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    A Deep Q-Learning Approach to Improve the Effects of Novice Drivers’ Driving Behavior at a Signalized Intersection

    Source: Journal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 003::page 04026001-1
    Author:
    Rizelioğlu, Mehmet
    DOI: 10.1061/JCCEE5.CPENG-6780
    Publisher: American Society of Civil Engineers
    Abstract: AbstractThis study presents a deep Q-learning optimization framework to improve the effects of novice drivers’ behavior on signalized intersection performance. The driving behavior of 70 novice drivers was collected at a signalized intersection using ...
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      A Deep Q-Learning Approach to Improve the Effects of Novice Drivers’ Driving Behavior at a Signalized Intersection

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4314430
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    contributor authorRizelioğlu, Mehmet
    date accessioned2026-08-20T21:25:29Z
    date available2026-08-20T21:25:29Z
    date copyright2026/01/19
    date issued2026
    identifier otherJCCEE5.CPENG-6780.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314430
    description abstractAbstractThis study presents a deep Q-learning optimization framework to improve the effects of novice drivers’ behavior on signalized intersection performance. The driving behavior of 70 novice drivers was collected at a signalized intersection using ...
    publisherAmerican Society of Civil Engineers
    titleA Deep Q-Learning Approach to Improve the Effects of Novice Drivers’ Driving Behavior at a Signalized Intersection
    typeJournal Article
    journal volume40
    journal issue3
    journal titleJournal of Computing in Civil Engineering
    identifier doi10.1061/JCCEE5.CPENG-6780
    journal fristpage04026001-1
    journal lastpage04026001-16
    page16
    treeJournal of Computing in Civil Engineering:;2026:;Volume ( 040 ):;issue: 003
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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