Abstract
The domain of fully Autonomous Vehicles (AVs) as an application of the IoT paradigm may help reduce accidents and improve traffic conditions. However, for end-users it raises concerns about safety and security. To fully embrace AV technology and address the end-user skepticism, users should be able to comprehend and trust the decisions made by the intelligent systems within the AV. To address this challenge, the objectives of this research are threefold. First, to understand the users’ concerns about the safety and security of AVs through a comprehensive social media analysis using platforms such as Twitter and Reddit. Second, to analyze the publicly available policy documents released by governing bodies such as the U.S. Department of Transportation and the European Commission to assess the focus of the governing policies in this sector. Third, to compare and contrast the findings of the first two objectives to identify the gaps and overlaps between the current government regulations and various users’ concerns and explain how these concerns are being acknowledged or need to be addressed with the use of software or hardware such that it will harbor public trust in adopting the technology of fully autonomous vehicles.
This project was partially supported by grants CNS-1852475 and CNS-1938687.
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References
Baker, R.T., Wagner, J.: Policy pathways to vehicle automation: industry perspectives on the role of public policy in autonomous vehicle development. In: 2013 International Conference on Connected Vehicles and Expo (ICCVE), pp. 431–436 (2013)
Blömacher, K., Nöcker, G., Huff, M.: The evolution of mental models in relation to initial information while driving automated. Transport. Res. F: Traffic Psychol. Behav. 68, 198–217 (2020)
Chen, X., Zeng, H., Xu, H., Di, X.: Sentiment analysis of autonomous vehicles after extreme events using social media data. In: 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), pp. 1211–1216 (2021)
Cohen, T., et al.: A constructive role for social science in the development of automated vehicles. Transp. Res. Interdiscipl. Perspect. 6, 100133 (2020)
Coppola, P., Silvestri, F.: Autonomous vehicles and future mobility solutions. In: Coppola, P., Esztergár-Kiss, D. (eds.) Autonomous Vehicles and Future Mobility, pp. 1–15. Elsevier (2019)
Ding, Y., Korolov, R., (Al) Wallace, W., Wang, X.C.: How are sentiments on autonomous vehicles influenced? An analysis using twitter feeds. Transp. Res. Part C: Emerg. Technol. 131, 103356 (2021)
Dirsehan, T., Can, C.: Examination of trust and sustainability concerns in autonomous vehicle adoption. Technol. Soc. 63, 101361 (2020)
Dokic, J., Müller, B., Meyer, G.: European roadmap smart systems for automated driving, April 2015
Gandhi, U.D., Malarvizhi Kumar, P., Chandra Babu, G., Karthick, G.: Sentiment analysis on twitter data by using convolutional neural network (CNN) and long short term memory (LSTM). Wirel. Person. Commun. 1–10 (2021). https://doi.org/10.1007/s11277-021-08580-3
Hulse, L.M., Xie, H., Galea, E.R.: Perceptions of autonomous vehicles: relationships with road users, risk, gender and age. Saf. Sci. 102, 1–13 (2018)
Hussain, Q., Alhajyaseen, W.K., Adnan, M., Almallah, M., Almukdad, A., Alqaradawi, M.: Autonomous vehicles between anticipation and apprehension: investigations through safety and security perceptions. Transp. Policy 110, 440–451 (2021)
Jefferson, J., McDonald, A.D.: The autonomous vehicle social network: analyzing tweets after a recent tesla autopilot crash. Proc. Hum Factors Ergonom. Soc. Annl Meet. 63(1), 2071–2075 (2019)
Legacy, C., Ashmore, D., Scheurer, J., Stone, J., Curtis, C.: Planning the driverless city. Transp. Rev. 39(1), 84–102 (2019)
McDonald, T., et al.: Data mining twitter to improve automated vehicle safety Tech Report, February 2021. https://rosap.ntl.bts.gov/view/dot/56364,
Pyrialakou, V., Gkartzonikas, C., Gatlin, J., Gkritza, K.: Perceptions of safety on a shared road: Driving, cycling, or walking near an autonomous vehicle. J. Safety Res. 72, 249–258 (2020)
Sadiq, R., Khan, M.: Analyzing self-driving cars on twitter. arXiv preprint arXiv:1804.04058 (2018)
Sindi, S., Woodman, R.: Autonomous goods vehicles for last-mile delivery: Evaluation of impact and barriers. In: 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), pp. 1–6 (2020)
Younang, V.: GitHub link containing the documents, code and link source used for our analysis, September 2022. https://github.com/victorine07/av-social-mefia-analysis
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Wakam Younang, V.C., Yang, J., Jacuinde, L.G., Sen, A. (2023). A Comparative Analysis of User’s Concerns and Government Policies on Autonomous Vehicles. In: Tekinerdogan, B., Wang, Y., Zhang, LJ. (eds) Internet of Things – ICIOT 2022. ICIOT 2022. Lecture Notes in Computer Science, vol 13735. Springer, Cham. https://doi.org/10.1007/978-3-031-23582-5_4
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