Browse > Article
http://dx.doi.org/10.17661/jkiiect.2020.13.2.129

A design of Optimized Vehicle Routing System(OVRS) based on RSU communication and deep learning  

Son, Su-Rak (Department of Software Engineering, Catholic kwandong University)
Lee, Byung-Kwan (Department of Software Engineering, Catholic kwandong University)
Sim, Son-Kweon (Department of Geography Education, Catholic kwandong University)
Jeong, Yi-Na (Department of Software Engineering, Catholic kwandong University)
Publication Information
The Journal of Korea Institute of Information, Electronics, and Communication Technology / v.13, no.2, 2020 , pp. 129-137 More about this Journal
Abstract
Currently, The autonomous vehicle market is researching and developing four-level autonomous vehicles beyond the commercialization of three-level autonomous vehicles. Because unlike the level 3, the level 4 autonomous vehicle has to deal with an emergency directly, the most important aspect of a four-level autonomous vehicle is its stability. In this paper, we propose an Optimized Vehicle Routing System (OVRS) that determines the route with the lowest probability of an accident at the destination of the vehicle rather than an immediate response in an emergency. The OVRS analyzes road and surrounding vehicle information collected by The RSU communication to predict road hazards, and sets the route for the safer and faster road. The OVRS can improve the stability of the vehicle by executing the route guidance according to the road situation through the RSU on the road like the network routing method. As a result, the RPNN of the ASICM, one of the OVRS modules, was about 17% better than the CNN and 40% better than the LSTM. However, because the study was conducted in a virtual environment using a PC, the possibility of accident of the VPDM was not actually verified. Therefore, in the future, experiments with high accuracy on VPDM due to the collection of accident data and actual roads should be conducted in real vehicles and RSUs.
Keywords
Autonomous vehicles; driving directions; deep neural networks; road side units; road information;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
연도 인용수 순위
1 Byeongjoon Noh, Wonjun No, ,Jaehong Lee, David Lee, "Vision-Based Potential Pedestrian Risk Analysis on Unsignalized Crosswalk Using Data Mining Techniques", Applied Sciences, Vol. 10, No. 3, February, 2020.
2 Dario Vangi, Carlo Cialdai, Michelangelo-Santo Gulino, Kjell Gunnar Robbersmyr, "Vehicle Accident Databases: Correctness Checks for Accident Kinematic Data", Designs, Vol. 2, No. 1, January, 2018.   DOI
3 Jhihoon Joo, Odongo Steven Eyobu, Ji Hun Kim, Hong-Jong Jeong, Dong Seog Han, "Analysis of Radio Propagation Characteristics for V2V Scenarios in WAVE Standard Based Vehicular Communication System", The Journal of Korean Institute of Communications and Information Sciences. Vol. 42 No. 6, pp. 1175-1184, 2017   DOI
4 Bongsue Suh, "Performance Analysis of RSUs in Probability-Based Data Delivery Strategy for Energy-Constrained V2I Systems". The Journal of Korean Institute of Information Technology, Vol. 16 No.11, pp. 69-76, 2018
5 Seok-Gyu Park, Heui-Hak Ahn, Yi-Na Jeuong, "Preventing Communication Disruption in the Urban Environment Using RRPS (RSU Request Priority Scheduling)", Journal of Korea Institute of Information, Electronics, and Communication Technology, Vol.9 No.6, pp. 584-590, 2016   DOI
6 Jungmin Kwon, Hyunggon Park, "Data Driven Reliable Dissemination Strategy Based Systematic Network Coding in V2I Networks", The Journal of Korean Institute of Communications and Information Sciences, Vol.45 No.2, pp. 327-336, 2020   DOI
7 Bongsue Suh, "Variable Transmission Distance-Based Data Delivery Strategy to Support Near-Optimal Delivery Delay for V2I Systems", The Journal of Korean Institute of Information Technology, Vol.17 No.12, pp. 93-100, 2019   DOI
8 Eum Han, Ilsoo Yun, Sang Soo Lee, Kitae Jang, ․Byungkyu Park, "Development of Real-time Traffic Signal Control Strategy for Coordinated Signalized Intersections under V2I Communication Environment", The Journal of The Korea Institute of Intelligent Transportation Systems, Vol.17, No.3, pp. 59-71, 2018   DOI
9 Kyoung Soo Bok, Seung Wan Hong, Jae Hog Cha, Jong Tae Lim, Jaesoo Yoo, "Cooperative RSU Scheduling for Efficient Data Dissemination in VANET Environments", JOURNAL OF THE KOREA CONTENTS ASSOCIATION, Vol.13 No.10, pp. 27-36, 2013   DOI
10 YiNa Jeong, SuRak Son, ByungKwan Lee, "he Lightweight Autonomous Vehicle Self-Diagnosis (LAVS) Using Machine Learning Based on Sensors and Multi-Protocol IoT Gateway", Sensor, Vol. 19, No. 11, June, 2019.