Driversim: driver learning for car skilss using virtual simulator with recommendation system / Alajor, Matthew Kyle M.; David, Mary Anne Monique F.; Fernando, Christian Angelo G. and Mina, Bianca Philline A. 6

By: Alajor, Matthew Kyle M.; David, Mary Anne Monique F.; Fernando, Christian Angelo G. and Mina, Bianca Philline A. 4 0 16, [, ] | [, ] |
Contributor(s): 5 6 [] |
Language: Unknown language code Summary language: Unknown language code Original language: Unknown language code Series: ; Janaury 202446Edition: Description: x, 295 ppContent type: text Media type: unmediated Carrier type: volumeISBN: ISSN: 2Other title: 6 []Uniform titles: | | Related works: 1 40 6 []Subject(s): -- 2 -- 0 -- -- | -- 2 -- 0 -- 6 -- | 2 0 -- | -- -- 20 -- | | -- -- -- -- 20 -- | -- -- -- 20 -- --Genre/Form: -- 2 -- Additional physical formats: DDC classification: | LOC classification: | | 2Other classification:
Contents:
Action note: In: Summary: ABSTRACT: Simulators have long been utilized to maximize cost-effectiveness and safety while providing vital experience and training for inviduals. The majority of driving simulators available for use usually do not meet the necessary driver learning standards, despite being a well-known training instrument. Congruent with this, the proponents developed a driving and repair simulator comprising three sections: Driving Fundamentals, Repair Simulation, and On-Road Scenarios. The system was designed with the Unity game engine and was integrated with realistic Arduino controls. Moreover, through collecting 83 evaluation responses from driving schools and consulting 10 IT experts knowledgeable about the developed system was evaluated using asurvey questionnaire based on ISO Standard 25010, following the criteria and subcriteria under it - Functional Suitability, Performance Efficiency, Compatibility, Usability, Reliability, Security, Maintainability, and Portability. As a result, the system obtained an overall Very Good remark from IT professionals, with a mean score of 4.02. On the other hand, the system received an overall mean score of 4.09 from driving school respondents, which is equivalent to a rating of Very Good. A confusion matrix was employed to evaluate both the rule-based scoring algorithm and the Dijkstra algorithm within the system. The majority of cases were accurately classified by the rule-based scoring method, which showed an accuracy rate of 80% and an F1-score of 85.37% indicating a reasonably high degree of precision. Comparably, the Dijkstra method demonstrated a strong 95% accuracy rate and a remarkable F1-score of 97.44%, hihjlighting its resilience and efficiency in pathfinding assignments. Other editions:
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Undergraduate Thesis: (B.S in Information Technology) - Pamantasan ng Lungsod ng Maynila, 2024. 56

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ABSTRACT: Simulators have long been utilized to maximize cost-effectiveness and safety while providing vital experience and training for inviduals. The majority of driving simulators available for use usually do not meet the necessary driver learning standards, despite being a well-known training instrument. Congruent with this, the proponents developed a driving and repair simulator comprising three sections: Driving Fundamentals, Repair Simulation, and On-Road Scenarios. The system was designed with the Unity game engine and was integrated with realistic Arduino controls. Moreover, through collecting 83 evaluation responses from driving schools and consulting 10 IT experts knowledgeable about the developed system was evaluated using asurvey questionnaire based on ISO Standard 25010, following the criteria and subcriteria under it - Functional Suitability, Performance Efficiency, Compatibility, Usability, Reliability, Security, Maintainability, and Portability. As a result, the system obtained an overall Very Good remark from IT professionals, with a mean score of 4.02. On the other hand, the system received an overall mean score of 4.09 from driving school respondents, which is equivalent to a rating of Very Good. A confusion matrix was employed to evaluate both the rule-based scoring algorithm and the Dijkstra algorithm within the system. The majority of cases were accurately classified by the rule-based scoring method, which showed an accuracy rate of 80% and an F1-score of 85.37% indicating a reasonably high degree of precision. Comparably, the Dijkstra method demonstrated a strong 95% accuracy rate and a remarkable F1-score of 97.44%, hihjlighting its resilience and efficiency in pathfinding assignments.

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