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  • 标题:The Importance of the Open Data Approach for Multimodal Travel Improvement
  • 本地全文:下载
  • 作者:Bia Mandžuka ; Krešimir Vidović ; Miroslav Vujić
  • 期刊名称:Interdisciplinary Description of Complex Systems - scientific journal
  • 印刷版ISSN:1334-4676
  • 出版年度:2022
  • 卷号:20
  • 期号:2
  • 页码:136-148
  • DOI:10.7906/indecs.20.2.6
  • 语种:English
  • 出版社:Croatian Interdisciplinary Society Provider Homepage: http://indecs.eu
  • 摘要:The dynamic urban network continues to face a number of problems caused by traffic. One of the main problems is the increasing use of personal vehicles (especially for shorter journeys) and an unattractive alternative - public transport. In this context, Intelligent Transport Systems can be defined as a holistic, management and information communication upgrade of the classic transport and traffic system. From the passengers' point of view, the usage of personal vehicles is still more pronounced compared to public transport. The main reason is that the public transport service quality needs to be improved if compared to the personal vehicles. The concept of multimodal travel is not new, but with the usage of adequate Intelligent Transport Systems services, it is possible to support and encourage modal shift, optimise the use of public space and influence passengers' behaviour patterns. Multimodal Journey Planners provide travellers with better and more complete information when choosing a mode of transport so they can select the most suitable option for their needs. The open data approach is crucial for defining a system that responds to the end-users' actual needs and aspirations (personalisation of the service). Another major challenge in providing a high-quality multimodal journey planning service is the availability and accessibility of data. EU directives require each Member State to establish a National Access Point. The National Access Point is a digital interface, a single/unique access point providing all information regarding travel and traffic. In this article, the importance of traffic data collection, acquisition and distribution according to the open data concept is described.
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