Detection of vehicle steering based on smartphone

Zhiping Qi; Zhenchao Ouyang; Jianwei Niu; Yu Li

doi:10.1109/ISPA/IUCC.2017.00156

Detection of vehicle steering based on smartphone

Zhiping Qi
, Zhenchao Ouyang
, Jianwei Niu
, Yu Li

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Aggressive and abnormal driving may cause serious traffic accidents; therefore, it is crucial and necessary to monitor vehicle steering. For its powerful sensors and processing capacity, the smartphone-based Intelligent Transport System (ITS) can not only capture not only behaviors but also driving styles of vehicle steering. However, vehicle steering behaviors are highly affected by complex conditions such as speed, curvature of the bend, etc. Previous works generally ignore the influence of the speed, and build the models that regard each steering behavior as the same. This paper analyzes the patterns of five common steering behaviors (i.e., left turn, right turn, left lane, right lane and uturn) according to real trace data, and then divide all steering behaviors into 4 speed levels. Different machine learning models are trained on our data set, and the result shows that the decision tree model performs better than other models, and can achieve an average 90% accuracy for the five steering behaviors under four-speed-level.

Original language	English
Title of host publication	Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017
Editors	Gregorio Martinez, Richard Hill, Geoffrey Fox, Peter Mueller, Guojun Wang
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1024-1030
Number of pages	7
ISBN (Electronic)	9781538637906
DOIs	https://doi.org/10.1109/ISPA/IUCC.2017.00156
State	Published - 25 May 2018
Event	15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017 - Guangzhou, China Duration: 12 Dec 2017 → 15 Dec 2017

Publication series

Name	Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017

Conference

Conference	15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017
Country/Territory	China
City	Guangzhou
Period	12/12/17 → 15/12/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

Machine learning
Smartphone
Speed level
Vehicle steering behavior

Access to Document

10.1109/ISPA/IUCC.2017.00156

Cite this

Qi, Z., Ouyang, Z., Niu, J., & Li, Y. (2018). Detection of vehicle steering based on smartphone. In G. Martinez, R. Hill, G. Fox, P. Mueller, & G. Wang (Eds.), Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017 (pp. 1024-1030). (Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISPA/IUCC.2017.00156

Qi, Zhiping ; Ouyang, Zhenchao ; Niu, Jianwei et al. / Detection of vehicle steering based on smartphone. Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017. editor / Gregorio Martinez ; Richard Hill ; Geoffrey Fox ; Peter Mueller ; Guojun Wang. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1024-1030 (Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017).

@inproceedings{65d37076ad1145c998cdcb4aaeb2ce95,

title = "Detection of vehicle steering based on smartphone",

abstract = "Aggressive and abnormal driving may cause serious traffic accidents; therefore, it is crucial and necessary to monitor vehicle steering. For its powerful sensors and processing capacity, the smartphone-based Intelligent Transport System (ITS) can not only capture not only behaviors but also driving styles of vehicle steering. However, vehicle steering behaviors are highly affected by complex conditions such as speed, curvature of the bend, etc. Previous works generally ignore the influence of the speed, and build the models that regard each steering behavior as the same. This paper analyzes the patterns of five common steering behaviors (i.e., left turn, right turn, left lane, right lane and uturn) according to real trace data, and then divide all steering behaviors into 4 speed levels. Different machine learning models are trained on our data set, and the result shows that the decision tree model performs better than other models, and can achieve an average 90\% accuracy for the five steering behaviors under four-speed-level.",

keywords = "Machine learning, Smartphone, Speed level, Vehicle steering behavior",

author = "Zhiping Qi and Zhenchao Ouyang and Jianwei Niu and Yu Li",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017 ; Conference date: 12-12-2017 Through 15-12-2017",

year = "2018",

month = may,

day = "25",

doi = "10.1109/ISPA/IUCC.2017.00156",

language = "英语",

series = "Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1024--1030",

editor = "Gregorio Martinez and Richard Hill and Geoffrey Fox and Peter Mueller and Guojun Wang",

booktitle = "Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017",

address = "美国",

}

Qi, Z, Ouyang, Z , Niu, J & Li, Y 2018, Detection of vehicle steering based on smartphone. in G Martinez, R Hill, G Fox, P Mueller & G Wang (eds), Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017. Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017, Institute of Electrical and Electronics Engineers Inc., pp. 1024-1030, 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017, Guangzhou, China, 12/12/17. https://doi.org/10.1109/ISPA/IUCC.2017.00156

Detection of vehicle steering based on smartphone. / Qi, Zhiping; Ouyang, Zhenchao ; Niu, Jianwei et al.
Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017. ed. / Gregorio Martinez; Richard Hill; Geoffrey Fox; Peter Mueller; Guojun Wang. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1024-1030 (Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Detection of vehicle steering based on smartphone

AU - Qi, Zhiping

AU - Ouyang, Zhenchao

AU - Niu, Jianwei

AU - Li, Yu

PY - 2018/5/25

Y1 - 2018/5/25

N2 - Aggressive and abnormal driving may cause serious traffic accidents; therefore, it is crucial and necessary to monitor vehicle steering. For its powerful sensors and processing capacity, the smartphone-based Intelligent Transport System (ITS) can not only capture not only behaviors but also driving styles of vehicle steering. However, vehicle steering behaviors are highly affected by complex conditions such as speed, curvature of the bend, etc. Previous works generally ignore the influence of the speed, and build the models that regard each steering behavior as the same. This paper analyzes the patterns of five common steering behaviors (i.e., left turn, right turn, left lane, right lane and uturn) according to real trace data, and then divide all steering behaviors into 4 speed levels. Different machine learning models are trained on our data set, and the result shows that the decision tree model performs better than other models, and can achieve an average 90% accuracy for the five steering behaviors under four-speed-level.

AB - Aggressive and abnormal driving may cause serious traffic accidents; therefore, it is crucial and necessary to monitor vehicle steering. For its powerful sensors and processing capacity, the smartphone-based Intelligent Transport System (ITS) can not only capture not only behaviors but also driving styles of vehicle steering. However, vehicle steering behaviors are highly affected by complex conditions such as speed, curvature of the bend, etc. Previous works generally ignore the influence of the speed, and build the models that regard each steering behavior as the same. This paper analyzes the patterns of five common steering behaviors (i.e., left turn, right turn, left lane, right lane and uturn) according to real trace data, and then divide all steering behaviors into 4 speed levels. Different machine learning models are trained on our data set, and the result shows that the decision tree model performs better than other models, and can achieve an average 90% accuracy for the five steering behaviors under four-speed-level.

KW - Machine learning

KW - Smartphone

KW - Speed level

KW - Vehicle steering behavior

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U2 - 10.1109/ISPA/IUCC.2017.00156

DO - 10.1109/ISPA/IUCC.2017.00156

M3 - 会议稿件

AN - SCOPUS:85048358111

T3 - Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017

SP - 1024

EP - 1030

BT - Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017

A2 - Martinez, Gregorio

A2 - Hill, Richard

A2 - Fox, Geoffrey

A2 - Mueller, Peter

A2 - Wang, Guojun

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017

Y2 - 12 December 2017 through 15 December 2017

ER -

Qi Z, Ouyang Z , Niu J, Li Y. Detection of vehicle steering based on smartphone. In Martinez G, Hill R, Fox G, Mueller P, Wang G, editors, Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1024-1030. (Proceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017). doi: 10.1109/ISPA/IUCC.2017.00156

Detection of vehicle steering based on smartphone

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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