A Novel Flexible Lane Changing (FLC) Method in Complicated ‎Dynamic Environment for Automated Vehicles

سال انتشار: 1402
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 226

فایل این مقاله در 14 صفحه با فرمت PDF قابل دریافت می باشد

استخراج به نرم افزارهای پژوهشی:

لینک ثابت به این مقاله:

شناسه ملی سند علمی:

JR_JACM-9-2_002

تاریخ نمایه سازی: 17 بهمن 1401

چکیده مقاله:

Decision making and path planning in case of highly transient dynamics of the surrounding as well as the effect of road condition are the issues that are not completely solved in the previous researches. The goal is to perform a safe and comfortable lane change that includes flexible re-planning capabilities. In this paper, a novel structure for path planning and decision making part of a vehicle automatic lane change has been introduced which comprehensively considers both longitudinal and lateral dynamics of the vehicle. The presented method is able to perform re-planning even in the middle of a lane change maneuver according to new traffic condition. Inclusion of the dynamics of all involved vehicles and providing online performance are the other advantages of the proposed system. The algorithm is simulated and various scenarios are constructed to evaluate the efficiency of the system. The results show that the system has completely acceptable performance.

نویسندگان

Mohsen Rafat

PhD. Candidate, Mechanical Engineering Department, K. N. Toosi University of Technology, ۱۹۹۹۱-۴۳۳۴۴ Tehran, Iran‎

Shahram Azadi

Associate Professor, Mechanical Engineering Department, K. N. Toosi University of Technology, ۱۹۹۹۱-۴۳۳۴۴ Tehran, Iran‎

مراجع و منابع این مقاله:

لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :
  • Pourmahmoudi, A., Ghaffari, A., Javadi, M., and Khodayari, A., A ...
  • Sazgar, H., Azadi, Sh., Kazemi, R., Trajectory planning and combined ...
  • Tang, J., Liu, F., Zhang, W., et al., Lane-changes prediction ...
  • Tanimoto, J., Fundamentals of Evolutionary Game Theory and its Applications, ...
  • Li, L., Gan, J., Ji, X., Qu, X., Ran, B., ...
  • Li, F., Li, G., LI, X., Research on Lane Change ...
  • Ruina, D., Jieyun, D., Bo, S., Qichang, Y., Yuanmu, T., ...
  • Toledo, T., Koutsopoulos, H.N., Ben-Akiva, M., Integrated driving behavior modeling, ...
  • Nobukawa, K., Bao, Sh., LeBlanc, D.J., Zhao, D., Peng, H., ...
  • Wang, M., Hoogendoorn, S.P., Daamen, W., Van Arem, B., Happee, ...
  • Kretzschmar, H., Kuderer, M., Burgard, W., Learning to predict trajectories ...
  • Bae, H., Kang, Y., Decision Making Methods Based on Nonlinear ...
  • Kuderer, M., Gulati, S., Burgard, W., Learning driving styles for ...
  • Wang, X., Wen, J., Nan, Z., Shi, J., Xu, L., ...
  • Li, L., Gan, J., Zhou, K., Qu, X., Ran, B., ...
  • Tanimoto, J., Evolutionary Games with Sociophysics: Analysis of Traffic Flow ...
  • Dixit, S., Fallah, S., Montanaro, U., et al., Trajectory planning ...
  • Kukida, Sh., Tanimoto, J., Hagishima, A., Analysis of the influence ...
  • Tanimoto, J., Fujiki, T., Wang, Zh., Hagishima, A., Ikegaya, N., ...
  • Tanimoto, J., Nakamura, K., Social dilemma structure hidden behind traffic ...
  • Nakata, M., Yamauchi, A., Tanimoto, J., Hagishima, A., Dilemma game ...
  • Iwamura, Y., Tanimoto, J., Complex traffic flow that allows lane-changing ...
  • Xu, G., Liu, L., Song, Z., Ou, Y., Generating lane ...
  • Celik, O., Ertugrul, S., Predictive human operator model to be ...
  • Jiang, Y., Yang, Ch., Wang, M., Wang, N., Liu, X., ...
  • Akai, N., Hirayama, T., Morales, L., Akagi, Y., Liu, H., ...
  • Li, A., Jiang, H., Zhou, J., Zhou, X., Implementation of ...
  • Song, R., Driver intention prediction using model-added Bayesian network, Proceedings ...
  • Wang, W., Xi, J., Hedrick, K., A Learning-Based Personalized Driver ...
  • Tharwat, A., Gabel, T., Parameters optimization of support vector machines ...
  • Wang, J., Wang, J., Wang, R., Hu, C., A Framework ...
  • Samiee, S., The design of driver drowsiness detection system based ...
  • Yoon, S., Kum, D., The Multilayer Perceptron Approach to Lateral ...
  • Liu, Y., Wang, X., Li, L., Cheng, Sh., Chen, Zh., ...
  • Cao, P., Xu, Zh., Fan, Q., Liu, X., Analysing driving ...
  • Zhao, M., Wang, Sh., Sun, D., Wang, X., A Car-Following ...
  • Liu, X., Liang, J., Xu, B., A Deep Learning Method ...
  • Samiee, S., Azadi, Sh., Kazemi, R., Eichberger, A., Rogic, B., ...
  • Samiee, S., Azadi, S., Kazemi, R., et al., Towards a ...
  • Jula, H., Kosmatopoulos, EB., Ioannou, PA., Collision Avoidance Analysis for ...
  • Hu, Z., Xiong, S., Su, Q., Zhang, X., Sufficient Conditions ...
  • Ali, I., Essam, D., Kasmarik, K., A novel design of ...
  • Kadzinski, M., Tomczyka, M.K., Słowinski, R., Preference-based cone contraction algorithms ...
  • Rasekhipour, Y., Khajepour, A., Chen, S., et al., A potential ...
  • Suh, J., Chae, H., Yi, K., Stochastic model predictive control ...
  • Cai, J., Jiang, H., Chen, L., et al., Implementation and ...
  • Olofsson, M., Pettersson, J., Parameterization and Validation of Road and ...
  • Cao, P., Modeling Active Perception Sensors for Real-Time Virtual Validation ...
  • نمایش کامل مراجع