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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: July 2026
Volume 11 | Issue 7
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 122
Article Submitted : 25330
Article Published : 9497
Total Authors : 25208
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| Paper Title: | A Hybrid Deep Reinforcement Learning and Safety-Barrier Framework for Autonomous Vehicle Lane-Changing Decisions |
| Authors Name: | Miss.Vidya Hindurao Patil , Dr. Seema Suhas Patil |
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IJRTI_213481
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| Published Paper Id: | IJRTI2606089 |
| Published In: | Volume 11 Issue 6, June-2026 |
| DOI: | |
| Abstract: | For intelligent driving systems, negotiating highly interactive lateral cut-ins on busy expressway lanes is a challenging task. While model-free reinforcement layouts are constrained by risky exploration behaviors and sparse reward patterns during early model optimization stages, traditional rule-structured state machines suffer from stochastic ambient vehicular habits. This paper proposes a unified decision and deterministic filtering system to address these issues. We design a cooperative arrangement that combines an algebraic Control Barrier Function layer with a Twin Delayed Deep Deterministic Policy Gradient network. While the secondary quadratic validation step instantly overrides dangerous execution paths, the underlying neural architecture continuously monitors and modifies path policies to maintain passenger comfort and trip efficiency metrics. Our integrated methodology achieves a 98.5% navigational execution rate, inhibits rapid variations in vehicular jerk profiles, and totally eliminates physical contact instances against erratic nearby cars, according to extensive computerized assessments over various operational densities. |
| Keywords: | Trajectory planning, deep reinforcement learning, autonomous cars, lane changes, and control barrier functions. |
| Cite Article: | "A Hybrid Deep Reinforcement Learning and Safety-Barrier Framework for Autonomous Vehicle Lane-Changing Decisions", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 6, page no.a870-a871, June-2026, Available :http://www.ijrti.org/papers/IJRTI2606089.pdf |
| Downloads: | 00081 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2606089
Registration ID:213481
Published In: Volume 11 Issue 6, June-2026
DOI (Digital Object Identifier):
Page No: a870-a871 Country: Shirala, Maharashtra, India Research Area: Electronics & Communication Engg. Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2606089 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2606089 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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