Application of Reinforcement Learning as a Tool of Adaptive Traffic Signal Control on Isolated Intersections

Reinforcement Learning For Adaptive Traffic Signal Control

By 2050, two-thirds of the world’s 9.6 billion people will live in urban areas [2]. In many cities, opportunities to expand urban road networks are limited, so existing roads will need to more efficiently accommodate higher volumes of traffic. Consequently, there is a pressing need for technologically viable, low-cost solutions that can work with existing infrastructure to help alleviate increa...

Reinforcement learning in neurofuzzy traffic signal control

the effect of using learning logs as a self-assessment tool on the syntactic development among iranian pre-intermediate efl learners

چکیده: هدف از انجام این پژوهش ،بررسی استفاده از یادداشتهای یادگیری به عنوان یکی از ابزار های خود ارزشیابی بر افزایش مهارت دستوری (صورتهای شرطی و مجهول) زبان آموزان در مقطع پیش متوسطه بوده است .بدین منظور یک تست استاندارد در مقطع پیش متوسطه بین 90 نفر زبان آموز در سنین 15 تا 20 سال در آموزشگاه زبان انگلیسی امین و پارسا در شهرستان شاهرود برگزار شد از میان این افراد 60 فراگیر انتخاب شدند. و این 6...

Using a Deep Reinforcement Learning Agent for Traffic Signal Control

Ensuring transportation systems are efficient is a priority for modern society. Technological advances have made it possible for transportation systems to collect large volumes of varied data on an unprecedented scale. We propose a traffic signal control system which takes advantage of this new, high quality data, with minimal abstraction compared to other proposed systems. We apply modern deep...

the effect of explicit teaching of metacognitive vocabulary learning strategies on recall and retention of idioms

چکیده ندارد.