DETERMINATION OF HIGHWAY BOTTLENECKS BY USING INTELLIGENT TRANSPORTATION SYSTEMS AND GEOGRAPHIC INFORMATION SYSTEMS


MALTAŞ A., ÖZEN H.

Sigma Journal of Engineering and Natural Sciences, vol.38, no.4, pp.1925-1937, 2020 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 38 Issue: 4
  • Publication Date: 2020
  • Journal Name: Sigma Journal of Engineering and Natural Sciences
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, Academic Search Premier, Directory of Open Access Journals
  • Page Numbers: pp.1925-1937
  • Keywords: Automatic vehicle location, bottleneck detection, geographic information system, intelligent transportation system, traffic congestion
  • Van Yüzüncü Yıl University Affiliated: No

Abstract

An occurrence of congestion at a highway segment, also named bottleneck, is one of the major problems of traffic. As a result of the bottlenecks, vehicle speeds are transparently decreased and its effects continue on the traffic flow by acting upstream or downstream as an interface for a while. Thus, negative effects are observed over the capacity of the highway segment where the bottleneck occurs until traffic flow returns to normal conditions again. Therefore, traffic engineers aim to avoid this major problem in design and operation of highways. Intelligent Transportation System (ITS) is an advanced application that is used to utilize existing infrastructure more effectively instead of building new infrastructures. Today, ITS has been one of the trend study fields thanks to the development of technology and through the spread of smart cities. Automatic Vehicle Location (AVL), a powerful tool to manage fleets such as service vehicles, emergency vehicles, or public transit vehicles, is a GPS-based technology within the context of the ITS. So, agencies and organizations can follow vehicles of their fleets by utilizing satellites. In this study, an AVL dataset, integrated into public transportation systems, and Geographic Information Systems (GIS) are used to detect bottlenecks in a highway segment in Istanbul. The results showed that if the locations of bus stops and traffic signals are known, the segments, where bottlenecks occur and congestion increases, may be determined by using AVL data.