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An Information System for Bus Travelling and Performance Evaluation

Topics: Analtyics and optimization; Analytics for Intelligent Transportation; Big Data Analytics for Intelligent Transportation; Big Data and Vehicle Analytics; Decision Support Systems; Driver Behavior Analysis; Fleet telematics; Interaction Design for Analytics; Reporting Tools; Traffic and Vehicle Data Collection and Processing; Traffic management Reporting Systems; Vehicle Information Systems; Visualisation Approaches

Authors: Leandro Ricardo 1 ; Susana Sargento 2 and Ilídio C. Oliveira 3

Affiliations: 1 Instituto de Telecomunicações, Portugal ; 2 Universidade de Aveiro and Instituto de Telecomunicações, Portugal ; 3 Universidade de Aveiro and Instituto de Engenharia Electrónica e Informática de Aveiro, Portugal

Keyword(s): Vehicular Networks, Long-Term Time Estimation, Prediction, Machine Learning.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Health Engineering and Technology Applications ; Knowledge-Based Systems ; Symbolic Systems

Abstract: A wide vehicular network has a huge potential to collect city-data, specially with respect to city mobility, one of the top concerns of the municipalities. In this work, we propose the use of the mobility data generated by the movement of the connected buses to deliver a new set of tools to support both the bus passengers and bus fleet operator use cases. Considering the bus passengers, it is possible to build smart schedules, which deliver an estimated time of arrival based on the city dynamics along time, and that can be accessed directly in the smartphone. Considering the bus fleet operator, it is possible to characterize the behaviour of buses and bus lines. Using the GPS trace of buses and map-matching algorithm, we are able to discover the line each bus is assigned to. Estimated times of arrival and predictions are implemented recurring to time estimations and predictions, using both data mining and machine learning approaches. Proof-of-concept applications were implem ented to demonstrate the real-life applicability, including a mobile app for the citizens, and a web dashboard for the fleet operator. (More)

CC BY-NC-ND 4.0

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Paper citation in several formats:
Ricardo, L.; Sargento, S. and C. Oliveira, I. (2018). An Information System for Bus Travelling and Performance Evaluation. In Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS; ISBN 978-989-758-293-6; ISSN 2184-495X, SciTePress, pages 395-402. DOI: 10.5220/0006707903950402

@conference{vehits18,
author={Leandro Ricardo. and Susana Sargento. and Ilídio {C. Oliveira}.},
title={An Information System for Bus Travelling and Performance Evaluation},
booktitle={Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS},
year={2018},
pages={395-402},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006707903950402},
isbn={978-989-758-293-6},
issn={2184-495X},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Vehicle Technology and Intelligent Transport Systems - VEHITS
TI - An Information System for Bus Travelling and Performance Evaluation
SN - 978-989-758-293-6
IS - 2184-495X
AU - Ricardo, L.
AU - Sargento, S.
AU - C. Oliveira, I.
PY - 2018
SP - 395
EP - 402
DO - 10.5220/0006707903950402
PB - SciTePress