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Otonom Araçların Benimsenmesi ve Güvenlik Algılarının İncelenmesi

Year 2021, , 633 - 639, 31.12.2021
https://doi.org/10.31590/ejosat.1039725

Abstract

Çevresel algılama özelliklerine sahip olan seviye “3” otonom araçların çok yakın bir zamanda tüm araçlarda görülmesi beklenirken, sürücünün sürüş görevini ortadan kaldıran seviye "5" otonom araçların ise on sene içerisinde ticarileştirileceği düşünülmektedir. Seviye "5" otonom araçların sürdürülebilir kentsel hareketliliği arttıracağı ve insan kaynaklı hataları azaltıp trafik kazalarını azaltması beklenmektedir. Bununla birlikte bu teknolojinin çeşitli güvenlik sorunlarını da beraberinde getireceği düşünülmektedir. Bu noktada yeni teknoloji ürünü olacak bu araçların benimsenip benimsenmeyeceği önemli bir konudur. Bu çalışmada otonom araçların benimsenmesini etkileyecek faktörler incelenecek olup, aynı zamanda kişilerin bu araçlara karşı güvenlik algıları araştırılacaktır. Araştırma sonucu çıkacak bulguların, otonom araçlar ile ilgili karar vericiler ve politika belirleyiciler için yararlı olması beklenmektedir.

References

  • Bakioglu, G., & Atahan, A. O. (2020). Evaluating the Influencing Factors on Adoption of Self-driving Vehicles by Using Interval-Valued Pythagorean Fuzzy AHP. In International Conference on Intelligent and Fuzzy Systems (pp. 503-511). Springer, Cham. Bakioglu, G., & Atahan, A. O. (2021). AHP integrated TOPSIS and VIKOR methods with Pythagorean fuzzy sets to prioritize risks in self-driving vehicles. Applied Soft Computing, 99, 106948.
  • Bansal, P., Kockelman, K.M. (2016). Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies.
  • Begg, D. (2014). A 2050 vision for London: What are the implications of driverless transport, transport times, London, UK.
  • Brell, T., Philipsen, R., Ziefle, M. (2018). sCARy! Risk perceptions in autonomous driving: the influence of experience on perceived benefits and barriers. Risk Anal. 39 (2), 342–357. https://doi.org/10.1111/risa.13190.
  • Casley, S.V., Jardim, A.S., Quartulli, A.M. (2013). Study of public acceptance of autonomous cars, interactive qualifying project, Worcester Polytechnic Institute.
  • Chen D., Ahn S., Chitturi M., Noyce D.A. (2017). Towards vehicle automation: Roadway capacity formulation for traffic mixed with regular and automated vehicles, Transp. Res. Part B Methodol. 100, 196–221
  • Choi, J.K., Ji, Y.G. (2015). Investigating the importance of trust on adopting an autonomous vehicle. Int. J. Hum. Comput. Interact. 31 (10), 692–702.
  • Dixit VV, Chand S, Nair DJ. (2016). Autonomous vehicles: disengagements, accidents and reaction times. PLoS one, 11(12), p.e0168054. https://doi.org/10.1371/journal.pone.0168054
  • Fagnant, D.J., Kockelman, K. (2015). Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations. Transport. Res. Pol. Pract. 77, 167–181.
  • Favarò, F.M., Nader, N., Eurich, S.O., Tripp, M., Varadaraju, N. (2017). Examining accident reports involving autonomous vehicles in California.
  • Gkartzonikas C., Gkritza K. (2019). What have we learned? A review of stated preference and choice studies on autonomous vehicles. Transportation Research Part C, vol.98, 323–337.
  • Howard, D., Dai, D. (2014). Public perceptions of self-driving cars: the case of Berkeley, California. In: Paper Presented at the 93rd Annual Meeting of the Transportation Research Board, Washington D.C.
  • König, M. and Neumayr, L. (2017) Users’ resistance towards radical innovations: The case of the self-driving car. Transportation Research Part F: Traffic Psychology and Behaviour. 44, 42-52.
  • Kyriakidis, M., Happee, R., De Winter, J.C.F. (2015). Public opinion on automated driving: Results of an international questionnaire among 5000 respondents. Transportation Res. Part F: Traffic Psychol. Behav. 32, 127–140.
  • NHTSA (2021). https://www.nhtsa.gov/technology-innovation/automated-vehicles-safety
  • Noy, I. Y., Shinar, D., & Horrey, W. J. (2018). Automated driving: Safety blind spots. Safety science, 102, 68-78.
  • Payre, W., Cestac, J., Delhomme, P. (2014). Intention to use a fully automated car: Attitudes and a priori acceptability. Transportation Res. Part F: Traffic Psychol. Behav. 27 (PB), 252–263.
  • Pettigrew, S., Dana, L. M., & Norman, R. (2019). Clusters of potential autonomous vehicles users according to propensity to use individual versus shared vehicles. Transport Policy, 76, 13-20.
  • Power, J.D. (2012). Vehicle owners show willingness to spend on automotive infotainment features, Technical Report, Westlake Village.
  • SAE International standard J3016: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles J3016 (2018)
  • Sanbonmatsu, D.M., Strayer, D.L., Yu, Z., Biondi, F., Cooper, J.L. (2018). Cognitive underpinnings of beliefs and confidence in beliefs about fully automated vehicles. Transp. Res. Part F 55, 114–122.
  • Schoettle, B., Sivak, M.,. A. (2014). Survey of public opinion about connected vehicles in the U.S., the U.K., and Australia. 2014 International Conference on Connected Vehicles and Expo (ICCVE), Vienna, pp. 687–692
  • Shabanpour, R., Golshani, N., Shamshiripour, A., Mohammadian, A.K. (2018). Eliciting preferences for adoption of fully automated vehicles using best-worst analysis. Transportation Res. Part C: Emerging Technol. 93, 463–478.
  • Shin, J., Bhat, C. R., You, D., Garikapati, V. M., & Pendyala, R. M. (2015). Consumer preferences and willingness to pay for advanced vehicle technology options and fuel types. Transportation Research Part C: Emerging Technologies, 60, 511-524.
  • World Health Organization. WHO Director-General’s opening remarks at the media briefing on COVID-19. 2020.

Investigating the Safety Perception and Adoption of Autonomous Vehicle

Year 2021, , 633 - 639, 31.12.2021
https://doi.org/10.31590/ejosat.1039725

Abstract

With the advancement of technology, transportation systems have started to transform the way of digitalization. Level 3 autonomous vehicle having the capability of environmental detection will nearly be available for all vehicles soon. Level 5 self-driving vehicles will probably be commercialized within 10 years, and these vehicles are expected to enhance the sustainable urban mobility and decrease the traffic crashes caused by human error. However, new technology may bring some safety and security issues. In this regard, adoption of autonomous vehicle will be of decisive importance. This study examines the factors affecting the adoption of autonomous vehicle, and safety and security perceptions towards those vehicles. The findings of this study will be conducive for decision-makers and policy-makers.

References

  • Bakioglu, G., & Atahan, A. O. (2020). Evaluating the Influencing Factors on Adoption of Self-driving Vehicles by Using Interval-Valued Pythagorean Fuzzy AHP. In International Conference on Intelligent and Fuzzy Systems (pp. 503-511). Springer, Cham. Bakioglu, G., & Atahan, A. O. (2021). AHP integrated TOPSIS and VIKOR methods with Pythagorean fuzzy sets to prioritize risks in self-driving vehicles. Applied Soft Computing, 99, 106948.
  • Bansal, P., Kockelman, K.M. (2016). Forecasting Americans’ long-term adoption of connected and autonomous vehicle technologies.
  • Begg, D. (2014). A 2050 vision for London: What are the implications of driverless transport, transport times, London, UK.
  • Brell, T., Philipsen, R., Ziefle, M. (2018). sCARy! Risk perceptions in autonomous driving: the influence of experience on perceived benefits and barriers. Risk Anal. 39 (2), 342–357. https://doi.org/10.1111/risa.13190.
  • Casley, S.V., Jardim, A.S., Quartulli, A.M. (2013). Study of public acceptance of autonomous cars, interactive qualifying project, Worcester Polytechnic Institute.
  • Chen D., Ahn S., Chitturi M., Noyce D.A. (2017). Towards vehicle automation: Roadway capacity formulation for traffic mixed with regular and automated vehicles, Transp. Res. Part B Methodol. 100, 196–221
  • Choi, J.K., Ji, Y.G. (2015). Investigating the importance of trust on adopting an autonomous vehicle. Int. J. Hum. Comput. Interact. 31 (10), 692–702.
  • Dixit VV, Chand S, Nair DJ. (2016). Autonomous vehicles: disengagements, accidents and reaction times. PLoS one, 11(12), p.e0168054. https://doi.org/10.1371/journal.pone.0168054
  • Fagnant, D.J., Kockelman, K. (2015). Preparing a nation for autonomous vehicles: opportunities, barriers and policy recommendations. Transport. Res. Pol. Pract. 77, 167–181.
  • Favarò, F.M., Nader, N., Eurich, S.O., Tripp, M., Varadaraju, N. (2017). Examining accident reports involving autonomous vehicles in California.
  • Gkartzonikas C., Gkritza K. (2019). What have we learned? A review of stated preference and choice studies on autonomous vehicles. Transportation Research Part C, vol.98, 323–337.
  • Howard, D., Dai, D. (2014). Public perceptions of self-driving cars: the case of Berkeley, California. In: Paper Presented at the 93rd Annual Meeting of the Transportation Research Board, Washington D.C.
  • König, M. and Neumayr, L. (2017) Users’ resistance towards radical innovations: The case of the self-driving car. Transportation Research Part F: Traffic Psychology and Behaviour. 44, 42-52.
  • Kyriakidis, M., Happee, R., De Winter, J.C.F. (2015). Public opinion on automated driving: Results of an international questionnaire among 5000 respondents. Transportation Res. Part F: Traffic Psychol. Behav. 32, 127–140.
  • NHTSA (2021). https://www.nhtsa.gov/technology-innovation/automated-vehicles-safety
  • Noy, I. Y., Shinar, D., & Horrey, W. J. (2018). Automated driving: Safety blind spots. Safety science, 102, 68-78.
  • Payre, W., Cestac, J., Delhomme, P. (2014). Intention to use a fully automated car: Attitudes and a priori acceptability. Transportation Res. Part F: Traffic Psychol. Behav. 27 (PB), 252–263.
  • Pettigrew, S., Dana, L. M., & Norman, R. (2019). Clusters of potential autonomous vehicles users according to propensity to use individual versus shared vehicles. Transport Policy, 76, 13-20.
  • Power, J.D. (2012). Vehicle owners show willingness to spend on automotive infotainment features, Technical Report, Westlake Village.
  • SAE International standard J3016: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles J3016 (2018)
  • Sanbonmatsu, D.M., Strayer, D.L., Yu, Z., Biondi, F., Cooper, J.L. (2018). Cognitive underpinnings of beliefs and confidence in beliefs about fully automated vehicles. Transp. Res. Part F 55, 114–122.
  • Schoettle, B., Sivak, M.,. A. (2014). Survey of public opinion about connected vehicles in the U.S., the U.K., and Australia. 2014 International Conference on Connected Vehicles and Expo (ICCVE), Vienna, pp. 687–692
  • Shabanpour, R., Golshani, N., Shamshiripour, A., Mohammadian, A.K. (2018). Eliciting preferences for adoption of fully automated vehicles using best-worst analysis. Transportation Res. Part C: Emerging Technol. 93, 463–478.
  • Shin, J., Bhat, C. R., You, D., Garikapati, V. M., & Pendyala, R. M. (2015). Consumer preferences and willingness to pay for advanced vehicle technology options and fuel types. Transportation Research Part C: Emerging Technologies, 60, 511-524.
  • World Health Organization. WHO Director-General’s opening remarks at the media briefing on COVID-19. 2020.
There are 25 citations in total.

Details

Primary Language Turkish
Subjects Engineering
Journal Section Articles
Authors

Gözde Bakioğlu 0000-0003-3754-2631

Ali Atahan 0000-0002-4800-4022

Publication Date December 31, 2021
Published in Issue Year 2021

Cite

APA Bakioğlu, G., & Atahan, A. (2021). Otonom Araçların Benimsenmesi ve Güvenlik Algılarının İncelenmesi. Avrupa Bilim Ve Teknoloji Dergisi(32), 633-639. https://doi.org/10.31590/ejosat.1039725