All Issue

2022 Vol.40, Issue 3 Preview Page

Article

Urban Structure-Based Factor Analysis of Two-Wheeler Accidents Using Data Cube Model

도시환경정보 기반의 데이터 큐브 모델을 이용한 이륜차 사고의 다차원 요인 분석

Yujin KIM1
,
Byeongjoon NOH2
,
Hwasoo YEO3*
김 유진1
,
노 병준2
,
여 화수3*
1Master Course, Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
2Post-doctoral Researcher, Applied Science Institute, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
3Professor, Department of Civil and Environmental Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea
1한국과학기술원 건설및환경공학과 석사과정
2한국과학기술원 응용과학연구소 박사후연구원
3한국과학기술원 건설및환경공학과 교수
*Corresponding Author
30 June 2022. pp. 358-379
PDF XML Citation
Abstract

Road traffic accidents (RTAs) have emerged a global problem, killing about 1.2 million people every year and injuring more than 50 million people. Recently, the overall number of traffic accidents has been on the decline due to technological advances such as ICT (Information Communication Technology), but the proportion of accidents related to two-wheeled vehicle has increased both domestically and externally over the past five years. One of the reasons is the rapid increase in two-wheeler accidents as online-to-offline (O2O) mobility services such as food delivery using two-wheeled vehicles have grown. Other transportation accident analysis has been conducted in various aspects, however, the identification and analysis of the cause of two-wheeler accidents which have increased rapidly in recent years are still sufficient. Reflecting this phenomenon, this study proposes a new factor analysis system for two-wheeler accidents, called FASTA. The keys of this study are to design a data cube model for multi-dimensional analysis, perform in-depth analysis of two-wheeler accidents by using on-line analytical processing (OLAP) operations with varying levels of abstraction, and apply data mining techniques to figure out the factors affecting such accidents. In our experiment, we conducted scenario-based analysis, and validated the proposed system by implementing and applying it with the two-wheeler accidents and the various social factors. The results represent the relationships two-wheeler accidents with major factors such as land use, the number of restaurants, and type of household in qualitative and quantitative perspectives. Through the proposed analysis system, we believe that decision-makers can gain a better understanding of two-wheeler accidents, and these insights would be reflected to design and plan the road environment safer.

Keywords
data cube model
food delivery service
multi-dimensional analysis
negative binomial regression
OLAP operations
two-wheeler accident

교통사고는 전 세계적으로 대두되고 있는 사회적 문제이며, 매년 약 120만 명이 사망하고, 약 5,000만 명 이상이 상해를 입는다. 최근 ICT(Information Communication Technology) 등의 기술 적용 및 융합으로 교통사고의 전반적인 수치는 감소하는 추세에 있지만, 사고의 유형을 자세히 조망해보면, 일반 차량의 교통사고 추세와는 상이하게 국내 ‧ 외 이륜차와 관련된 사고의 비율은 최근 5년간 증가하는 경향을 보이고 있다. 이륜차 사고의 주된 원인으로는 이륜차를 활용한 음식배달 온 ‧ 오프라인(Online-to-Offline, O2O) 모빌리티 서비스의 성장 등을 들 수 있다. 타 교통수단 사고 분석은 다양한 측면에서 이루어져 왔지만, 최근 급격히 증가한 이륜차의 사고 원인 식별 및 분석은 아직 미비한 실정이다. 따라서 본 연구에서는 FASTA(Factor Analytic System for Two-wheeler Accident) 라고 하는 새로운 이륜차 사고 요인 분석 시스템을 제안한다. 본 연구의 핵심은 다차원 분석을 위한 데이터 큐브 모델을 설계하고, 여러 수준의 추상화 단계에서 온라인 분석 프로세스(OLAP) 연산을 통해 이륜차 사고에 대한 심층적인 분석을 수행하고, 데이터 마이닝 기법을 적용하여 사고에 영향을 미치는 요인을 정량적으로 분석하는 것이다. 본 실험에서는 시나리오 기반의 분석을 실시하였고, 제안된 시스템을 이륜차 사고 및 다양한 도시 환경적 요인과 함께 구현하고 적용함으로써 검증했다. 연구 결과는 질적, 양적 측면에서 토지이용, 음식점 수, 가구 형태 등의 주요 요인과 이륜차 사고와의 관계를 나타낸다. 제안된 분석시스템을 통해, 의사결정자들이 이륜차 사고에 대해 심층적으로 이해할 수 있고, 도로 환경을 더욱 안전하게 설계하고 계획하는 것에 기여할 수 있을 것으로 기대된다.

키워드
데이터 큐브 모델
O2O 음식배달 서비스
다차원 분석
음이항 회귀분석
OLAP 연산
이륜차 사고
References
1
Banks H. T., Joyner M. L. (2017), AIC under the Framework of Least Squares Estimation, Applied Mathematics Letters, 74, 33-45. 10.1016/j.aml.2017.05.005
2
Dogan G., Brown T. (2014), ProTru: A Provenance Based Trust Architecture for Wireless Sensor Networks, Internation Journal of Network Management, December 2012, 17-31. 10.1002/nem
3
Duo Z., Chengxiang Z., Jiawei H. (2009), Topic Cube: Topic Modeling for OLAP on Multidimensional Text Databases, Society for Industrial and Applied Mathematics - 9th SIAM International Conference on Data Mining 2009, Proceedings in Applied Mathematics, 3, 1117-1128. 10.1137/1.9781611972795.96
4
Eavis T., Dimitrov G., Dimitrov I., Cueva D., Lopez A., Taleb A. (2010), Parallel OLAP with the Sidera Server, Future Generation Computer Systems, 26(2), 259-266. 10.1016/j.future.2008.10.007
5
Ekwonwune E. N., Ngozi N. C. A., Eberechi O. O. (2018), ICT Devices: Vital Tools for Enhancing Road Traffic Monitoring, Communications and Network, 10(03), 43-50. 10.4236/cn.2018.103004
6
Eun S. J. (2020), Trends in Mortality from Road Traffic Injuries in South Korea, 1983-2017: Joinpoint Regression and Age-period-cohort Analyses, Accident Analysis and Prevention, 134(October 2019), 105325. 10.1016/j.aap.2019.105325
7
Hadi M. A., Aruldhas J., Chow L. F., Wattleworth J. A. (1995), Estimating Safety Effects of Cross-section Design for Various Highway Types Using Negative Binomial Regression, Transportation Research Record, 1500, 169-177.
8
He B., Wei C., Zhu Z., Zhang X., Song Z. (2021), Lognormal and Gamma Mixed Negative Binomial Model for Defects Prediction in Steel Products, 1203-1207. 10.1109/DDCLS52934.2021.9455556
9
Hong G. S., Gang G. P. (2013), Traffic Safety Innovation in ITS Convergence Technology, Information and Communications Magazine, 30(11), 24-31. 10.6109/jicce.2013.11.1.030
10
Hu L., Hu X., Wan J., Lin M., Huang J. (2020), The Injury Epidemiology of Adult Riders in Vehicle-two-wheeler Crashes in China, Ningbo, 2011-2015, Journal of Safety Research, 72, 21-28. 10.1016/j.jsr.2019.12.011
11
Jang Y. J., Kim W. G., Yang I. S. (2011), Mature Consumers' Patronage Motives and the Importance of Attributes Regarding HMR Based on the Food-related Lifestyles of the Upper Middle Class, International Journal of Hospitality Management, 30(1), 55-63. 10.1016/j.ijhm.2010.06.001
12
Jeong H. S. (2016), Changes in the Industrial Characteristics and Employment Structure of Restaurants and Pubs, The June Issue of the Monthly Labor Review, 65-75, Korea Labor Institute.
13
Jiang F., Yuen K. K. R., Lee E. W. M. (2020), Analysis of Motorcycle Accidents Using Association Rule Mining-based Framework with Parameter Optimization and GIS Technology, Journal of Safety Research, 75, 292-309. 10.1016/j.jsr.2020.09.004
14
Kim D., Kim K., Choe D., Jung J. (2016), Service Issues and Policy Directions for Promoting the O2O Industry in Korea, Jounal of Society for E-Business Studies. 10.7838/jsebs.2016.21.4.137
15
Kim J., Kim S. (2019), A Study on User Experience of Mobility Platform Service: Focused on kakao Taxi and Tada, Journal of Digital Convergence, 17(7), 351-357. 10.14400/JDC.2019.17.7.351
16
Kim S., Lee K., Lee Y. (2018), Selection Attributes of Home Meal Replacement by Food-related Lifestyles of Single-person Households in South Korea, Food Quality and Preference, 66(June 2017), 44-51. 10.1016/j.foodqual.2018.01.004
17
Klanjčić M., Gauvin L., Tizzoni M., Szell M. (2021), Identifying Urban Features for Vulnerable Road User Safety in Europe. 10.31235/osf.io/89cyu
18
KOrean Statistical Information Service, https://kosis.kr/index/index.do , 2021.3.15
19
Kośmicki E., Pieńkowski D. (2013), W Poszukiwaniu Koncepcji Współczesnej Modernizacji Gospodarki i Społeczeństwa (Próba Eksplikacji Głównych Problemów), Problemy Ekorozwoju, 8(1), 115-123.
20
Kumar S., Toshniwal D. (2017), Severity Analysis of Powered Two Wheeler Traffic Accidents in Uttarakhand, India, European Transport Research Review, 9(2), 1-10. 10.1007/s12544-017-0242-z
21
Kwak Y. A., Cho Y. S. (2020), Strategy of Food Retailer and Delivery Rider's Accident in South Korea, Journal of Distribution Science, 18(5), 49-60. 10.15722/jds.18.5.202005.49
22
Law T. H., Noland R. B., Evans A. W. (2009), Factors Associated with the Relationship between Motorcycle Deaths and Economic Growth, Accident Analysis and Prevention, 41(2), 234-240. 10.1016/j.aap.2008.11.005
23
Lee J. S. (2020), Directions for Improvement of Traffic Safety for Two-Wheeler Vehicles, KOTI Special Edition, 24-29.
24
Lee K. Y., Chung Y. D., Kim M. H. (2010), An Efficient Method for Maintaining Data Cubes Incrementally, Information Sciences, 180(6), 928-948. 10.1016/j.ins.2009.11.037
25
Lim J., Kim H., Cho H., Lee H. (2021), A Study on the Driving Behavior of Delivery Two Wheeled Vehicles: Focusing on Apartment Complexes, Journal of the Korea Academia-Industrial Cooperation Society, 22(9), 19-27. 10.5762/kais.2021.22.9.19
26
Liu H., Davidson R. A., Rosowsky D. V., Stedinger J. R. (2005), Negative Binomial Regression of Electric Power Outages in Hurricanes, Journal of Infrastructure Systems, 11(4), 258-267. 10.1061/(asce)1076-0342(2005)11:4(258)
27
Ministry of Food and Drug Safety, Retrieved February 25, 2021, from https://www.mfds.go.kr/index.do
28
Noh B., Son J., Park H., Chang S. (2017), In-depth Analysis of Energy Efficiency Related Factors in Commercial Buildings Using Data Cube and Association Rule Mining, Sustainability (Switzerland), 9(11). 10.3390/su9112119
29
Noh B., Yeo H. (2021), SafetyCube: Framework for Potential Pedestrian Risk Analysis Using Multi-dimensional OLAP, Accident Analysis and Prevention, 155(April), 106104. 10.1016/j.aap.2021.106104
30
Nyamawe A. S., Nyamawe A. S., Mbosso E. C. (2014), Road Safety: Adoption of ICT for Tracking Vehicles' Over-speeding in Tanzania. International Journal of Computer Applications, 96(16), 12-15. 10.5120/16877-6876
31
Park H. W., Nah K. (2015), Study on Restaurant Francise Service Reflected on a Single Household Consumer Patterns-Focus on 2030 Generation, Journal of Digital Design, 15(3), 697-704. 10.17280/jdd.2015.15.3.066
32
Peden M. (2005), Global Collaboration on Road Traffic Injury Prevention, International Journal of Injury Control and Safety Promotion, 12(2), 85-91. 10.1080/15660970500086130
33
Poch M., Mannering F. (1996), Negative Binomial Analysis of Intersection-accident Frequencies, Journal of Transportation Engineering, 122(2), 105-113. 10.1061/(ASCE)0733-947X(1996)122:2(105)
34
Roh M., Park K. (2019), Adoption of O2O Food Delivery Services in South Korea: The Moderating Role of Moral Obligation in Meal Preparation, International Journal of Information Management, 47(October 2018), 262-273. 10.1016/j.ijinfomgt.2018.09.017
35
Saccomanno F. F., Grossi R., Greco D., Mehmood A. (2001), Identifying Black Spots along Highway SS107 in Southern Italy Using Two Models, Journal of Transportation Engineering, 127(6), 515-522. 10.1061/(ASCE)0733-947X(2001)127:6(515)
36
Samsung Traffic Safety Research Institute, http://sts.samsungfire.com/, 2021.06.15
37
Schymik G., Corral K., Schuff D., St. Louis R. (2007), Architecting a Dimensional Document Warehouse, Proceedings of the Annual Hawaii International Conference on System Sciences, 1-8. 10.1109/HICSS.2007.85
38
Song J. W. (2019), An Effect of Food Delivery App Service Convenience of Rising-generation Single Households on the Continuous Use Intention: Focusing on Moderating Effect of Willingness to Pay Delivery App Service Charge, Food Service Industry Journal, 15(3), 161-176.
39
Sun S., Bi J., Guillen M., Pérez-Marín A. M. (2021), Driving Risk Assessment Using Near-miss Events Based on Panel Poisson Regression and Panel Negative Binomial Regression, Entropy, 23(7), 1-22. 10.3390/e23070829
40
Traffic Accident Analysis System, Retrieved March 10, 2021, from http://taas.koroad.or.kr/
41
Yu J. H., Choi I. B., Song S. H. (2020), A Study on Prevention of Traffic Accidents Through Motorcycle Accident Characteristics Analysis, Transportation Technology and Policy, 17(1), Korean Society of Transportation, 29-36.
Information
  • Publisher :Korean Society of Transportation
  • Publisher(Ko) :대한교통학회
  • Journal Title :Journal of Korean Society of Transportation
  • Journal Title(Ko) :대한교통학회지
  • Volume : 40
  • No :3
  • Pages :358-379
  • Received Date : 2022-01-18
  • Revised Date : 2022-02-15
  • Accepted Date : 2022-04-28
  • DOI :https://doi.org/10.7470/jkst.2022.40.3.358
Journal Informaiton Journal of Korean Society of Transportation Journal of Korean Society of Transportation
Archives
: 2015 Vol.34~
  • NRF
  • KOFST
  • crossref cited-by
  • crosscheck
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close