Title: Partition tolerant collaborative gateway architecture for interoperable ITS applications

Authors: Manipriya Sankaranarayanan; C. Mala; Samson Mathew

Addresses: Department of Computer Science and Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India ' Department of Computer Science and Engineering, National Institute of Technology, Tiruchirappalli, Tamil Nadu, India ' National Transportation Planning and Research Centre, Thiruvananthapuram, Kerala 695011, India

Abstract: One of the aims of intelligent transportation systems (ITS) is to provide reliable and uninterrupted traffic information to travellers to improve traffic flow, safety and management. This objective can be accomplished by ensuring interoperability between independent ITS services or applications. This paper proposes a collaborative gateway architecture (CGA) that addresses technological and service related issues in delivering traffic data for interoperable ITS. To ensure seamless and trustworthy operation of ITS services in CGA, this paper further proposes a partition tolerant support system (PTS2) that provides the facility to reuse similar data or information originating from different sources, types and formats. The effectiveness of ITS services in CGA environment is analysed and tested through simulation of traffic congestion rate (CongRa) estimation processes functioning through data acquired from cooperative vehicles and computer vision technologies respectively. From the simulated results, it is seen that the CongRa estimation application, which operates under the proposed interoperable architecture along with its support framework, ensures that the application is partition tolerant and function with higher accuracy, credibility, consistency and enhanced quality of information compared to that which operates as an independent application.

Keywords: intelligent transportation systems; ITS; ITS applications; cooperative vehicles; collaborative gateway architecture; CGA; partition tolerant; interoperability; traffic congestion rate estimation; computer vision.

DOI: 10.1504/IJAHUC.2020.111463

International Journal of Ad Hoc and Ubiquitous Computing, 2020 Vol.35 No.4, pp.222 - 240

Received: 03 Jun 2020
Accepted: 10 Jul 2020
Published online: 27 Nov 2020 *

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