The Frontiers of Society, Science and Technology, 2021, 3(2); doi: 10.25236/FSST.2021.030205.
Xinyu Zhang1, Xinyu Chen2, Haolun Cheng3, Yue Yu4
1School of Optoelectronic and Science and Engineering, University of Electronic and Technology of China, Chengdu, Sichuan 611731, China
2College of Letters and Science, UCSB, Goleta, California 93117, United States
3School of Arts and Science, Rutgers University-New Brunswick, New Brunswick, 08901, United States
4Hangzhou No.2 High School, Hangzhou, Zhejiang 310000, China
In view of the instability and high-risked motor vehicle collision, this work proposes an Assisted Driving System (ADS) based on Internet of Things (IoT) concepts to prevent traffic accident. In detail, ADS utilizes Automated Emergency Braking (AEB) and embedded actuators in the steering wheel to control the vehicle in an emergency situation. AEB consists of four different subsystems that allow the vehicle to recognize potential collision and need to full-stop in interaction with pedestrian, biker, another vehicle, and infrastructure. Pedestrians and bikers need an application or Simplified System Device (SSD) to receive feedback from the interaction. Radar sensors, front-camera, RFID sensor and Speedometer also allow the ADS to operate on a single-vehicle circumstances. It is believed that the proposed system of this work has great application prospects.
Internet of Things (IoT), Assisted Driving System, Collision Avoiding, Automated Emergency Braking
Xinyu Zhang, Xinyu Chen, Haolun Cheng, Yue Yu. The Application Study of the Assisted-Driving System Based on Internet of Things System. The Frontiers of Society, Science and Technology (2021) Vol. 3, Issue 2: 27-34. https://doi.org/10.25236/FSST.2021.030205.
[1] Nhan Tran. Global status report on road safety 2018 [D]. Geneva: World Health Organization, 2018. 2018: 1 – 3.
[2] Rajesh Subramanian. Motor Vehicle Traffic Crashes as a Leading Cause of Death in the United States, 2002 [D]. Washington. D. C.: National Highway Traffic Safety Administration, 2002. 2002: 1 – 2.
[3] Musarra G, Lyons A, Conca E, et al. Non-Line-of-Sight Three-Dimensional Imaging with a Single-Pixel Camera [J], PHYSICAL REVIEW APPLIED, 2019, Volume 12, Issue 1, July: 011002.
[4] Vehicle Speed Sensor (VSS). (Sensors) (Brief Article) [J]. Motor Age, 2003, Volume 122, Issue 8, August: 43.
[5] Adarsh P S , Sachin C. Embedded Machine Learning-Based Data Reduction in Application-Specific Constrained IoT Networks [J]. SAC '20: Proceedings of the 35th Annual ACM Symposium on Applied Computing, 2020, March: 747–753.
[6] Qing L, Fengxiang Q, Xiaobing W, Lei Y. Drivers' smart advisory system improves driving performance at STOP sign intersections [J]. Journal of Traffic and Transportation Engineering, 2017, Volume 4, Issue 3, June: 262-271.
[7] Debargha D, Marieke M, Berry E, Jacques T. The Impact of Vehicle Appearance and Vehicle Behavior on Pedestrian Interaction with Autonomous Vehicles [J]. AutomotiveUI '20: 12th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 2017, September: 158-162.
[8] James C. Owens. Jack Danielson. Fatality Analysis Reporting System (FARS) [P]. Washington D.C.: National Highway Traffic Safety Administration, 2018.
[9] Glenn R. W, Michele K. D, Lisa H, et al. Comparison of Lidar-Based and Radar-Based Adaptive Cruise Control Systems [J]. SAE transactions, 2000, 109: 126-139.