journal article·2022Open access

A Multi-Mode Public Transportation System Using Vehicular to Network Architecture

Settawit Poochaya, Peerapong Uthansakul, Monthippa Uthansakul, Patikorn Anchuen, Kontorn Thammakul, Arfat Ahmad Khan, Niwat Punanwarakorn, Pech Sirivoratum, Aranya Kaewkrad, Panrawee Kanpan, Apichart Wantamee

Computers, Materials & Continua· Volume 73· Issue 3

Abstract

The number of accidents in the campus of Suranaree University of Technology (SUT) has increased due to increasing number of personal vehicles. In this paper, we focus on the development of public transportation system using Intelligent Transportation System (ITS) along with the limitation of personal vehicles using sharing economy model. The SUT Smart Transit is utilized as a major public transportation system, while MoreSai@SUT (electric motorcycle services) is a minor public transportation system in this work. They are called Multi-Mode Transportation system as a combination. Moreover, a Vehicle to Network (V2N) is used for developing the Multi-Mode Transportation system in the campus. Due to equipping vehicles with On Board Unit (OBU) and 4G LTE modules, the real time speed and locations are transmitted to the cloud. The data is then applied in the proposed mathematical model for the estimation of Estimated Time of Arrival (ETA). In terms of vehicle classifications and counts, we deployed CCTV cameras, and the recorded videos are analyzed by using You Only Look Once (YOLO) algorithm. The simulation and measurement results of SUT Smart Transit and MoreSai@SUT before the covid-19 pandemic are discussed. Contrary to the existing researches, the proposed system is implemented in the real environment. The final results unveil the attractiveness and satisfaction of users. Also, due to the proposed system, the CO2 gas gets reduced when Multi-Mode Transportation is implemented practically in the campus.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Vehicular Ad Hoc Networks (VANETs) · IoT and Edge/Fog Computing · Caching and Content Delivery

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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