0% Complete
صفحه اصلی
/
سی و سومین کنفرانس بین المللی مهندسی برق
Lane Change Decision Making Using Deep Reinforcement Learning
نویسندگان :
Pedram Lamei
1
Mohammad Haeri
2
1- Sharif university of technology
2- Sharif university of technology
کلمات کلیدی :
Deep reinforcement learning،Decision making،Lane change،Autonomous vehicles،Autonomous driving
چکیده :
This paper explores the application of deep reinforcement learning for decision-making in autonomous vehicle lane-changing scenarios. Lane changes, a critical aspect of driving, pose significant challenges for autonomous systems due to complex traffic dynamics and safety constraints. The study investigates two deep reinforcement learning algorithms, deep Q-network and proximal policy optimization to train agents for efficient and safe lane changes in a stochastic highway environment. By defining a structured state, action, and reward space, the proposed methods emphasize collision avoidance, adherence to traffic norms, and travel efficiency. Simulation results reveal distinct strengths of two approaches. Deep Q-network demonstrates aggressive efficiency with higher overtakes and rapid transitions, while proximal policy optimization prioritizes safety through conservative strategies, achieving consistent maximum distances. Comparative analysis highlights the trade-offs between these methods, offering insights for developing robust autonomous driving policies. This research contributes to advancing intelligent transportation systems by addressing decision-making challenges and promoting adaptive learning for enhanced vehicle autonomy.
لیست مقالات
لیست مقالات بایگانی شده
Improving Adaptive Algorithm to Reduce Grounding System Impedance Computing Time
Soheil Rahnamayian Jelodar - Seyed Hossein Hesamedin Sadeghi - Reza Rahmani - Mohammad Ali Narooie Dehchil - Hossein Askarian Abyaneh
مدل جامع مدیریت انرژی الکتریکی ریزشبکه مسکونی با استفاده از کنترل پیشبین مبتنی بر مدل
سینا رودنیل - سعید قاسمزاده - کاظم زارع - امیر امینزاده قوی فکر
A Modified Low Rank Learning Based on Iterative Nuclear Weighting in Ripplet Transform for Denoising MR Images
Nooshin Farhangian - Mansour Nejati Jahromi - Mahdi Nouri
کنترل تشنج در مدل صرع ساز با استفاده از کنترل کننده سطح دینامیکی
مهدی کمالی دولت آبادی - مرضیه کمالی - فرزانه شایق
High-Gain Quasi-Z-Source DC-DC Converter with Single Magnetic Core and Pole Placement Control for DC Microgrid Applications
Ali Nadermohammadi - Zahra Behboudi - Amirhossein Akhbari - Soheil Norouzi - Seyed Hossein Hosseini - Mehran Sabahi
Secret Sharing Implementation of Predictive Functional Control
Enayat Amiri - Mohammad Haeri - Saeed Adelipour
بهینه سازی تزویج فیبر نوری باریک شده و موجبر نوری بر بستر پلیمر
مهتاب حسینعلی زاده - مونا ثریا - غلام محمد پارسا نسب - شکراله کریمیان
A Novel Multi-Variable Search Space Method for Selective Harmonic Control-PWM in Active Power Filters
Mohammadhossein Mohammadpour - Faegheh Taghipour Reyneh - Hoda Ghoreishy - Seyyed Asghar Gholamian
بهبود دقت و سرعت روش حداکثر جریان در تشخیص خطاهای آغازین وقایع آبشاری
مجتبی فکری - جواد نیکوکار - گئورک قره پتیان
Techno-Economic Dispatch of Distributed Energy Resources for Optimal Grid-Connected Operation of a Microgrid
Selma Cheshmeh khavar - Arya Abdolahi
بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 43.6.0
