IMPLEMENTATION OF A VIDEO ANALYTICS-BASED VEHICLE TRACKING SYSTEM FOR COUNTING VEHICLES BASED ON MOVEMENT DIRECTION AT A FOUR-WAY INTERSECTION

Congestion is an important issue that has various adverse impacts on society and needs attention. Better traffic management efforts can be undertaken to reduce congestion by paying closer attention to the traffic conditions of a traffic space relative to neighboring traffic, especially at interse...

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Bibliographic Details
Main Author: Seipanya, Ayub
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/85274
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:85274
spelling id-itb.:852742024-08-20T09:29:59ZIMPLEMENTATION OF A VIDEO ANALYTICS-BASED VEHICLE TRACKING SYSTEM FOR COUNTING VEHICLES BASED ON MOVEMENT DIRECTION AT A FOUR-WAY INTERSECTION Seipanya, Ayub Indonesia Final Project vehicle, detection, tracking, counting INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/85274 Congestion is an important issue that has various adverse impacts on society and needs attention. Better traffic management efforts can be undertaken to reduce congestion by paying closer attention to the traffic conditions of a traffic space relative to neighboring traffic, especially at intersections. Observations of these conditions can begin by identifying traffic parameters, particularly traffic volume, and it is necessary to know the number of vehicles passing through a traffic space to obtain the traffic volume value. Counting the number of vehicles in traffic is usually done manually, but with the advancement of artificial intelligence technology, vehicle counting can be carried out using object detection technology. Moreover, object detection technology combined with object tracking technology can make vehicle counting easier and more accurate. This study discusses the development of a vehicle tracking system to count vehicles at intersections by applying the V-Model waterfall methodology, which consists of communication, planning, modeling, construction, and evaluation. The system implementation is carried out according to the requirements and designs that have been established, with the implementation stages consisting of dataset management, model training, and vehicle tracking development. The test results of this system show good detection, classification, tracking, and vehicle counting capabilities, marked by high evaluation metric values, both for the system using ByteTrack and the system using DeepSORT. However, the system using ByteTrack has higher evaluation metric values compared to the system using DeepSORT. Nevertheless, the system does not work optimally when dealing with data contexts containing occlusions, such as between vehicles and light poles. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description Congestion is an important issue that has various adverse impacts on society and needs attention. Better traffic management efforts can be undertaken to reduce congestion by paying closer attention to the traffic conditions of a traffic space relative to neighboring traffic, especially at intersections. Observations of these conditions can begin by identifying traffic parameters, particularly traffic volume, and it is necessary to know the number of vehicles passing through a traffic space to obtain the traffic volume value. Counting the number of vehicles in traffic is usually done manually, but with the advancement of artificial intelligence technology, vehicle counting can be carried out using object detection technology. Moreover, object detection technology combined with object tracking technology can make vehicle counting easier and more accurate. This study discusses the development of a vehicle tracking system to count vehicles at intersections by applying the V-Model waterfall methodology, which consists of communication, planning, modeling, construction, and evaluation. The system implementation is carried out according to the requirements and designs that have been established, with the implementation stages consisting of dataset management, model training, and vehicle tracking development. The test results of this system show good detection, classification, tracking, and vehicle counting capabilities, marked by high evaluation metric values, both for the system using ByteTrack and the system using DeepSORT. However, the system using ByteTrack has higher evaluation metric values compared to the system using DeepSORT. Nevertheless, the system does not work optimally when dealing with data contexts containing occlusions, such as between vehicles and light poles.
format Final Project
author Seipanya, Ayub
spellingShingle Seipanya, Ayub
IMPLEMENTATION OF A VIDEO ANALYTICS-BASED VEHICLE TRACKING SYSTEM FOR COUNTING VEHICLES BASED ON MOVEMENT DIRECTION AT A FOUR-WAY INTERSECTION
author_facet Seipanya, Ayub
author_sort Seipanya, Ayub
title IMPLEMENTATION OF A VIDEO ANALYTICS-BASED VEHICLE TRACKING SYSTEM FOR COUNTING VEHICLES BASED ON MOVEMENT DIRECTION AT A FOUR-WAY INTERSECTION
title_short IMPLEMENTATION OF A VIDEO ANALYTICS-BASED VEHICLE TRACKING SYSTEM FOR COUNTING VEHICLES BASED ON MOVEMENT DIRECTION AT A FOUR-WAY INTERSECTION
title_full IMPLEMENTATION OF A VIDEO ANALYTICS-BASED VEHICLE TRACKING SYSTEM FOR COUNTING VEHICLES BASED ON MOVEMENT DIRECTION AT A FOUR-WAY INTERSECTION
title_fullStr IMPLEMENTATION OF A VIDEO ANALYTICS-BASED VEHICLE TRACKING SYSTEM FOR COUNTING VEHICLES BASED ON MOVEMENT DIRECTION AT A FOUR-WAY INTERSECTION
title_full_unstemmed IMPLEMENTATION OF A VIDEO ANALYTICS-BASED VEHICLE TRACKING SYSTEM FOR COUNTING VEHICLES BASED ON MOVEMENT DIRECTION AT A FOUR-WAY INTERSECTION
title_sort implementation of a video analytics-based vehicle tracking system for counting vehicles based on movement direction at a four-way intersection
url https://digilib.itb.ac.id/gdl/view/85274
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