused on dockless vehicle location and allocation as an optimization problem (Chen et al., 2018), as well as parking location needs (Fang et al., 2018). Further research has explored the relationship between e-scooter use and public transit and personal car use (Smith and Schwieterman, 2018). ...
... They conducted a temporal study and completed a comparison of dockless e-scooter-sharing and docked bike-sharing in Washington. Furthermore, Caspi et al. (2020) studied how demographics, land use, and the built environment can affect e-scooter trip generation. Additionally, they argued that schools and colleges are a ready market for shared e-scooter services given the high rate of student use. ...
Article
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... Furthermore, multi-objective models have been proposed in the node-based CSLP literature (see e.g. Bai et al. [11], Brey et al. [19], Chen et al. [24], Hodgson and Rosing [63] and Yi and Bauer [202]). For instance, in order to assign higher weight to candidate locations having more vehicle kilometers traveled within their range, Brey et al. [19] consider maximizing traffic intensity captured by charging stations together with a p-median objective minimizing the average distance traveled to refuel vehicles. ...
... For instance, in order to assign higher weight to candidate locations having more vehicle kilometers traveled within their range, Brey et al. [19] consider maximizing traffic intensity captured by charging stations together with a p-median objective minimizing the average distance traveled to refuel vehicles. Hodgson and Rosing [63] and Yi and Bauer [202] combine demand coverage maximization and facility access cost minimization while Bai et al. [11] and Chen et al. [24] determine the optimal locations of battery swapping stations and battery charging stations in a way to minimize system costs and maximize service level, either by maximizing the number of customers served [24] or by minimizing the time spent by drivers to complete recharging [11]. ...
... For instance, in order to assign higher weight to candidate locations having more vehicle kilometers traveled within their range, Brey et al. [19] consider maximizing traffic intensity captured by charging stations together with a p-median objective minimizing the average distance traveled to refuel vehicles. Hodgson and Rosing [63] and Yi and Bauer [202] combine demand coverage maximization and facility access cost minimization while Bai et al. [11] and Chen et al. [24] determine the optimal locations of battery swapping stations and battery charging stations in a way to minimize system costs and maximize service level, either by maximizing the number of customers served [24] or by minimizing the time spent by drivers to complete recharging [11]. ...
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Charging infrastructure planning has a strategic impact on promoting the use of electric vehicles (EVs) and other alternative fuel vehicles. Importantly, decision makers need to answer the question on the number and location of charging stations in a way to satisfy customer recharging demand and meet certain restrictions imposed by real-life considerations. In this context, we consider the charging station location problem (CSLP), which belongs to the category of facility location problems and seeks to optimize the locations of charging stations. A growing body of literature has developed on this subject in recent years. Various approaches have been proposed to model the problem taking into account different features, constraints, decisions and performance measures as well as the dynamic and stochastic components inherent to the problem. Moreover, efficiently solving CSLP, particularly when applied to real-life case-studies, might be challenging in practice. Considerable effort has thus been made by researchers to develop innovative solution methods based on exact or heuristic approaches to obtain good quality solutions within short computation times. Therefore, we provide in this paper a comprehensive review on the literature relevant to CSLP, with a particular focus on modeling and solving the problem. We analyze the literature from different perspectives including demand representation, demand coverage approaches, objective functions, side constraints, decision variables, model structure as well as time dependency and uncertainty on the problem parameters. We also present various ways of classifying existing works, which allows readers to capture different aspects of the problem that researchers have tended to focus on and identify opportunities for further developments. We believe our work could be helpful to researchers by providing an overview of the CSLP literature and suggesting perspectives for future research in the field.
... A model for locating charging stations and replace batteries in a network of electric scooters is developed in [8]. A maximum coverage model is used as a reference for mathematical modeling and the multi-objective function seeks to minimize installation costs and maximize the number of customers served. ...
... Equation (7) calculates the total number of batteries in the terminal over time (t), making the balance of withdrawals, returns, and reallocations of batteries between terminals. Equation (8) defines that at the beginning of the period (t = 1), all batteries in the terminal are charged and available for withdrawal. Equation (9) defines the number of batteries charged and available for withdrawal at each terminal point (i) for every time (t), making the balance between the quantity of batteries available at terminal (i) in the previous time (t − 1), batteries picked up from terminal (i) in the previous time (t − 1), batteries returned in terminal (i) in time (t − tr s − 1) already recharged and available for a new withdrawal, and the reallocated batteries that were removed and returned at terminal (i) in the previous time (t − 1). ...
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This paper introduces the mobile battery network for electronic devices through powerbanks in a city, and proposes an optimization model to find the optimum site and set-up of the network considering costumers demand, logistics components, the batteries degradation, and terminal’s charger regime. To this end, a series of degradation tests were carried out on lithium-ion batteries, in four different charger regimes, in which the battery voltage amplitude and the charging electric current were varied. The results of these tests were incorporated into the optimization model as the depreciation rate and charge time over battery life. The mathematical modeling innovates by including new components designed specifically for this new problem: battery availability according to charging time; different types of customer service; objective function modeling that includes the logistical costs of battery relocation, terminal maintenance, and battery depreciation. The results indicate that the network performance using batteries in the fastest charging configuration tends to have a positive impact on their efficiency and profitability. The model can be used as a reference for other applications that require recharge points that enable the use of mobile batteries, such as electric scooters, electric bicycles, and drones, among others.
... Despite the impacts of micromobility systems on transportation networks, the literature on electric scooters is scant (Moran et al., 2020;Yang et al., 2020, Wood et al., 2019Caspi et al., 2020;Gössling, 2020), while studies on decision-making for deploying electric scooters are scarce. In general, the need for decision-support tools to develop regulations and enhance safety for e-scooter usage has been acknowledged among researchers and practitioners (Nikiforiadis et al., 2021;Yang et al., 2020;. ...
... So far, studies on planning decisions for shared electric scooter systems have mostly focused on optimally locating charging infrastructures. For instance, the early work of Wang (2007) sought to determine the optimal location for e-scooter refueling stations, while more recently Chen et al. (2018) formulated the associated location-allocation problem as a bi-objective optimization problem, aiming to minimize charging cost and maximize demand coverage of charging stations. However, planning for electric scooter deployment must consider several issues such as rider comfort and most importantly, safety . ...
Article
E-scooters have emerged in recent years as an innovative and user-friendly transportation mode in urban areas worldwide. However, their incorporation in urban road networks is complex, since legal, social, and technical considerations often arise with respect to their usage. As official regulatory frameworks are often lacking, micromobility operators typically devise ad hoc geofences to create virtual geographic boundaries, restricting parking or access for users. In this context, this paper proposes a methodological tool for assisting decision-making in regulating e-scooter usage in urban areas. A service network design model is introduced for that purpose, aiming to maximize the extent of geofences in an urban area for the sake of maximizing road safety, while considering travel time impacts for users. The problem is formulated as a bi-level bi-objective optimization model and solved using a Non-Dominated Sorting Genetic Algorithm, NSGA-II. Subsequently, sensitivity analysis regarding the design criteria is performed and results are discussed.
... Step 7.2-In stage 2, Lorentzian distance measure Cha, 2008), and Pearson distance measure (Cha, 2008) are used to calculate distances of alternatives from the negative-ideal solution as Eqs. (23)-((24). ...
... Step 7.2-In stage 2, Lorentzian distance measure Cha, 2008), and Pearson distance measure (Cha, 2008) are used to calculate distances of alternatives from the negative-ideal solution as Eqs. (23)-((24). ...
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Due to high popularity of electric scooters, cities with high population have faced challenges regarding establishment of battery swapping stations (BSS) along populated areas of the urban districts. However, locating a BSS in a big city is a multi-dimensional problem which require reliable tools to efficiently address. This paper proposes a novel robust decision-making tool, named mulTi-noRmalization mUlti-distance aSsessmenT (TRUST), to tackle location selection problem for BSS considering sustainability criteria. The proposed approach applies a multi-normalization procedure using three linear normalization techniques, logarithmic-normalization, and constraint-based normalization which are integrated through an aggregation operator. Then, Euclidean, Manhattan, Lorentzian, and Pearson distance measures are used to determine distance of alternatives from the negative ideal solution in order to calculate the final score. Advantages of the proposed approach are consideration of a multi-normalization algorithm to minimize subjectivity in normalized data, consideration of constraint-based normalization technique to ensure that specific standards, and utilization of four distance measures through a two-stage process to determine a relative distance score. To show the feasibility and applicability of the new approach, a real-life case study is investigated to locate a BSS in Istanbul. Results show that the best alternative is Beyoğlu for locating a BSS for electric scooters.
... All of these factors contribute to a poorer quality of life for urban inhabitants [5]. While transport is an integral part of the economic activity and social life of city dwellers [6], it is also one of the largest sources of air pollution in urban areas [7,8], which in turn has adverse effects on human health, the climate, and ecosystems [9]. Internal combustion vehicles are responsible for the emission of particulate matter (PM2.5 and PM10), soot (BC), particles (UFP), nitrogen oxide (NO2), and carbon monoxide (CO), which are harmful to the body [10,11]. ...
... The issue of shared electric mobility in the subject literature has been analysed in many respects and from many different perspectives [50]. Besides the environmental aspects noted above, the most frequently discussed issues are costs [51], safety [52,53], parking [53], the fleet, types of power supply, and the systems with which such vehicles are equipped [8,54], as well as infrastructure and patterns of use [51]. However, no studies have been conducted aimed at assessing the quality of e-scooter sharing services. ...
Article
Full-text available
Shared micromobility is a new phenomenon being observed in urban transport. It is a response to the problems associated with congestion and environmental pollution. Small electric vehicles such as e-scooters are highly suitable for crowded city centres, often providing an alternative to private motor vehicles or public transport, and serve as a good first-and last-mile transport option. While they have become a feature of sustainable transport systems in cities, their impact on the environment often depends on the services offered by operators of this mode of personal transport. There are many tools available to measure the quality of transport, e-services and shared mobility services. However, no specific mechanism has been designed for vehicles in the field of shared e-scooters (research gap). The aim of the article is to verify whether the three dimensions identified by the authors: mobile application functions, device features, and customer service are valid for examining the quality of shared e-micromobility factors on the example of e-scooters. Based on the obtained results, the authors created the MMQUAL (MicroMobility QUALity) model, which accurately describes the quality of the studied phenomenon. The results of the study can serve as a platform for researchers interested in further exploring the issue and improving the proposed model. They may also be of commercial value to operators, who could use this tool to boost the competitiveness of their services by enhancing those features that have the greatest impact on their quality.
... Further, Deb et al. also developed a pareto dominance based CSO for solving multi-objective charging station placement problem [57]. Phonrattanasak and Leeprechanon applied ACO to solve the charging station placement problem [58] References [59][60][61] used PSO to solve the charging station placement problem. Liu et al. used an adaptive PSO (APSO) to solve the charging station placement problem considering cost as the objective function [59]. ...
... Lin and Hua used basic PSO to solve the charging station placement problem considering EV flow as objective [60]. Further, Chen et al. used multi-objective PSO to solve charging station placement problem for electric scooters considering minimization of cost and land area associated with charging stations as well as maximization of service capacity of charging stations as objective functions [61]. ...
Article
The escalated energy demand in conjunction with the global warming and environmental degradation has paved the path of transportation electrification. Electric Vehicles (EVs) need to recharge their batteries after travelling certain distance. Thus, large scale deployment of EVs calls for development of sustainable charging infrastructure. The placement of charging stations is a complex optimization problem involving a number of decision variables, objective functions, and constraints. Placement of charging station mimics a non-convex and non- combinatorial problem involving both transport and distribution network. The complex and non-linear nature of the charging station placement problem has compelled researchers to apply Nature Inspired Optimization (NIO) algorithms for solving the problem. This study aims to review the NIO algorithms applied for solving the charging station placement problem. This work will endow the research community with a systematic review of NIO algorithms for solving charging station placement problem thereby revealing the key features, advantages, and disadvantages of each of these algorithms. Thus, this work will help the researchers in selecting suitable algorithm for solving the charging station placement problem and will serve as a guide for developing efficient algorithms to solve the charging station placement problem.
... Hosseinzadeh et al. (2021) found commercial land use percent, industrial land use percent, Walk Score and Bike Score influenced E-Scooter trip density at a TAZ level using a generalized additive model . Other works related to escooter trip characteristics focused on determining times of day and days of the week (McKenzie, 2019) e-scooters were used most often, optimizing charging methods (Masoud et al., 2019;Chen et al., 2018), evaluating the scheduling and distribution of e-scooters (García Á lvarez et al., 2018) and suggesting regulations for escooter use (Riggs and Kawashima, 2020;Anderson-Hall et al., 2019;Hicham et al., 2019). Regarding the previously conducted studies, understanding e-scooter trips and their environmental determinants in different geographical contexts is still in the early stages of research. ...
Article
Shared e-scooters have become a common mode of transportation in many cities around the world. E-sooters provide convenient and quick rides for short distances and can act as a connection for first/last mile trips. To date, limited studies have explored the spatial variation of e-scooter trips and there is knowledge to be gained by investigating variables associated with e-scooter trip generation. This study implemented a spatial analysis approach, Geographical Weighted Regression (GWR), to explore how factors relating to demographics, density, diversity, design, urbanism scores, distance to transit and other transportation-related variables influence e-scooter trips in Louisville, KY. More than 400,000 e-scooter trips across 159 Traffic Analysis Zones (TAZs) were included in the study. Results show TAZ-level factors including land use, age distribution, gender distribution, Walk Score and Park Score impacted the density of e-scooters trips in the TAZ. The GWR model showed improvements over a global Ordinary Least Squares (OLS) model. Local goodness of fit ranged from 0.732–0.895 across the study area. This study can help governments and e-scooter sharing companies develop policies that maximize e-scooter use, equity, and accessibility while improving the mobility of cities.
... '+ California, then the ridership of this mode speedy grew and surpassed bike-sharing just 2 years later [1]. Even with this short period of introduction, e-scooter also attracts many researchers to explore its characteristics including accidents [4][5][6][7], impact on urban mobility [8][9][10], social perception [11], customer segmentation [12] and charging station optimization [13]. ...
... The advantages of distributed refilling facilities provide the base for increasing the number of e-scooter users and for promoting the massive use of this new and sustainable form of transportation, and reducing the number of trips made in cars powered by internal combustion engines [40]. It is also important to note that a decrease in dependence on private vehicles would decongest urban centres [33]. ...
Article
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Means and modes of transport in urban environments are changing. The emergence of new means of personal transport, such as e-scooters or e-bikes, combined with new concepts such as 'vehicle sharing' are changing urban transport. A greater social awareness of the harmful effects of polluting gases is leading to the adoption of new e-mobility solutions. A sustainable e-scooter recharging dock has been designed, built, and put into operation in a small town north of the city of Valencia (Spain). In the proposed novel solution, a stand-alone PV system is built for the free recharge of e-scooters using an original system that supports new sustainable means of transport. The design of the PV system considers the size limitations of the equipment, where a single PV module must generate the energy needed to recharge the e-scooters. A battery is used to store the energy and adjust power generation and consumption profiles. A commercial electronic converter adjusts the various electrical characteristics of generation, storage, and consumption. As a result of the system analysis, the surplus autonomy provided for the e-scooter recharging dock is calculated. Potential stakeholders in the use of the proposed system and their reasons for adopting this sustainable solution are identified. Experimental results of the first months of operation are included and these demonstrate the correct operation of the proposed system.
... Among the batteries with the most advanced technology, the li-ion battery is chosen, which is characterized by providing more energy with less weight [2,4,5,7]. ...
Article
At the last decade, a growing number of electric scooters appeared on the world market as a key to solve mobility problems in the crowded cities. The main purpose of this paper is to design a three-wheeled electric scooter with protracted autonomy. This model is driven by double BLDCM positioned on the back wheels and controlled by a fuzzy logic controller. The scooter contains an electronic differential system that provides robust control of the scooter and it also allows each drive wheel to be separately controlled to rotate at different speeds. The proposed controller of electric scooter system is simulated with MATLAB Simulink environment. The findings of simulation show the effectiveness of the suggested supervision.
... One way is installing a photovoltaic module on scooters so that they can have solar charging during the trip and parking time (Ridden, 2019). The other way could equip conventional dock-based stations with grid charging or battery-exchange platforms (Chen, Cheng, Lie, & Yu, 2018), or solar charging platforms (Shah, 2019). Charging scooters at the parking space could be a simple and effective solution, which needs the equipment of charging platforms connecting to either the national grid or photovoltaic cells. ...
Article
The revolution in mobility-sharing services brings disruptive changes to the transportation landscape around the globe. The authorities often rush to regulate the services without a good knowledge of these new options. In Singapore and some other cities, dockless bike-sharing systems rose and fell in just one year and were followed by the booming of docking scooter-sharing systems. This study conducts a comparative analysis of bike-sharing and scooter-sharing activities in Singapore to help understand the phenomenon and inform policy-making. Based on the collected data (i.e., origin-destination pairs enriched with the departure and arrival time and the GPS locations) for one month, this study proposed methods to construct the paths and estimated repositioning trips and the fleet sizes. Hence, the spatio-temporal heterogeneity of the two systems in two discrete urban areas was investigated. It explored the impact of the fleet size, operational regulations (dockless versus docking), and weather conditions on the usages. We found that shared scooters have spatially compact and quantitatively denser distribution compared with shared bikes, and their high demands associate with places such as attractions, metros, and the dormitory. Results suggest that scooter sharing has a better performance than bike sharing in terms of the increased sharing frequency and decreased fleet size; however, the shareability still has potential to be improved. High repositioning rates of shared-scooters indicates high maintenance cost for rebalancing and charging. Rainfall and high temperatures at noon suppress the usages but not conclusively. The study also proposes several initiatives to promote the sustainable development of scooter-sharing services.
... Motor síncrono 26,27,28,29,30,31 Motor trifásico 26 Movilidad 92,191,194,198,199,200,204,206 Movilidad eléctrica 198,199 O R Radiación 17,20,23,24 Reciclaje 65, 73 Reinforced 1,6,7,47 Resolución de problemas 122,123,124,132,133,134,135 Reutilización 65,73,74,77,79,83,84,85,86,204 ...
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A coleção de trabalhos intitulada “Entre Ciencia e Ingenieria 3” é uma obra que tem como foco principal a discussão científica por intermédio de diversos trabalhos que compõe seus capítulos. O volume abordará de forma categorizada e interdisciplinar, pesquisas cujos resultados possam auxiliar na tomada de decisão, tanto no campo acadêmico, quanto no profissional. Nos capítulos apresentados, são encontrados estudos de grande valia nas áreas da simulação computacional, materias, gestão energética, aspectos industriais, estudos ambientais, na área da educação e otimização. A composição dos temas buscou a proposta de fundamentar o conhecimento de acadêmicos (as), mestres (as) e todos (as) aqueles (as) que de alguma forma se interessam pela área da Engenharia, através de temáticas atuais com resoluções inovadoras, descritas nos capítulos da coleção. Sendo assim, a divulgação científica é apresentada com grande importância para o desenvolvimento de toda uma nação, portanto, fica evidenciada a responsabilidade de transmissão dos saberes através de plataformas consolidadas e confiáveis, como a Atena Editora, capaz de oferecer uma maior segurança para os novos pesquisadores e os que já atuam nas diferentes áreas de pesquisa, exporem e divulgarem seus resultados.
... Lastly, larger cities have more infrastructural ability to accommodate micromobility options including the accessibility of charging stations (Y.-W. Chen et al., 2018;Nikiforiadis et al., 2019). On the other hand, in rural areas, people rely more on their personal vehicles. ...
Article
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The present research examines how perceptions of e-scooter mobile apps (i.e., a communication technology) influence intent to use e-scooters (i.e., a transportation technology) while considering other perceptions specific to e-scooters (ease of use, usefulness, safety, environmental impact, and enjoyment), context of use (geographic landscape), and demographic factors (age and sex). Results suggest mobile app perceived ease of use is associated with e-scooter use intent and this effect is mediated by e-scooter perceived usefulness, even when controlling for e-scooter perceived ease of use as well as other influential elements of e-scooter use. In addition to illustrating the importance of user experiences with mobile apps within the e-scooter context, this interdisciplinary research furthers a fundamental argument that media technologies are an integral factor in the adoption of transportation technologies.
... Existing studies have primarily focused on the social impacts of these scooter services (Petersen, 2019;Loizos, 2018) and parking placements (Fang et al., 2018), and acceptance rates (Riggs, 2018;Degele et al., 2018). Additional research has centered on the distribution optimization (Chen et al., 2018), the electrical engineering-focused efforts towards efficient batteries (Pellegrino et al., 2010), the reduction of personal automobile usage (Smith & Schwieterman, 2018), as well as the spatial and temporal analysis between e-scooters and other AVs (McKenzie, 2019). Moreover, one recent study focused on safety concerns of one e-scooter company (Bird) conducting an analysis of the official Instagram profile (Allem & Majmundar, 2019). ...
Article
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Triggered by the widespread use of electric scooters in Serbian cities, the authors conducted an empirical research of media discourses in terms of their use and the influence they have on the various aspects of wellbeing in the urban environment. Among other, the authors explore the relation between the use of electric scooters and urban security challenges as seen by newspapers, as well as the lens of the Twitter community in Serbia. Through the identification of the main topics represented in both newspapers and Twitter posts, the ways and tones in which the topics have been addressed, as well as arguments provided to support the publicly expressed attitudes, this paper provides both the quantitative and qualitative analysis of data, attempting to give an answer to whether the use of electric scooters could be considered an urban security challenge or just another issue causing moral panic.
... Chen et al. (2018) developed a mathematical model for charging stations considering the limitations between the capacity and distance, is considered the existence of charging stations and switch stations ...
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The use of electric vehicles (cars, motorcycles, scooters, trucks, buses) in the cities is an essential component so that cities can be considered smart cities. In this paper, we propose a mathematical model for the Electric School Bus Routing Problem which aims to minimise costs and optimise transportation times and cost of the students. We propose a Genetic Algorithm with a pre-Selection Operator, Tournament Selection Operator, Crossover-K Operator, and MutationS Operator to solve the Electric School Bus Routing Problem (SBRP). International Journal of Combinatorial Optimization Problems and Informatics, 11(2), May-Aug 2020, 1-12. ISSN: 2007-1558.
... What research there is has primarily focused on the social impacts of these scooter services (Petersen, 2019;Loizos, 2018), parking placement (Fang et al., 2018), adoption rates (Riggs, 2018;Degele et al., 2018), and safety concerns (Allem and Majmundar, 2019). Additional research has centered on distribution optimization (Chen et al., 2018) and electrical engineering-focused efforts towards efficient batteries (Pellegrino et al., 2010). One recent scooter-share usage study based out of Chicago conducted analysis using hypothetical trips. ...
Conference Paper
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Micro-mobility services, such as dockless e-scooters and e-bikes, are inundating urban centers around the world. The mass adoption of these services, and ubiquity of the companies operating them, offer a unique opportunity through which to compare cities. In this position paper, a series of spatiotemporal measures are proposed based on activity data collected from shared micro-mobility services. The purpose of this paper is to identify a number of ways that these new mobility services can serve to augment existing city similarity approaches.
... It studies the correlation between e-scooter uses and accidents and provides recommendations on how to improve safety for e-scooter riders. The optimal location of charging stations for e-scooters is studied in [3]. The way riders park their e-scooters in the city of San Jose is studied in [5]. ...
Preprint
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Shared e-scooters have become a familiar sight in many cities around the world. Yet the role they play in the mobility space is still poorly understood. This paper presents a study of the use of Bird e-scooters in the city of Atlanta. Starting with raw data which contains the location of available Birds over time, the study identifies trips and leverages the Google Places API to associate each trip origin and destination with a Point of Interest (POI). The resulting trip data is then used to understand the role of e-scooters in mobility by clustering trips using 10 collections of POIs, including business, food and recreation, parking, transit, health, and residential. The trips between these POI clusters reveal some surprising, albeit sensible, findings about the role of e-scooters in mobility, as well as the time of the day where they are most popular.
... Among the batteries with the most advanced technology, the li-ion battery is chosen, which is characterized by providing more energy with less weight [2,4,5,7]. ...
Article
Full-text available
At the last decade, a growing number of electric scooters appeared on the world market as a key to solve mobility problems in the crowded cities. The main purpose of this paper is to design a three-wheeled electric scooter with protracted autonomy. This model is driven by double BLDCM positioned on the back wheels and controlled by a fuzzy logic controller. The scooter contains an electronic differential system that provides robust control of the scooter and it also allows each drive wheel to be separately controlled to rotate at different speeds. The proposed controller of electric scooter system is simulated with MATLAB Simulink environment. The findings of simulation show the effectiveness of the suggested supervision.
... What research there is has primarily focused on the social impacts of these scooter services (Petersen, 2019;Loizos, 2018), parking placement (Fang et al., 2018), adoption rates (Riggs, 2018;Degele et al., 2018), and safety concerns (Allem and Majmundar, 2019). Additional research has centered on distribution optimization (Chen et al., 2018) and electrical engineering-focused efforts towards efficient batteries (Pellegrino et al., 2010). One recent scooter-share usage study based out of Chicago conducted analysis using hypothetical trips. ...
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Full-text available
The United States is currently in the midst of a micro-mobility revolution of sorts. Almost overnight, U.S. cities have been inundated with short-term rental scooters owned and operated by start-up companies promising a disruption to the urban transportation status-quo. These scooter-share services are presented as a dockless alternative to traditionally government-funded, docking station-based bike-sharing programs. Given the rapid rise of electric scooter companies, and how little is known about their operations, there is pressing public interest in understanding the impact of these transportation-sharing platforms. By exploring the nuanced spatial and temporal activity patterns of each of these platforms, this research identifies differences and similarities between dockless e-scooters and existing bike-sharing services. The findings from this research contribute to our understanding of urban transportation behavior and differences within mobility platforms.
... The Generational Distance (GD) and the Spacing (SP) [30] have been used to evaluation the performance of each algorithm. ...
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Hydraulic turbine governing system (HTGS) is essential equipment which regulates frequency and power of the power grids. In previous studies, optimal control of HTGS is always aiming at one single operation condition. The variation of operation conditions of HTGS is seldom considered. In this paper, multiobjective optimal function is proposed for HTGS under multiple operation conditions. In order to optimize the solution to the multiobjective problems, a novel multiobjective grey wolf optimizer algorithm with searching factor (sMOGWO) is also proposed with two improvements: adding searching step to search more no-domain solutions nearby the wolves and adjusting control parameters to keep exploration ability in later period. At first, the searching ability of the sMOGWO has been verified on several UF test problems by statistical analysis. And then, the sMOGWO is applied to optimize the solutions of the multiobjective problems of HTGS, while different algorithms are employed for comparison. The experimental results indicate that the sMOGWO is more effective algorithm and improves the control quality of the HTGS under multiple operation conditions.
... Since e-PMVs need battery recharging, a handful of studies investigated some issues related to the charging points. Chen et al. [54] showed that the optimal location for e-PMVs charging systems is in the function of the greatest number of times a station is used. Moreover, the optimal location is affected by the minimum total cost and the maximum capacity of the service (i.e., the maximum number of rechargeable vehicles in a day), the land-pricing, the service distance, and the installed capacity. ...
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Nowadays, the diffusion of electric-powered micro Personal Mobility Vehicles (e-PMVs) worldwide—i.e., e-bikes, e-scooters, and self-balancing vehicles—has disrupted the urban transport sector. Furthermore, this topic has captured many scholars and practitioners’ interest due to multiple issues related to their use. Over the past five years, there has been strong growth in the publication of e-PMV studies. This paper reviews the existing literature by identifying several issues on the impact that e-PMVs produce from different perspectives. More precisely, by using the PRIMA’s methodological approach and well-known scientific repositories (i.e., Scopus, Web of Science, and Google Scholar), 90 studies between 2014 and 2020 were retrieved and analyzed. An overview and classification into endogenous issues (e.g., impact on transport and urban planning) and exogenous issues (e.g., impact on safety and the environment) are provided. While several issues are deeply investigated, the findings suggest that some others need many improvements. Therefore, the status quo of these studies is being assessed to support possible future developments.
... Among those that have appeared, some again use spatial clustering methods, such as Hua et al. [5], who estimate the demand for parking of some companies in Nanjing (China) based on GPS data for the origins and destinations of the company Muving's e-motorcycle trips. Chen et al. [29] apply minimizing impedance and maximizing coverage solutions to locate recharging stations for the batteries used by e-scooters. However, none of them has made use of the time information in the data to consider the dynamic component of the use of the system in optimal location models. ...
Article
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Moped-style scooters are one of the most popular systems of micro-mobility. They are undoubtedly good for the city, as they promote forms of environmentally-friendly mobility, in which flexibility helps prevent traffic build-up in the urban centers where they operate. However, their increasing numbers are also generating conflicts as a result of the bad behavior of users, their unwarranted use in public spaces, and above all their parking. This paper proposes a methodology for finding parking spaces for shared motorcycle services using Geographic information system (GIS) location-allocation models and Global Positioning System (GPS) data. We used the center of Madrid and data from the company Muving (one of the city’s main operators) for our case study. As well as finding the location of parking spaces for motorbikes, our analysis examines how the varying distribution of demand over the course of the day affects the demand allocated to parking spaces. The results demonstrate how reserving a relatively small number of parking spaces for scooters makes it possible to capture over 70% of journeys in the catchment area. The daily variations in the distribution of demand slightly reduce the efficiency of the network of parking spaces in the morning and increase it at night, when demand is strongly focused on the most central areas.
... Motor síncrono 26,27,28,29,30,31 Motor trifásico 26 Movilidad 92,191,194,198,199,200,204,206 Movilidad eléctrica 198,199 O R Radiación 17,20,23,24 Reciclaje 65, 73 Reinforced 1,6,7,47 Resolución de problemas 122,123,124,132,133,134,135 Reutilización 65,73,74,77,79,83,84,85,86,204 ...
... Electric bike-sharing system Basic costs of electric bike-sharing systems (operational, infrastructure) [9,10] Electric bike parameters (cost of purchase, safety, range) [9,11] Location of the station (bike, docking) [11,13] Weather conditions [5] Electric scooter and moped-sharing system Basic costs of electric scooter-and moped-sharing systems (operational, infrastructure) [15,16] Weather conditions [5] Electric bike parameters (cost of purchase, safety, range, battery capacity) [18,19] Charging and docking station (location, policy, battery charging speed) [19] Weather conditions [5] Electric car-sharing systems Basic costs of electric car-sharing systems (operational, infrastructure) [6,12] Electric bike parameters (cost of purchase, fleet size, safety, range, battery capacity) [14,20,21] Charging and parking locations (location, policy, battery charging speed) [22][23][24][25][26][27][28][29][30] Models of systems (rental rules, vehicle relocation time) [29,30] From the perspective of sustainable transport development, the best services rely on electric vehicles or encourage drivers to transition from owning a vehicle to using a shared car. Until the coronavirus pandemic outbreak, services relied heavily on the demand for mobility and the provision of transport alternatives within urban areas. ...
Article
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The global spread of the COVID-19 virus has led to difficulties in many branches of the economy, including significant effects on the urban transport industry. Thus, countries around the world have introduced different mobility policies during the pandemic. Due to government restrictions and the changed behaviors of transport users, companies providing modern urban mobility solutions were forced to introduce new business practices to their services. These practices are also apparent in the context of the electric shared mobility industry. Although many aspects and problems of electric shared mobility have been addressed in scientific research, pandemic scenarios have not been taken into account. Noticing this research gap, we aimed to update a previously developed model of factors that influence the operation of electric shared mobility by incorporating aspects related to the COVID-19 pandemic and its impact on this industry. This article aims to identify the main factors influencing the electric shared mobility industry during the COVID-19 and post-lockdown periods, together with their operation areas and the involved stakeholders. The research was carried out on the basis of expert interviews, social network analysis (SNA), and the use of the R environment. The article also presents sustainable transport management recommendations for cities and transport service operators, which can be implemented after a lockdown caused by an epidemic. The results in this paper can be used to support transport modeling and the creation of new policies, business models, and sustainable development recommendations. The contents will also be helpful to researchers worldwide in preparing literature reviews for articles related to sustainable management in the COVID-19 pandemic reality.
... Motor síncrono 26,27,28,29,30,31 Motor trifásico 26 Movilidad 92,191,194,198,199,200,204,206 Movilidad eléctrica 198,199 O R Radiación 17,20,23,24 Reciclaje 65, 73 Reinforced 1,6,7,47 Resolución de problemas 122,123,124,132,133,134,135 Reutilización 65,73,74,77,79,83,84,85,86,204 ...
... The Multi-Objective Particle Swarm Optimization (MOPSO) algorithm also achieves efficient results. The main variables it uses to detect stops are generational distance, maximum spread, spacing and diversity metric [33]. However, the construction of the stations should take into account the safety of the user and the efficiency of the trips for a friendlier e-scooter context [34]. ...
Article
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In recent years, European countries have been trying to cultivate electrical scooters (e-scooters) as an alternative form of micro-mobility. The purchase and maintenance costs of private e-scooters are expensive so cities have been collaborating with companies to construct an e-scooter rental network. This paper aims to interpret the usage patterns of e-scooters and suggest optimal station locations for charging and parking. The dataset depicts a three-month time period (August, September, and May of the year 2020/2021) of 26,374 trips, in which there were no pandemic limitations. The results are based on two main features: the initial–final position of the e-scooter (the total distance is unknown) and the travel time. Most e-scooter rides refer to leisure trips but there is a portion of users that ride e-scooters for casual trips or commutes to and from work. Here, an electrical scooter network that covers the demand of the city of Thessaloniki is suggested. The implementation plan indicates three stages of construction up to the completion of the network. The construction operation is responsible for the creation and development of a sustainable network by adding approximately 20 stations at every stage. The capacity of the stations fluctuates between 3 and 20 parking spaces, which should accommodate e-scooters and preserve free spaces for potential riders. According to the characteristics of the city of Thessaloniki, its coverage requires the construction of 67 carefully distributed stations.
... Recent reports also point out to a significant gender gap in the use of shared e-scooters (Krizek, McGuckin 2019;Howe 2020) underpinned by different mobility strategies of females and males, the way e-scooters are designated, or cultural factors. In addition, a different category is represented by the issue of fleet optimisation, like re-distribution of the e-scooters and their re-charging, which, in fact, increases the footprint of those green vehicles (Chen et al. 2018, de Bortoli 2021. ...
Article
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Underpinned by the shift towards implementing solutions supporting sustainable mobility, shared e-scooter services are evergreen in many urban areas worldwide. However, their growing use leads to new challenges connected with their operation in the urban space. This article showcases instruments called mobility points, designated to define, and improve parking practices of shared e-scooters. To evaluate the potential of mobility points fieldwork was conducted into the vectorization of shared e-scooters’ operational zones and mobility points in Cracow. The study proves that the mobility points’ visual and technical organization is adequate and thought-out in ways based on functions of the areas they are placed in. However, due to insufficient cooperation between the private and public sectors that would ensure the mobility points are virtually implemented into the service operation, the mobility points’ potential to solve parking issues is low. This calls into question their role in the sustainable mobility agenda.
... Recently, a study [16] on predicting demand using deep learning methods was also performed. There have been other studies suggesting ways to improve the legal system [1,8,17,18], promoting ways to enhance inclusiveness such as gender equity [19], selecting the location of battery charging systems [20], and estimating travel purpose [21]. Furthermore, a teaching concept differentiated by education level was introduced to improve the understanding of electric mobility including e-scooter [22]. ...
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The shared e-scooter is a popular and user-convenient mode of transportation, owing to the free-floating manner of its service. The free-floating service has the advantage of offering pick-up and drop-off anywhere, but has the disadvantage of being unavailable at the desired time and place because it is spread across the service area. To improve the level of service, relocation strategies for shared e-scooters are needed, and it is important to predict the demand for their use within a given area. Therefore, this study aimed to develop a demand prediction model for the use of shared e-scooters. The temporal scope was selected as October 2020, when the demand for e-scooter use was the highest in 2020, and the spatial scope was selected as Seocho and Gangnam, where shared e-scooter services were first introduced and most frequently used in Seoul, Korea. The spatial unit for the analysis was set as a 200 m square grid, and the hourly demand for each grid was aggregated based on e-scooter trip data. Prior to predicting the demand, the spatial area was clustered into five communities using the community structure method. The demand prediction model was developed based on long short-term memory (LSTM) and the prediction results according to the activation function were compared. As a result, the model employing the exponential linear unit (ELU) and the hyperbolic tangent (tanh) as the activation function produced good predictions regarding peak time demands and off-peak demands, respectively. This study presents a methodology for the efficient analysis of the wider spatial area of e-scooters.
... To date, few research works have addressed the problematic of automatic dispatching of charging currents for ebikes charging station. Existing works have addressed the issues of battery distribution in a charging station [23], ebike rental stations [24], optimal location of ebike charging spots [25]. The parameters taken into account are: the number and duration of the ride, the length of the ride, the power of the photovoltaic panels, the number of ebike users. ...
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This work deals with the automatic dispatching of the charging currents in a charging station for power-assisted bikes (ebike). The decision variables such as arduousness index and urgency are determined. The arduousness index is carried out from the GPS ride data. Urgency is calculated using the parking time and ebike batteries state of charge. They are used to determine ebike's charging priorities at the charging station using continue fuzzy logic. Photovoltaic power forecasting is determined over the control horizon using the artificial neural network. On the one hand, the values of the priority, the photovoltaic power forecasting and the storage battery's state of charge are calculated. They allow to control the states of the switches associated with each charging spot and the operating mode of the storage battery (source or load) using discrete fuzzy logic. On the other hand, the interest of the ride's arduousness for a charging station is presented. A comparative study between the charging method integrating the ride arduousness and not is carried out. A case study of the polytech Annecy campus at the University of Savoie Mont Blanc in France is proposed. Results show that: the arduousness index is essential for controlling the charging priority of ebikes at the charging station; Fuzzy logic allows to manage the current dispatching on a charging station; taking into account the ride's arduousness allows to save up to 413.03 (Wh) of profit and 97.90% energy flexibility on the charging station.
... There is a growing body of conceptual and review papers on different aspects of e-scooters and factors associated with their trips. These include studies on vehicle development, including battery life and recharge [9], optimization [10], life cycle assessment [11], vehicle dynamics [12], business model development [13], service loyalty [14], economic models [15], policy and regulation [16], shared space management [17], safety [18], environmental impact [19], parking analysis [20], geofences [21], e-scooter injuries [22], and COVID-19 [23]. While aspects such as infrastructure and commercialization are important, gaining a deep understanding of mobility behavior related to e-scooters plays a pivotal role in the ongoing transition of urban mobility systems worldwide [24]. ...
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The emergence of micromobility services in the form of dockless shared e-scooters has resulted in a wide range of behavioral changes in urban environments. In order to effectively steer these changes towards sustainability targets, the characteristics of e-scooter trips and users’ behaviors should be understood further. However, there is a lack of systematic literature reviews in this domain. To address this gap, we provide a two-fold systematic literature review. The first aspect focuses on the categorization of temporal and spatial patterns of shared e-scooter usage. The second aspect focuses on a deeper understanding of e-scooter users’ behaviors, utilizing the principles of persona design. The analysis of temporal patterns highlights the commonality of midday, evening, and weekend peak usage across cities, while spatial patterns suggest e-scooters are used for traveling to recreational and educational land use, as well as city center areas. The synthesis of findings on users’ behaviors has resulted in six categories, with four user types based on usage frequency (one time, casual, power, and non-adopters), and two motivation-based personas (users who are not satisfied with current mobility options and users who have had positive travel experience from e-scooter usage). The overall findings provide important lessons for evaluating this emerging mobility service, which should be considered for steering its development in public-private stakeholder networks.
... The comparisons of the optimization models were conducted as per a set of performance indicators, which included average fitness function values, the coefficient of variation of fitness function values, hypervolume indicator, generational distance, spacing, diversity, spread, and coverage. These performance metrics are capable of evaluating three main aspects, which are diversity, accuracy, and cardinality (Cui et al. 2020;Falahiazar and Shah-Hosseini 2018;Chen et al. 2018). Then, the significance levels of the optimal solutions of the different metaheuristic optimization algorithms are evaluated using nonparametric testing. ...
Article
Recently, the number of deteriorating bridges has drastically increased. As such, enormous amounts of resources are invested yearly to maintain the performance of bridges within acceptable levels. This entails the development of bridge management systems to manage the imbalance between the extensive needs for maintenance, repair and rehabilitation actions, and the limited available funds. In this regard, the present study introduces a three-tier platform to model and allocate limited resources in maintenance projects. The first model involves building a discrete event simulation model to mimic the bridge deck replacement process. The second encompasses structuring an efficient and straightforward surrogate machine learning model for mimicking the computationally expensive discrete event simulation model. In the second phase, a novel hybrid Elman neural-network invasive-weed optimization model is developed for predicting the time, cost, greenhouse gases, and utilization rates of resource allocation plans using a database generated from the previous model. The third constitutes the formulation of a multiobjective differential evolution optimization model subject to the utilization rates of the involved resources and their dispersion. Results manifest superiority in cost prediction accuracies, achieving a mean absolute percentage error, mean absolute error, and root-mean-squared error of 4.873%, 78.466%, and 39.515%, respectively. Additionally, the developed multiobjective optimization model significantly outperformed a set of well-performing metaheuristics, yielding a hypervolume indicator, generational distance, spacing, diversity, spread, and coverage of 81.721%, 0.029%, 0.1881%, 0.5229%, 0.9618%, and 0.4087%, respectively. The results also demonstrate the developed multiobjective optimization model accomplished an improvement in the minimization time, cost, and greenhouse gases by 71.01%, 27.87%, and 39.29%, respectively, when compared against a genetic algorithm. The developed models are automated through the hybrid programming of C#.net and MATLAB. It is expected that the developed method can enable the practitioners and transportation agencies to establish timely-efficient, cost-effective, and sustainable resource allocation plans while accommodating the efficacious utilization of resources.
... When we look at studies on the e-scooter sharing system in the world, we find studies mostly on e-scooters' technical features, charging stations, or safety issues (Bishop, et al., 2011;Seebauer, 2015;Nocerino, et al., 2016;Chen, et al., 2018;Genikomsakis, et al., 2018;Degele, et al., 2018;Allem and Majmundar, 2019). However, there have not been found any studies related to the operations on distribution through different locations of dockless e-scooters in a city. ...
... (3) Users: Factors of the user subsystem, such as charging satisfaction, charging habits, population distribution, income level [12], charging behavior [15], travel behaviors of urban residents [13], population density [16], and driver behavior [7] are all selection criteria to be aligned with users' behaviors and needs. ...
... Though scooter studies have been on the increase, much remains to be learned about scooter interactions with pedestrians and bikes, or the increasing complexity of the transportation system (Gössling, 2020;Younes et al., 2020). Research to date has investigated topics such as e-scooter safety (Allem and Majmundar, 2019;Bai and Jiao, 2020;Dormanesh et al., 2020;Mayhew and Bergin, 2019;Nellamattathil and Amber, 2020;Shah et al., 2021;Yang et al., 2020;Yang et al., 2020), micromobility systems (design, regulations, and policies) (Anderson-Hall et al., 2019;Gössling, 2020;Shaheen and Cohen, 2019;Tuncer and Brown, 2020), parking Fang, 2019), temporal and spatial distributions (Chen et al., 2018;Espinoza et al., 2019;McKenzie, 2019;Younes et al., 2020;Zhu et al., 2020), business models (Degele et al., 2018), and social, cultural issues and riding behavior (Fitt and Curl, 2020;Kopplin et al., 2021;Nikiforiadis et al., 2021;Zhang et al., 2021). Abduljabbar et al. (2021) have provided a systematic literature review on the association of micromobility and sustainable cities. ...
Article
In this study, app store reviews from two major micromobility companies are investigated using machine learning techniques to identify the factors that influence rider satisfaction. The Latent Dirichlet Allocation model is applied to over 12,000 rider-generated reviews to identify twelve topics discussed within the reviews. These topics cover areas such as pricing, safety, customer service, map, refund, payment, app interface, and ease of use, to name a few. Using logistic regression, the most significant factors influencing rider satisfaction were identified. Moreover, name-centered gender prediction analysis is employed to identify rider gender and then discover differences in review content and factors of satisfaction across gender. Results suggest rider satisfaction levels tend to vary across topics and gender. Women were more satisfied with the services and exhibited more positive sentiment than men. Yet, scooter is still a male dominated mode of transportation. Findings contribute to the existing literature by demonstrating the use of app store reviews in a transportation mobility study. The development of a method to assess factors contributing to rider satisfaction offers the ability to evaluate e-scooter rider needs and barriers. An apparent policy opportunity to increase scooter ridership includes an emphasis on contributing factors such as ease of use, safety (speed and riding lane), as well as app issues that showed significant influence on user satisfaction. It is recommended that a policy approach focused on improving rider satisfaction and delivering service improvements incorporate opinion mining as a methodology.
... However, their sustainable deployment requires new technology and infrastructures as, for example, specialized charging stations to accommodate large fleets of EVs. There have been considerable research effort on different aspects related to EV charging as, for example, the location of EV charging stations [1][2][3][4] or electricity price forecasting [5], among others. Charging scheduling is particularly interesting due to the large charging times often required by batteries and also to the power and physical constraints of the charging stations. ...
Article
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Scheduling the charging times of a large fleet of Electric Vehicles (EVs) may be a hard problem due to the physical structure and conditions of the charging station. In this paper, we tackle an EV’s charging scheduling problem derived from a charging station designed to be installed in community parking where each EV has its own parking lot. The main goals are to satisfy the user demands and at the same time to make the best use of the available power. To solve the problem, we propose an artificial bee colony (ABC) algorithm enhanced with local search and some mating strategies borrowed from genetic algorithms. The proposal is analyzed experimentally by simulation and compared with other methods previously proposed for the same problem. The results of the experimental study provided interesting insights about the problem and showed that the proposed algorithm is quite competitive with previous methods.
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Due to the development of the shared economy, increasingly more shared mobility providers have launched services based on the use of electric vehicles. The increasing growth of electric shared mobility services has produced various types of problems that do not occur (or occur with a limited effect) under conventional shared mobility systems. This increase in electric shared mobility problems has led to many effects, including limitations of the system zones or going out of business. To avoid difficulties in the functioning of electric shared mobility systems, various scientific studies have been undertaken to model and optimize the operation of these systems. Modeling and optimization mainly relate to one category of the system—for example, only to bike sharing. However, to understand the system of electric shared mobility holistically, there is a need to define the criteria generally as stimulants or destimulants. Based on these assumptions, we conducted research on the identification of factors influencing the development of electric shared mobility services. We conducted our own expert research based on the Social Network Analysis method. The aim of this study was to determine the factors that influence the development or recession of services in the entire electric shared mobility market in reference to selected stakeholders. The obtained results indicate a non-standard approach to the modeling and optimization of electric shared mobility services. This study could be used as support for creating electric shared mobility models and could also be helpful for service providers or local mobility managers through the developed recommendations.
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To maximize the total amount of alternative fuel consumption in a traffic network and satisfy the travel demands to the greatest extent possible, this paper addresses the problem of finding the optimal locations in a transportation network in which to construct capacitated alternative-fuel stations with a limited construction budget. Different from most existing studies that treat traffic flows in each origin-destination pair as a constant, a stochastic chance-constrained programming model (SCCPM) is proposed to characterize the problem of interest in this paper, where random variables are employed to capture the uncertainty of traffic flows. Moreover, for solution convenience, a linear equivalent model of the proposed one is deduced. Finally, two sets of numerical experiments are implemented by the Cplex solver to test the performance of the model. Firstly, a series of experiments are conducted on the small scale network to analyze the sensitivities of the parameters in the proposed model. Then we find the optimal locations for alternative-fuel stations in the large-scale network and draw the conclusion that most of the alternative-fuel vehicles are located in demands cluster districts according to the thermodynamic diagram.
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In the process of electric vehicle marketization, the charging infrastructure, especially the planning and construction of fast charging stations, is extremely important. The construction of charging stations is limited by various social factors and should adapt to the development of the charging demand. Therefore, based on the background research that has considered the social factors and determined a certain number of candidate sites, this paper proposes a method that selects the optimal constructing plan of charging stations with the lowest social costs from the candidate construction plans. First, an optimization model for siting and sizing the charging stations is created and then, the optimal number and location of the charging stations in the unplanned areas and the optimal number and power of in-station charging facilities are obtained by solving the model. After that, two development trends of the charging demand are considered. In case the existing charging stations are not suitable for the changed charging demand, the charging station construction scale is expanded or downsized based on the sequential strategy of the charging station construction, which helps avoid the fund loss and resource waste.
Chapter
At the beginning of the sixties, the Italian scooters became popular in Italy, an age that was considered unimportant the safety of people. However, safety standards are now stronger, and helmet use is mandatory in most countries. That is why this paper try to analyze in greater detail the characteristics associated with the anthropometric measurements of a representative sample of a broader society for determining the ideal characteristics of a helmet associated with this type of vehicle. For this reason and considering the relevance of our study to a Smart City, we will use a multicriteria analysis and an intelligent data analysis in order to understand much better the ideal and suitable measurements to be able to design a helmet for an Italian scooter.
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Nowadays, the development of new energy science has gradually entered a good situation, and accordingly, electric vehicles have been recognized by people all over the world and rapidly popularized in various countries. However, the rapid growth of electric vehicles has caused a series of problems, such as insufficient number of charging stations, uneven distribution, and high cost, which are becoming increasingly serious. In order to solve the above problems, this paper takes Ireland as an example for research. Based on the collection of relevant information, this paper first tries to build a social total cost model, and calculates the total operating cost of charging stations under various distribution conditions. In this model, the total social cost is subdivided into comprehensive economic cost and environmental cost. Economic costs include construction costs and fees, while environmental costs include electricity consumption and carbon dioxide emissions. Secondly, this paper established a charging station location optimization model based on genetic algorithm, which simplified the Irish territory into a rectangle with a length of 350 km and a width of 200 km, subdivided it into small squares, and adjusted the correlation coefficient to meet the charging demand. This solution solves the minimization problem of operating cost under the constraints of depreciation period of charging station, power consumption per unit distance of charging station and vehicle charging probability. Finally, in order to determine the factors that may have a significant impact on the total cost of charging stations, we conducted sensitivity analysis and found that the total cost is very sensitive to the number of charging stations and the possibility of EV charging per day.
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Location selection of charging stations of electric vehicles (EVs) contributes to long-term sustainable urban development. This study proposes a hybrid approach integrated with the Geographical information system (GIS) and Bayesian network (BN) to deal with the location selection problem for EVs. GIS serves for capturing spatial and geographical data, which provides dynamic and visual information for selecting charging sites. BN is employed to process various criteria and demonstrate the cause-effect relationship in alternative site selection. A BN model consisting of nine criteria from three aspects is established to determine the most suitable locations for charging stations of EVs. A total of ten alternative locations in Singapore is used to verify the applicability and effectiveness of the developed hybrid approach. Results indicate that (1) Criteria, including the number of MRT stations, household units, and charging efficiency, are identified as the most sensitive factors to the location selection; (2) The transportation efficiency has the strongest linkage with the location selection (with an average value of the strength of 0.445), revealing that the transportation efficiency is more important than the social and economic efficiency. The novelty of this research lies in the development of the hybrid GIS-based BN approach that is more accurate and stable under noise interruption compared to the traditional decision-making method (e.g., TOPSIS). The developed approach can be used as a decision tool to identify the major contributing factors and update the optimal decisions given new observation data in GIS in an automatic manner.
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Micro-mobility is increasingly recognised as a promising mode of urban transport, particularly for its potential to reduce private vehicle use for short-distance travel. Despite valuable research contributions that represent fundamental knowledge on this topic, today’s body of research appears quite fragmented in relation to the role of micro-mobility as a transformative solution for meeting sustainability outcomes in urban environments. This paper consolidates knowledge on the topic, analyses past and on-going research developments, and provides future research directions by using a rigorous and auditable systematic literature review methodology. To achieve these objectives, the paper analysed 328 journal publications from the Scopus database covering the period between 2000 and 2020. A bibliographic analysis was used to identify relevant publications and explore the changing landscape of micro-mobility research. The study constructed and visualised the literature’s bibliometric networks through citations and co-citations analyses for authors, articles, journals and countries. The findings showed a consistent spike in recent research outputs covering the sustainability aspects of micro-mobility reflecting its importance as a low-carbon and transformative mode of urban transport. The co-citation analysis, in particular, helped to categorise the literature into four main research themes that address benefits, technology, policy and behavioural mode-choice categories where the majority of research has been focused during the analysis period. For each cluster, inductive reasoning is used to discuss the emerging trends, barriers as well as pathways to overcome challenges to wide-scale deployment. This article provides a balanced and objective summary of research evidence on the topic and serves as a reference point for further research on micro-mobility for sustainable cities.
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E-scooter sharing provides a last-mile solution to complement transit services, but less was known about its effectiveness in serving short-distance transit trips. We investigate the potential of using e-scooter sharing to replace short-distance transit trips of excessive indirectness, multiple transfers, and long access-egress walking. First, we conducted a stated preference survey on e-scooter users in the Central Area of Singapore and estimated mixed logit models to examine factors influencing the choice of e-scooters and transit. We then calculated the number of transit trips that can be replaced by e-scooters. Second, we analyzed the decision of e-scooter companies in terms of the trade-offs between serving more e-scooter trips and making more revenue under varying fares. The results show that fare, MRT transfer, and MRT access-egress walking distance have significantly negative impacts on mode utilities with random tastes among respondents. Male, young and high-income groups are more heterogeneous in e-scooter preferences compared with other groups. The loss of mode share can be nearly 17% if maximizing the revenue. We classify trade-off situations into five categories and provide suggestions of how to balance between mode share and revenue for each category. Several implications are drawn for better harnessing and regulating this new mobility service, including where to deploy e-scooters to satisfy the demand unmet by the transit and how to reach a proper balance between private operators and public welfare.
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In most of the previous works, changed and unchanged regions are detected by analyzing the changes of backscattering coefficients for SAR images, which is termed as binary change detection. In fact, due to the increase and decrease of backscattering coefficients, the changed regions can be further analyzed as two kinds of changes, which is termed as ternary change detection. In this paper, a change detection method based on evolutionary multiobjective optimization is proposed to automatically perform binary and ternary change detection of multitemporal SAR images. First, the log-likelihood function of the Gaussian mixture model and the Bhattacharyya distance are designed as two objectives, respectively. In particular, a novel measurement method based on Bhattacharyya distance is designed for the ternary change detection task. Not only the separability between each two classes is maximized, but also the Bhattacharyya distance between two changed classes and unchanged class is kept closer to obtain a more balanced classification performance. Then a multiobjective optimization method based on non-dominated sorting is used to optimize these two objectives simultaneously. In the proposed approach, chromosome ranking and perturbation probability selection operators are designed to make high-quality solutions with a high probability of being exploited and improve the performance of the algorithm. In addition, a one-step local search strategy based on the expectation–maximization method is integrated into the proposed algorithm to accelerate the convergence. Experimental results on simulated and real-world datasets demonstrate the effectiveness and robustness of the proposed algorithm.
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