Data Collection and Analysis Applied to Intelligent Transportation Systems A Case Study on Public Transportation

Author:

Oliveira Gabriel Gomes1,Iano Yuzo1,Vaz Gabriel Caumo1,Suriyan Kannadhasan2

Affiliation:

1. State University of Campinas – UNICAMP

2. Cheran College of Engineering, Aravakuruchi Taluk

Abstract

Abstract The big data concept has been gaining strength over the last years. With the arise and dissemination of social media and high access easiness to information through applications, there is a necessity for all kinds of service providers to collect and analyze data, improving the quality of their services and products. In this regard, the relevance and coverage of this niche of study is notorious. It is not a coincidence that governments, supported by companies and startups, are investing in platforms to collect and analyze data, aiming at the better efficiency of the services provided to the citizens. Considering the aforementioned aspects, this work makes a contextualization of the Big Data and ITS (Intelligent Transportation System) concepts by gathering recently published articles, from 2017 to 2021, taking survey and case studies into consideration with the objective of demonstrating the importance of those themes in current days. Within the scope of big data applied to ITS, this study proposes a database for the public transportation in the city of Campinas (Brazil), enabling its improvement according to the population demands. Finally, this study tries to present clearly and objectively the methodology employed with the maximum number of characteristics, applying statistical analyses (box-and-whisker diagrams and Pearson correlation), highlighting the limitations, and expanding the studied concepts to describe the application of an Advanced Traveler Information System (ATIS), a branch of Intelligent Transportation System (ITS), in a real situation. Therefore, besides the survey of the applied concepts, this work develops a specific case study, highlighting the identified deficiencies and proposing solutions. Future works are also contemplated with the objective of expand this study and improve the accuracy of the achieved results.

Publisher

Research Square Platform LLC

Reference43 articles.

1. Lifestylesandlocationalchoices—trade-offsandcompromises: a case-studyofmiddle-classcouples living in theIle-de-France region;Brun J;UrbanStudies,1994

2. Benetechco.net, (n.d) Infrared thermometer GM320 - Shenzhen Jumaoyuan Science And Technology Co.,Ltd. http://www.benetechco.net/en/products/infrared-thermometer-gm320.html.

3. Cox, M., &Ellsworth, D. (1997). Application-controlleddemandpaging for out-of-core visualization. Proceedings. Visualization’97 (Cat. No. 97CB36155), 235–244.

4. Cats, O., Burghout, W., Toledo, T., &Koutsopoulos, H. N. (2012). Modeling Real-Time Transit Informationand Its ImpactsonTravelers’ Decisions 2. Proceedingsofthe 91st TRB Annual Meeting, 36, 37.

5. Çaldağ, M. T., &Gökalp, E. (2020). ExploringCriticalsuccessfactors for blockchain-basedintelligenttransportation systems.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3