SUMO BASED HARDWARE/SOFTWARE CO-SIMULATION FOR TWO-INTERSECTION ADAPTIVE AND COLLABORATIVE TRAFFIC SIGNAL CONTROLLER
Congestion is a problem faced by all big cities in the world. One of the causes of congestion is the ineffective regulation of traffic lights at intersections, especially during rush hour. Traffic management at existing intersections is currently carried out using a fixed-time Traffic Signaling C...
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Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/73864 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | Congestion is a problem faced by all big cities in the world. One of the causes of
congestion is the ineffective regulation of traffic lights at intersections, especially
during rush hour. Traffic management at existing intersections is currently carried
out using a fixed-time Traffic Signaling Controller. This causes the Traffic
Signaling Controller not to be adaptive to fluctuations in traffic flow at
intersections. In addition, the existing coordination between controllers is only
limited to time offsets.
In this final project, an adaptive and collaborative Traffic Signaling Controller for
two adjacent intersections is developed using Reinforcement Learning. The
development of this adaptive and collaborative Traffic Signaling Controller needs
to be carried out by taking into account various aspects, one of the main ones is
safety. By paying attention to safety aspects, the development of adaptive and
collaborative Traffic Signaling Controller cannot be implemented directly in the
field. Therefore, a system that can simulate actual environmental conditions as a
training platform for the controllers that is being developed and to ensure that the
controllers work properly before being implemented directly in the field is needed.
This final project book specifically discusses the design, implementation, and
testing of the traffic environment simulator. This simulator is used as an
environment that trains and tests Reinforcement Learning algorithms previously
implemented in the field. The simulation is carried out using Simulator for Urban
Mobility (SUMO) and taking into account the regulations that apply in Indonesia.
In addition, interconnection between subsystems is also designed, especially with
miniatures that is controlled by Arduino Mega. In general, the design,
implementation and testing of this traffic environment simulator went well. The
simulator and miniature subsystems are connected to each other. However, it is
necessary to improve the connectivity between systems, namely reducing the delay
between the simulator and the miniature. |
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