Browse > Article
http://dx.doi.org/10.12815/kits.2021.20.1.160

Study of Analysis for Autonomous Vehicle Collision Using Text Embedding  

Park, Sangmin (Dept. of Transportation System Engineering, Univ. of Ajou)
Lee, Hwanpil (Division of Transportation Research, Korea Expressway Corporation Research Institute)
So, Jaehyun(Jason) (Dept. of Transportation System Engineering, Univ. of Ajou)
Yun, Ilsoo (Dept. of Transportation System Engineering, Univ. of Ajou)
Publication Information
The Journal of The Korea Institute of Intelligent Transport Systems / v.20, no.1, 2021 , pp. 160-173 More about this Journal
Abstract
Recently, research on the development of autonomous vehicles has increased worldwide. Moreover, a means to identify and analyze the characteristics of traffic accidents of autonomous vehicles is needed. Accordingly, traffic accident data of autonomous vehicles are being collected in California, USA. This research examined the characteristics of traffic accidents of autonomous vehicles. Primarily, traffic accident data for autonomous vehicles were analyzed, and the text data used text-embedding techniques to derive major keywords and four topics. The methodology of this study is expected to be used in the analysis of traffic accidents in autonomous vehicles.
Keywords
Text Embedding; Autonomous Vehicle; Accident; Topic Modelling;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Sun L. and Yin Y.(2017), "Discovering themes and trends in transportation research using topic modeling," Transport Research Part C: Emerging, vol. 77, pp.49-66.   DOI
2 Woo C. W. and Lee J. Y.(2020), "Investigation of Research Topic and Trends of National ICT Research-Development Using the LDA Model," Journal of the Korea Convergence Society, vol. 11, no. 7, pp.9-18.   DOI
3 Baek S.(2018), Exploration on utilization of word embedding for topic modeling in Korean data, Master's Thesis, The Graduate School of Seoul National University.
4 Blei D. M.(2012), "Probabilistic Topic Models," Communications of the ACM, vol. 55, no. 4, pp.77-84.   DOI
5 Blei D. M., Ng A. Y. and Jordan M. I.(2003), "Latent Dirichlet Allocation," Journal of Machine Learning Research, vol. 3, pp.993-1022.
6 Chae S.(2019), A Study of Text Embedding for Korean Sentiment Analysis, Master's Thesis, University of Seoul.
7 Oh C., Lee Y. and Ko M.(2016), "Establishment of ITS Policy Issues Investigation Method in the Road Section applied Text mining," The Journal of the Korea Institute of Intelligent Transport Systems, vol. 15, no. 6, pp.10-23.   DOI
8 Cho A., Lee K. H. and Cho W. S.(2015), "Latent Mobility Pattern Analysis of Bus Passenger with LDA," Journal of Korean Data & Information Science Society, vol. 26, no. 5, pp.1061-1069.   DOI
9 Favaro M. F., Nader N., Eurich O. S., Tripp M. and Varadaraju N.(2017), "Examining accident reports involving autonomous vehicles in California," PLos ONE, vol. 12, no. 9, e0184952.   DOI
10 Lai S., Liu K., He S. and Zhao J.(2016), "How to Generate a Good Word Embedding," IEEE Intelligent Systems, vol. 31, no. 6, pp.5-14.   DOI
11 Park J. and Lee S.(2020), "Big Data Analysis of Busan Civil Affairs Using the LDA Topic Modeling Technique," Information Policy, vol. 27, no. 2, pp.66-83.
12 Park S., Ko H., So J., Wee J. and Yun I.(2018), "Study of Test Scenario for Safety Evaluation of Automated Vehicle(Case of the Community Road in K-City)," Proceeding of 2018 Korea Institute of Intelligent Transport Systems, pp.331-334.
13 Park S., So J., Ko H., Jeong H. and Yun I.(2019), "Development of Safety Evaluation Scenarios for Autonomous Vehicle Tests Using 5-Layer Format(Case of the Community Road)," The Journal of the Korea Institute of Intelligent Transport Systems, vol. 18, no. 2, pp.114-128.   DOI
14 Petrovic D., Mijailovic R. and Pesic D.(2020), "Traffic Accidents with Autonomous Vehicles: Type of Collisions, Manoeuvres and Errors of Conventional Vehicles' Drivers," Transport Research Procedia, vol. 45, pp.161-168.   DOI
15 Ryu H.(2019), "Falling Accidents Analysis in Construction Sites by Using Topic Modeling," Journal of the Korea Convergence Society, vol. 10, no. 7, pp.175-182.   DOI