skip to main content
10.1145/3365921.3365924acmotherconferencesArticle/Chapter ViewAbstractPublication PagesmommConference Proceedingsconference-collections
research-article

Active Safety for Individual and Connected Vehicles using Mobile Phone Only

Published: 22 February 2020 Publication History

Abstract

Recently there has been an increasing interest in telematics solutions for vehicles. These systems provide real-time danger detection, driving style evaluation or crash detection services. The provided information can significantly increase driving safety, help to improve driving style, support rescue operations and enable better-informed insurance pricing. While recently introduced vehicles often provide inbuilt telematics systems, older cars usually lack such functionalities. One option to remedy this issue is to develop telematics solutions that are based on sensors other than the original car equipment. In this paper we present our telematics solution that employs smartphone sensors. This research stems from our previous work on crash detection which we substantially expanded towards a system for automatic profiling of driving style, detection of driving anomalies, and community-based identification of dangerous places on public roads. We describe our approach to the processing of sensor data, driving profile construction, anomaly detection, and interaction with the driver, illustrating these aspects with selected tangible results.

References

[1]
Piotr Blaszczyk, Wojciech Turek, and Krzysztof Cetnarowicz. 2014. Extensible platform for studying the behavior of drivers in urban traffic. In Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on. IEEE, 1359--1362.
[2]
German Castignani, Thierry Derrmann, Raphaël Frank, and Thomas Engel. 2015. Driver behavior profiling using smartphones: A low-cost platform for driver monitoring. IEEE Intelligent Transportation Systems Magazine 7, 1 (2015), 91--102.
[3]
German Castignani, Thierry Derrmann, Raphael Frank, and Thomas Engel. 2017. Smartphone-Based Adaptive Driving Maneuver Detection: A Large-Scale Evaluation Study. IEEE Transactions on Intelligent Transportation Systems 18, 9 (Sep 2017), 2330----2339. https://doi.org/10.1109/tits.2016.2646760
[4]
German Castignani, Raphaël Frank, and Thomas Engel. 2013. Driver behavior profiling using smartphones. In 16th International IEEE Conference on Intelligent Transportation Systems-(ITSC). IEEE, 552--557.
[5]
Saurabh Daptardar, Vignesh Lakshminarayanan, Sharath Reddy, Suraj Nair, Saswata Sahoo, and Purnendu Sinha. 2015. Hidden Markov Model based driving event detection and driver profiling from mobile inertial sensor data. In 2015 IEEE SENSORS. IEEE, 1--4. https://doi.org/10.1109/icsens.2015.7370312
[6]
Jin-Hyuk Hong, Ben Margines, and Anind K Dey. 2014. A smartphone-based sensing platform to model aggressive driving behaviors. In Proceedings of the 32nd annual ACM conference on Human factors in computing systems. ACM, 4047--4056.
[7]
Adrian Kłusek, Marcin Kurdziel, Mateusz Paciorek, Piotr Wawryka, and Wojciech Turek. 2018. Driver Profiling by Using LSTM Networks with Kalman Filtering. In 2018 IEEE Intelligent Vehicles Symposium, IV 2018, Changshu, Suzhou, China, June 26-30, 2018. IEEE, 1983--1988.
[8]
Xinhua Liu, Huafeng Mei, Huachang Lu, Hailan Kuang, and Xiaolin Ma. 2017. A Vehicle Steering Recognition System Based on Low-Cost Smartphone Sensors. Sensors 17, 3 (2017), 633.
[9]
Kevin P Murphy. 2007. Conjugate Bayesian analysis of the Gaussian distribution. Technical Report. University of British Columbia.
[10]
World Health Organization. 2018. Global status report on road safety 2018: Summary. https://www.who.int/violence_injury_prevention/road_safety_status/2018/en/
[11]
European Parliament and the Council of the European Union. 2015. Regulation (EU) 2015/758 of the European Parliament and of the Council concerning type-approval requirements for the deployment of the eCall in-vehicle system based on the 112 service and amending Directive 2007/46/EC. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32015R0758.
[12]
Blaszczyk Piotr, Wojciech Turek, Aleksander Byrski, and Krzysztof Cetnarowicz. 2015. Towards credible driver behavior modeling. In Intelligent Transportation Systems (ITSC), 2015 IEEE 18th International Conference on. IEEE, 1557--1562.
[13]
Sygic. 2019. Sygic. https://www.sygic.com/
[14]
Teltonika. 2019. BTAPP. https://teltonika.lt/product/btapp-mobile-application/
[15]
thePersonal. 2019. Ajusto. https://www.thepersonal.com/auto-insurance/ajusto
[16]
Johan Wahlstrom, Isaac Skog, and Peter Handel. 2017. Smartphone-Based Vehicle Telematics: A Ten-Year Anniversary. IEEE Transactions on Intelligent Transportation Systems 18, 10 (Oct 2017), 2802----2825. https://doi.org/10.1109/tits.2017.2680468
[17]
Chuang-Wen You, Martha Montes-de Oca, Thomas J Bao, Nicholas D Lane, Hong Lu, Giuseppe Cardone, Lorenzo Torresani, and AndrewT Campbell. 2012. CarSafe: a driver safety app that detects dangerous driving behavior using dual-cameras on smartphones. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing. ACM, 671--672.
[18]
Mingming Zhang, Chao Chen, Tianyu Wo, Tao Xie, Md Zakirul Bhuiyan, and Xuelian Lin. 2017. SafeDrive: Online Driving Anomaly Detection from Large-Scale Vehicle Data. IEEE Transactions on Industrial Informatics 13, 4 (2017), 2087--2096.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
MoMM2019: Proceedings of the 17th International Conference on Advances in Mobile Computing & Multimedia
December 2019
266 pages
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

  • Johannes Kepler University, Linz, Austria
  • @WAS: International Organization of Information Integration and Web-based Applications and Services

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 February 2020

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Car active-safety
  2. connected vehicles
  3. mobile-sensing

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Funding Sources

  • Polish National Center for Research and Development

Conference

MoMM2019

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 199
    Total Downloads
  • Downloads (Last 12 months)5
  • Downloads (Last 6 weeks)2
Reflects downloads up to 03 Jan 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media