Personalization of the Car-Sharing Fleet Selected for Commuting to Work or for Educational Purposes—An Opportunity to Increase the Attractiveness of Systems in Smart Cities

IF 7 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Smart Cities Pub Date : 2024-07-02 DOI:10.3390/smartcities7040066
K. Turoń
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Abstract

Car-sharing services, which provide short-term vehicle rentals in urban centers, are rapidly expanding globally but also face numerous challenges. A significant challenge is the effective management of fleet selection to meet user expectations. Addressing this challenge, as well as methodological and literature gaps, the objective of this article is to present an original methodology that supports the evaluation of the suitability of vehicle fleets used in car-sharing systems and to identify the vehicle features preferred by users necessary for specific types of travel. The proposed methodology, which incorporates elements of transportation system modeling and concurrent analysis, was tested using a real-world case study involving a car-sharing service operator. The research focused on the commuting needs of car-sharing users for work or educational purposes. The study was conducted for a German car-sharing operator in Berlin. The research was carried out from 1 January to 30 June 2022. The findings indicate that the best vehicles for the respondents are large cars representing classes D or E, equipped with a combustion engine with a power of 63 to 149 kW, at least parking sensors, navigation, hands-free, lane assistant, heated seats, and high safety standards as indicated by Euro NCAP ratings, offered at the lowest possible rental price. The results align with market trends in Germany, which focus on the sale of at least medium-sized vehicles. This suggests a limitation of small cars in car-sharing systems, which were ideologically supposed to be a key fleet in those kinds of services. The developed methodology supports both system operators in verifying whether their fleet meets user needs and urban policymakers in effectively managing policies towards car-sharing services, including fleet composition, pricing regulations, and vehicle equipment standards. This work represents a significant step towards enhancing the efficiency of car-sharing services in the context of smart cities, where personalization and optimizing transport are crucial for sustainable development.
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为上下班通勤或教育目的而选择的汽车共享车队的个性化--提高智能城市中系统吸引力的机遇
在城市中心提供短期车辆租赁的汽车共享服务正在全球迅速扩张,但也面临着诸多挑战。其中一个重大挑战是如何有效管理车队的选择,以满足用户的期望。针对这一挑战以及方法论和文献方面的空白,本文旨在提出一种独创的方法,以支持对汽车共享系统中使用的车队的适用性进行评估,并确定特定类型出行所需的用户偏好的车辆特征。所提出的方法结合了交通系统建模和并行分析的要素,并通过一项涉及汽车共享服务运营商的实际案例研究进行了测试。研究的重点是汽车共享用户出于工作或教育目的的通勤需求。研究对象是柏林的一家德国汽车共享运营商。研究时间为 2022 年 1 月 1 日至 6 月 30 日。调查结果表明,受访者最青睐的车辆是 D 级或 E 级大型汽车,配备功率为 63 至 149 千瓦的内燃机,至少配备停车传感器、导航、免提、车道辅助、加热座椅,以及欧洲 NCAP 评级所显示的高安全标准,并以尽可能低的租金提供。这些结果与德国的市场趋势相吻合,德国市场的重点是销售至少中型车。这表明小型汽车在汽车共享系统中的局限性,而小型汽车在意识形态上本应是此类服务的主要车队。所开发的方法既能帮助系统运营商验证其车队是否满足用户需求,也能帮助城市决策者有效管理汽车共享服务政策,包括车队组成、定价法规和车辆设备标准。这项工作是在智能城市背景下提高汽车共享服务效率的重要一步,在智能城市中,个性化和优化交通对可持续发展至关重要。
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来源期刊
Smart Cities
Smart Cities Multiple-
CiteScore
11.20
自引率
6.20%
发文量
0
审稿时长
11 weeks
期刊介绍: Smart Cities (ISSN 2624-6511) provides an advanced forum for the dissemination of information on the science and technology of smart cities, publishing reviews, regular research papers (articles) and communications in all areas of research concerning smart cities. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible, with no restriction on the maximum length of the papers published so that all experimental results can be reproduced.
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