ROC Ministry of Digital Affairs. Historical traffic accident data. (2022, Dec 13).[Online]. Available: https://data.gov.tw/dataset/12197
European-Union, “Regulation (eu) 2019/2144 of the european parliament and of the council of 27 november 2019 on type-approval requirements for motor vehicles and their trailers, and systems, components and separate technical units intended for such vehicles, as regards their general safety and the protection of vehicle occupants and vulnerable road users, amending regulation (eu) 2018/858 of the european parliament and of the council and repealing regulations (ec) no 78/2009, (ec) no 79/2009 and (ec) no 661/2009 of the european parliament and of the council and commission regulations (ec) no 631/2009, (eu) no 406/2010, (eu) no 672/2010, (eu) no 1003/2010, (eu) no 1005/2010, (eu) no 1008/2010, (eu) no 1009/2010, (eu) no 19/2011, (eu) no 109/2011, (eu) no 458/2011, (eu) no 65/2012, (eu) no 130/2012, (eu) no 347/2012, (eu) no 351/2012, (eu) no 1230/2012 and (eu) 2015/166 (text with eea relevance),” Official Journal L325, vol. 1, p. 1, 2019-11-27.
A. Association et al., “Advanced driver assistance systems (adas) repair costs,” AAAssociation, newsroom. AAA. com: American Automobile Association, 2018.
J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, “You only look once: Unified, real-time object detection,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2016.
J. Redmon and A. Farhadi, “Yolo9000: Better, faster, stronger,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 2017.
J. Redmon and A. Farhadi, “Yolov3: An incremental improvement,” arXiv preprint arXiv:1804.02767, 2018.
A. Bochkovskiy, C.-Y. Wang, and H.-Y. M. Liao, “Yolov4: Optimal speed and ac- curacy of object detection,” arXiv preprint arXiv:2004.10934, 2020.
S. Ren, K. He, R. Girshick, and J. Sun, “Faster r-cnn: Towards real-time object detection with region proposal networks,” Advances in neural information processing systems, vol. 28, 2015.
A. Bewley, Z. Ge, L. Ott, F. Ramos, and B. Upcroft, “Simple online and realtime tracking,” in 2016 IEEE International Conference on Image Processing (ICIP), 2016, pp. 3464–3468.
N. Wojke, A. Bewley, and D. Paulus, “Simple online and realtime tracking with a deep association metric,” in 2017 IEEE International Conference on Image Process- ing (ICIP), 2017, pp. 3645–3649.
M. Brostrm, “Real-time multi-object tracker using yolov5 and deep sort,” https://github.com/mikel-brostrom/Yolov5DeepSortP ytorch, 2020.
D. Fern ́andez Llorca, A. Herna ́ndez Mart ́ınez, and I. Garc ́ıa Daza, “Vision-based vehicle speed estimation: A survey,” IET Intelligent Transport Systems, vol. 15, no. 8, pp. 987– 1005, 2021.
C.-J. Lin, S.-Y. Jeng, and H.-W. Lioa, “A real-time vehicle counting, speed estimation, and classification system based on virtual detection zone and yolo,” Mathematical Prob- lems in Engineering, vol. 2021, 2021.
S. Javadi, M. Dahl, and M. I. Pettersson, “Vehicle speed measurement model for video- based systems,” Computers Electrical Engineering, vol. 76, pp. 238–248, 2019. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0045790618317774
Z. Czapla, “Vehicle speed estimation with the use of gradient-based image conversion into binary form,” in 2017 Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), 2017, pp. 213–216.
C. Liu, D. Q. Huynh, Y. Sun, M. Reynolds, and S. Atkinson, “A vision-based pipeline for vehicle counting, speed estimation, and classification,” IEEE Transactions on Intelligent Transportation Systems, vol. 22, no. 12, pp. 7547–7560, 2021.
Wi-Fi Alliance., “discover-wi-fi,” https://www.wi-fi.org/discover-wi-fi, 2022.
Bluetooth SIG, Inc., “Bluetooth technology overview,” https://www.bluetooth.com/learn-about-bluetooth/tech-overview/, 2022.
3GPP, “Release 16,” https://www.3gpp.org/release-16, 2021.
“LoRa and LoRaWAN: Technical overview,” 2015. [Online]. Available: https://lora- developers.semtech.com
Y. Xu, Y. Ge, D. Wei, R. Yu, J. Wang, and Z. Yao, “V2v test scenario-study on intersec- tion collision warning,” in 2021 IEEE 93rd Vehicular Technology Conference (VTC2021- Spring), 2021, pp. 1–5.
5G-PPP, “5g automotive vision,” 5G Infrastructure Public Private Partnership (5GPPP), White paper, 2015.
M. Islam, M. Rahman, M. Chowdhury, G. Comert, E. D. Sood, and A. Apon, “Vision- based pedestrian alert safety system (pass) for signalized intersections,” arXiv preprint arXiv:1907.05284, 2019.
J. C. Hayward, “Near miss determination through use of a scale of danger,” 1972.
A. Svensson, A method for analysing the traffic process in a safety perspective. Lund Institute of Technology Sweden, 1998.
R. Van Der Horst and J. Hogema, “Time-to-collision and collision avoidance systems,” 1993.
S. HIRST, “The format and presentation of collision warnings,” Ergonomics & Safety of Intelligent Driver Interface, 1997.
N. Aksan, L. Sager, S. Hacker, R. Marini, J. Dawson, S. Anderson, and M. Rizzo, “For- ward collision warning: clues to optimal timing of advisory warnings,” SAE International journal of transportation safety, vol. 4, no. 1, p. 107, 2016.
 J. Pan and J. McElhannon, “Future edge cloud and edge computing for internet of things applications,” IEEE Internet of Things Journal, vol. 5, no. 1, pp. 439–449, 2018.
M. Satyanarayanan, “The emergence of edge computing,” Computer, vol. 50, no. 1, pp. 30–39, 2017.
A. E. Eshratifar, A. Esmaili, and M. Pedram, “Bottlenet: A deep learning architec- ture for intelligent mobile cloud computing services,” in 2019 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), 2019, pp. 1–6.
許添本, 蒙以亨, 吳榮煌, 劉培森, 廖彥程, 李芊, 林謙, 蕭唯倫, 趙士淵, and 張佳雯, 車聯 網技術應用於機車安全改善之研究與場域試驗計畫. 中華民國交通部, 2019.
許添本, 蒙以亨, 劉培森, 黃暉慈, 張太乙, 李芊, 賴聖, 林謙, 廖彥程 et al., 聯網智慧機車 安全暨共享場域試驗研究計畫. 中華民國交通部, 2021.
S. Farrell, “Low-power wide area network (lpwan) overview,” Tech. Rep., 2018.
J. M. Marais, R. Malekian, and A. M. Abu-Mahfouz, “Lora and lorawan testbeds: A review,” 2017 Ieee Africon, pp. 1496–1501, 2017.
 “MQTT: The Standard for IoT Messaging,” 2022. [Online]. Available: https://mqtt.org/
J. Zhang, W. Xiao, B. Coifman, and J. P. Mills, “Vehicle tracking and speed estimation from roadside lidar,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 5597–5608, 2020.
R. A. Light, “Mosquitto: server and client implementation of the mqtt protocol,” Journal of Open Source Software, vol. 2, no. 13, p. 265, 2017.
G. Jocher. YOLOv5. [Online]. Available: https://github.com/ultralytics/yolov5