智能手机在发展中国家的公共交通规划和建议——综述

IF 6.4 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Rohit Verma, Sandip Chakraborty
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引用次数: 0

摘要

在这个互联系统无处不在的时代,交通单元已经成为一个重要的数据来源,从通勤者、车辆、司机或交通系统接触的任何部分收集数据。这些数据既有空间方面的,也有时间方面的,可用于多种服务,如旅行辅助系统、多式联运解决方案、实时旅行信息、智能停车、自动驾驶汽车等。随着当前可持续交通的热议,公共交通系统的使用由于经济和环境的节省而得到普及。在这篇综述文章中,我们提供了一些作品的亮点,这些作品试图利用技术来改善公共交通系统的多个部分,主要集中在发展中经济体,从而改善各国的整体通勤体验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smartphones for public transport planning and recommendation in developing countries—A review
In this era of connected systems that have penetrated everywhere, transport units have become a significant source of data, collected from commuters, vehicles, drivers, or any section being touched by the transport system. These data, which have both spatial as well as temporal aspects, is utilized for a plethora of services like travel assistant systems, multi‐modal transport solutions, real‐time travel information, smart parking, autonomous vehicles, to name a few. With the current buzz of sustainable transport, the use of public transport systems have been popularized owing to the economic and environmental savings. In this review article, we provide a highlight of works, which have tried to utilize techniques to improve multiple sections of the public transport system, primarily focusing on developing economies, thus improving the overall commute experience at various countries.
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来源期刊
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, THEORY & METHODS
CiteScore
22.70
自引率
2.60%
发文量
39
审稿时长
>12 weeks
期刊介绍: The goals of Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (WIREs DMKD) are multifaceted. Firstly, the journal aims to provide a comprehensive overview of the current state of data mining and knowledge discovery by featuring ongoing reviews authored by leading researchers. Secondly, it seeks to highlight the interdisciplinary nature of the field by presenting articles from diverse perspectives, covering various application areas such as technology, business, healthcare, education, government, society, and culture. Thirdly, WIREs DMKD endeavors to keep pace with the rapid advancements in data mining and knowledge discovery through regular content updates. Lastly, the journal strives to promote active engagement in the field by presenting its accomplishments and challenges in an accessible manner to a broad audience. The content of WIREs DMKD is intended to benefit upper-level undergraduate and postgraduate students, teaching and research professors in academic programs, as well as scientists and research managers in industry.
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