한국정보통신학회논문지 (Journal of the Korea Institute of Information and Communication Engineering)

  • 제26권2호
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  • Pages.278-287
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  • 2022
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  • 2234-4772(pISSN)
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  • 2288-4165(eISSN)
한국정보통신학회 (The Korea Institute of Information and Commucation Engineering)
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드라이빙 시뮬레이터 시나리오 개발을 위한 동적 도로환경 데이터 융합

Integration of Dynamic Road Environmental Data for the Creation of Driving Simulator Scenarios

  • Gwon, Joonho (Department of Computer Science and Engineering, University of Seoul) ;
  • Jun, Yeonsoo (International School of Urban Sciences, University of Seoul) ;
  • Yeom, Chunho (International School of Urban Sciences, University of Seoul)
  • 투고 : 2021.12.06
  • 심사 : 2021.12.29
  • 발행 : 2022.02.28
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초록

기술발전에 따라 드라이빙 시뮬레이터는 다양한 용도로 활용되고 있다. 드라이빙 시뮬레이터 실험에서 시나리오 개발은 실험결과의 신뢰를 높이고 연구목표를 달성하며 운전자에게 보다 실제같은 경험을 제공하는데 필수적이다. 그러나 시나리오를 개발하는데 데이터베이스 형성과 실시간 시나리오 운영 등에는 아직도 제약이 많다. 본 연구는 이러한 환경에서 실제 도로에서 실시간 주행속도와 기상데이터를 수집하고 활용하는데 가능성을 확인하고자 한다. 또한 본 연구를 통해 아두이노 센서 데이터와 공공API 데이터를 연계하는 방안도 제시하고자 한다. 연구결과의 검증을 위해 실제도로에서 시험을 실시했으며 본 연구를 통해 드라이빙 시뮬레이터에서 실시간 데이터를 활용한 시나리오 개발에 도움이 될 것으로 기대한다.

With the development of technology, driving simulators have been used in various ways. In driving simulator experiments, scenario creation is essential to increase fidelity, achieve research aims, and provide an immersive experience to the driver. However, challenges remain when creating realistic scenarios, such as developing a database and the execution of scenarios in real-time. Therefore, to create realistic scenarios, it is necessary to acquire real-time data. This study intends to develop a method of acquiring real-time weather and traffic speed information for actual, specific roads. To this end, this study suggests the concatenator for dynamic data obtained from Arduino sensors and public open APIs. Field tests are then performed on actual roads to evaluate the performance of the proposed solution. Such results may give meaningful information for driving simulator studies and for creating realistic scenarios.

키워드

과제정보

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2020S1A5C2A01092978).

참고문헌

  1. R. Zha and W. Tang, "Optimal design of driving simulator scenario system based on speed perception," in 2019 IEEE International Conference on Computation, Communication and Engineering (ICCCE), Fujian, China, pp. 178-180, 2019.
  2. T. M. Granda, G. W. Davis, V. W. Inman, and J. A. Molino, The use of high-fidelity real-time driving simulators for geometric design, CRC Press: Boca Raton, FL, USA, 2011.
  3. F. Vienne, S. Caro, L. Desire, J. Auberlet, F. Rosey, and E. Dumont, "Driving simulator: an innovative tool to test new road infrastructures," in TRA-Transport Research Arena, Paris, France, pp. 10, 2014.
  4. H. S. Kang, M. A. Jalil, and M. Mailah, "A PC-based driving simulator using virtual reality technology," in Proceedings of the 2004 ACM SIGGRAPH international conference on Virtual Reality continuum and its applications in industry, Los Angeles: CA, pp. 273-277, 2004.
  5. W. Lee, J. Kim, and J. Cho, "A driving simulator as a virtual reality tool." In Proceedings of 1998 IEEE International Conference on Robotics and Automation (Cat. No. 98CH36146), Leuven, Belgium, pp. 71-76, 1998.
  6. P. A. Hancock and T. B. Sheridan, The future of driving simulation, In Handbook of Driving Simulation for Engineering, Medicine, and Psychology, 1st ed. CRC Press: Boca Raton, FL, USA, 2011.
  7. Y. Zhang, Z. Guo, and Z. Sun, "Driving simulator validity of driving behavior in work zones," Journal of Advanced Transportation, vol. 2020, no. 1, pp. 1-10, Jun. 2020.
  8. F. Bella, "Effects of combined curves on driver's speed behavior: Driving simulator study," Transportation Research Procedia, vol. 3, no. 1, pp. 100-108, Jul. 2014. https://doi.org/10.1016/j.trpro.2014.10.095
  9. J. A. Greenberg and M. Blommer, Physical fidelity of driving simulators, In Handbook of Driving Simulation for Engineering, Medicine, and Psychology, 1st ed. CRC Press: Boca Raton, FL, USA, 2011.
  10. J. K. Kearney and T. F. Grechkin, Scenario authoring, In Handbook of Driving Simulation for Engineering, Medicine, and Psychology, 1st ed. CRC Press: Boca Raton, FL, USA, 2011.
  11. D. Evans, The importance of proper roadway design, In Handbook of Driving Simulation for Engineering, Medicine, and Psychology, 1st ed. CRC Press: Boca Raton, FL, USA, 2011.
  12. Y. Papelis, O. Ahmad, and M. Schikore. (2001, June). Scenario definition and control for the national advanced driving simulator. SAE Technical Paper[Online]. Available: https://www.sae.org/publications/technical-papers/content/2001-06-0219.
  13. H. A. Stoner, D. L. Fisher, and M. Mollenhauer, Simulator and scenario factors influencing simulator sickness, In Handbook of Driving Simulation for Engineering, Medicine, and Psychology, 1st ed. CRC Press: Boca Raton, FL, USA, 2011.
  14. J. Mueller, L. Stanley, T. Martin, and C. Gallagher, "Driving simulator and scenario effects on driver response," in Proceedings of IIE Annual Conference, Toronto, Canada, pp. 507, 2014.
  15. J. A. Mueller, "Driving in a simulator versus on-road: the effect of increased mental effort while driving on real roads and a driving simulator," Ph. D. dissertation, Montana State University, Bozeman, MT. 2015 [Online]. Available: https://scholarworks.montana.edu/xmlui/handle/1/9068.
  16. D. Liu, N. D. Macchiarella, and D. A. Vincenzi, "Simulation fidelity," in Human Factors in Simulation and Ttraining, 1st ed. CRC Press: Boca Raton, FL, USA, pp. 61-73, 2008.
  17. J. De Winter, P. A. Wieringa, J. Dankelman, M. Mulder, M. M. Van Paassen, and S. De Groot, "Driving simulator fidelity and training effectiveness," in Proceedings of the 26th European Annual Conference on Human Decision Making and Manual Control, Lyngby, Denmark, pp. 20-22, 2007.
  18. D. A. Noyce and M. V. Chitturi. (2018, February). Virtual road safety audits: Recommended procedures for using driving simulation and technology to expand existing practices. Repository & Open Science Access Portal [Online] pp. 1-47. Available: https://rosap.ntl.bts.gov/view/dot/35567.
  19. K. Santiago-Chaparro, M. DeAmico, A. Bill, M. Chitturi, and D. Noyce, "Realistic-scenario creation process for virtual road safety audits," Advances in Transportation Studies, vol. 2011, pp. 19-28, Dec. 2011.
  20. J. F. Dols, J. Molina, F. J. Camacho, J. Marin-Morales, A. M. Perez-Zuriaga, and A. Garcia, "Design and development of driving simulator scenarios for road validation studies," Transportation Research Procedia, vol. 18, no. 2016, pp. 289-296, Jun. 2016. https://doi.org/10.1016/j.trpro.2016.12.038
  21. D. Nabors and J. Soika. (2013, July). Road safety audit case studies: Using three-dimensional design visualization in the road safety audit process. [Online]. Available: https://safety.fhwa.dot.gov/rsa/case_studies/fhwasa14003/fhwasa14003.pdf.
  22. J. Cremer, J. Kearney, Y. Papelis, and R. Romano, "The software architecture for scenario control in the Iowa driving simulator," Proceedings of the 4th Computer Generated Forces and Behavioral Representation, Orlando, FL, pp. 1-9, 1994.
  23. J. Cremer, J. Kearney, and Y. Papelis, "Driving simulation: challenges for VR technology," IEEE Computer Graphics and Applications, vol. 16, no. 1, pp. 16-20, Sep. 1996. https://doi.org/10.1109/38.481562
  24. S. Bayarri, M. Fernandez, and M. Perez, "Virtual reality for driving simulation," Communications of the ACM, vol. 39, no. 5, pp. 72-76, May. 1996. https://doi.org/10.1145/229459.229468
  25. S. Sahami and T. Sayed, "How drivers adapt to drive in driving simulator, and what is the impact of practice scenario on the research?," Transportation Research Part F: Traffic Psychology and Behaviour, vol. 16, no. 2013, pp. 41-52, Jan. 2013. https://doi.org/10.1016/j.trf.2012.08.003
  26. Seoul. Public open API [Internet]. Available: http://data.seoul.go.kr/dataList/OA-13291/A/1/datasetView.do.
  27. T. Eiter, H. Fureder, F. Kasslatter, J. X. Parreira, and P. Schneider, "Towards a semantically enriched local dynamic map," International Journal of Intelligent Transportation Systems Research, vol. 17, no. 1, pp. 32-48, Mar. 2019. https://doi.org/10.1007/s13177-018-0154-x
  28. ISO. ISO/TS 18750:2015: Intelligent Transport Systems - Cooperative Systems - Definition of a Global Concept for Local Dynamic Maps [Internet]. Available: https://www.iso.org/standard/63273.html.
  29. ETSI. ETSI TR 102 863 (V1.1.1): Intelligent Transport Systems (ITS); Vehicular Communications; Basic Set of Applications; Local Dynamic Map (LDM); Rationale for and Guidance on Standardization [Internet]. Available: https://www.etsi.org/deliver/etsi_tr/102800_102899/102863/01.01.01_60/tr_102863v010101p.pdf.
  30. ETSI. ETSI EN 302 895 (V1.1.0): Intelligent transport systems - Extension of map database specifications for Local Dynamic Map for applications of Cooperative ITS [Internet]. Available: https://www.etsi.org/deliver/etsi_en/302800_302899/302895/01.01.01_60/en_302895v010101p.pdf.
  31. H. Shimada, A. Yamaguchi, H. Takada, and K. Sato, "Implementation and evaluation of local dynamic map in safety driving systems," Journal of Transportation Technologies, vol. 5, no. 2, pp. 102-112, Mar. 2015. https://doi.org/10.4236/jtts.2015.52010
  32. A. Imawan and J. Kwon, "A timeline visualization system for road traffic big data," in 2015 IEEE International Conference on Big Data (Big Data), Santa Clara: CA, pp. 2928-2929, 2015.
  33. B. Cao, Z. Yang, and H. Zhu, "Fusion and integration framework study on road network and dynamic traffic data in vehicle navigation," in 2009 Third International Symposium on Intelligent Information Technology Application Workshops, Nanchang, China, pp. 70-73. 2009.
  34. E. Paikari, M. Moshirpour, R. Alhajj, and B. H. Far, "Data integration and clustering for real time crash prediction," in Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014), Redwood City: CA, pp. 537-544, 2014.
  35. El Abdallaoui, H. El Alaoui, A. El Fazziki, F. Z. Ennaji, and M. Sadgal, "A system for collecting and analyzing road accidents big data," in 2019 15th International Conference on Signal-Image Technology &Internet-Based Systems (SITIS), Sorrento, Italy, pp. 663-671, 2019.
  36. Python Software Foundation. Python [Internet]. Available: https://www.python.org/.
  37. C. Alberca, S. Pastrana, G. Suarez-Tangil, and P. Palmieri, "Security analysis and exploitation of arduino devices in the internet of things," in Proceedings of the ACM International Conference on Computing Frontiers, New York: NY, pp. 437-442, 2016.
  38. M. Bogdan, "Traffic light using arduino uno and LabVIEW," in Proceedings of the 12th International Conference on Virtual Learning ICVL, Bucharest, Romania, pp. 286-290, 2017.
  39. J. Mabrouki, M. Azrour, D. Dhiba, Y. Farhaoui, and S. El Hajjaji, "IoT-based data logger for weather monitoring using arduino-based wireless sensor networks with remote graphical application and alerts," Big Data Mining and Analytics, vol. 4, no. 1, pp. 25-32, Jan. 2021. https://doi.org/10.26599/BDMA.2020.9020018
  40. A. Nayyar and V. Puri, "A review of Arduino board's, lilypad's & arduino shields," in 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), New Delhi, India, pp. 1485-1492, 2016.
  41. V. M. Cvjetkovic and U. Stankovic, "Arduino based physics and engineering remote laboratory," in International Conference on Interactive Collaborative Learning, Belfast, UK, pp. 560-574, 2016.
  42. Y. Lin, Y. Lin, M. Yang, and J. Lin, "ArduTalk: An arduino network application development platform based on IoTtalk," IEEE Systems Journal, vol. 13, no. 1, pp. 468-476, Nov. 2017. https://doi.org/10.1109/jsyst.2017.2773077
  43. A. Kurniawan. (2015, March). The hands-on arduino yun manual lab. PE Press [Online]. pp. 1-93. Available: https://play.google.com/store/books/details?id=YDcABwAAQBAJ.
  44. Korea Meteorological Administration. Weather AWS [Internet]. Available: https://www.weather.go.kr/m/obs/aws.jsp.
  45. X. Li, X. Yan, and S. C. Wong, "Effects of fog, driver experience and gender on driving behavior on s-curved road segments," Accident Analysis &Prevention, vol. 77, no. 1, pp. 91-104, Apr. 2015. https://doi.org/10.1016/j.aap.2015.01.022
  46. Q. Shangguan, T. Fu, and S. Liu, "Investigating rear-end collision avoidance behavior under varied foggy weather conditions: A study using advanced driving simulator and survival analysis," Accident Analysis & Prevention, vol. 139, no. 1, pp. 1-14, May. 2020.
  47. C. Chen, X. Zhao, H. Liu, G. Ren, Y. Zhang, and X. Liu, "Assessing the influence of adverse weather on traffic flow characteristics using a driving simulator and VISSIM," Sustainability, vol. 11, no. 3, pp. 1-16, Feb. 2019.
  48. G. Yang, M. M. Ahmed, and S. Gaweesh, "Impact of variable speed limit in a connected vehicle environment on truck driver behavior under adverse weather conditions: driving simulator study," Transportation Research Record, vol. 2673, no. 7, pp. 132-142, Apr. 2019. https://doi.org/10.1177/0361198119842111
  49. H. Tu, Z. Li, H. Li, K. Zhang, and L. Sun, "Driving simulator fidelity and emergency driving behavior," Transportation Research Record, vol. 2518, no. 1, pp. 113-121, Apr. 2015. https://doi.org/10.3141/2518-15
  50. M. Sarvi, M. Kuwahara, and A. Ceder, "Freeway ramp merging phenomena in congested traffic using simulation combined with a driving simulator," Computer-Aided Civil and Infrastructure Engineering, vol. 19, no. 5, pp. 351-363, Jun. 2004. https://doi.org/10.1111/j.1467-8667.2004.00362.x
  51. I. Kim, G. S. Larue, L. Ferreira, A. Rakotonirainy, and K. Shaaban, "Traffic safety at road-rail level crossings using a driving simulator and traffic simulation," Transportation Research Record, vol. 2476, no. 1, pp. 109-118, Jan. 2015. https://doi.org/10.3141/2476-15
  52. X. Zou, S. O'Hern, B. Ens, S. Coxon, P. Mater, R. Chow, M. Neylan, and H. L. Vu, "On-road virtual reality autonomous vehicle (VRAV) simulator: An empirical study on user experience," Transportation Research Part C: Emerging Technologies, vol. 126, no. 1, May. 2021.