Name	Name	Last commit message	Last commit date
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README.md	README.md
a.json	a.json
axv.json	axv.json
deep_policy_network.cpython-310.pyc	deep_policy_network.cpython-310.pyc
deep_policy_network.py	deep_policy_network.py
outputf.in	outputf.in
sd.json	sd.json
simple.edg.xml	simple.edg.xml
simple.net.xml	simple.net.xml
simple.nod.xml	simple.nod.xml
simple.sumocfg	simple.sumocfg
simple.type.xml	simple.type.xml
simple_routes.rou.xml	simple_routes.rou.xml
test.py	test.py
titanic_dataset.csv	titanic_dataset.csv
traffic.py	traffic.py
traffic2.py	traffic2.py
traffic3.py	traffic3.py
traffic4.py	traffic4.py
traffic5.py	traffic5.py
traffic6.py	traffic6.py
trafficControl.py	trafficControl.py
trafficControl2.py	trafficControl2.py
v.json	v.json

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MADRLTSC_EVP

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Traffic Management through Multi-Agent Deep Reinforcement Learning with Emergency Vehicle Prioritization optimizes urban traffic using agents to manage intersections and adjust signals dynamically. It prioritizes emergency vehicles and reduces waiting times. Simulated in SUMO and evaluated on a real-world map, fixed timeslot solutions.

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