Proposal and Evaluation of a Dynamic Path Finding Method Using Potential Values Considering Time Series in Automatic Driving

Yıl 2022, Cilt: 6 Sayı: 4, 460 - 475, 30.12.2022

Tomofumi Matsuzawa , Akito Fukai

https://doi.org/10.31197/atnaa.1141666

Öz

Many studies have been conducted using obstacle hazard values, called potential method, for connected
autonomous vehicle. However, most studies were conducted for static obstacles, and those for dynamic
obstacles assumed an environment without oncoming or crossing vehicles. In this study, we devise an
algorithm for generating potential values considering time series characteristics using information that can
be obtained through inter-vehicle communication and propose a path ?nding algorithm that uses these
potential values. As an evaluation of the usefulness of the proposed method, we compare it with existing
potential methods. The results show that, in some situations, the route derived by the proposed method
is superior to the route derived by the existing potential method in terms of safety and timer to reach the
destination.

Anahtar Kelimeler

Automatic Driving, Autonomous vehicle, Path finding, Artificial potential method

Kaynakça

• 1] C. Liang, and H. Peng, (1998) Optimal Adaptive Cruise Control with Guaranteed String Stability, In Proceeding of 4th international Symposium on Advanced Vehicle Control 1998, pp. 717-728.
• [2] L. Li, J. Gan, X. Ji, Qu, and B. Ran, (2022) Dynamic Driving Risk Potential Field Model Under the Connected and Automated Vehicles Environment and Its Application in Car-Following Modeling, IEEE Transactions on Intelligent Trans- portation Systems, Vol. 23, No. 1, pp. 122-141.
• [3] Y. Yashiro, K. Eguchi, S. Iwasaki, Y. Yamauchi, and M. Nakata, (2014) Development of Obstacle Avoidance Control for Robotic Products Using Potential Method, Mitsubishi Heavy Industries Technical Review, Vol. 51 No. 1, pp. 34-39.
• [4] H. Woo, Y. Ji, H. Kono, Y. Tamura, Y. Kuroda, T. Sugano, Y. Yamamoto, A. Yamashita, and H. Asama, (2016) Automatic detection method of lane-changing intentions based on relationship with adjacent vehicles using artificial potential fields, International Journal of Automotive Engineering, Vol. 7, pp. 127-134
• [5] S. Hoshino, and K. Maki, (2015) Safe and eficient motion planning of multiple mobile robots based on artificial potential for human behavior and robot congestion, Advanced Robotics, Vol. 29, No. 17, pp. 1095-1109.
• [6] K.V. Mardia, and P.J. Zemroch, (1975) Algorithm AS 86: The Von Mises Distribution Function, Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 24, No. 2, pp. 268-272.
• [7] P.E. Hart, N.J. Nilsson, and B. Raphael, (1968) A formal basis for theheuristic determination of minimum cost paths, IEEE Transactions on SystemsScience and Cybernetics, Vol. 4, No. 2, pp. 100-107.
• [8] V. Naumov, R. Baumann, and T. Gross, (2006) An evaluation of inter-vehicle ad hoc networks based on realistic vehicular traces, Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing, pp. 108-119.
• [9] A. Nabeel, C. Sinem, and O. Oznur, (2015) Vehicle Mobility and Communication Channel Models for Realistic and Eficient Highway VANET Simulation, IEEE Transactions on Vehicular Technology (TVT), Vol. 64, pp. 248-262.