Advanced Certificate in Safety Prediction Techniques
-- ViewingNowThe Advanced Certificate in Safety Prediction Techniques is a comprehensive course designed to equip learners with cutting-edge safety prediction techniques crucial for career advancement in various industries. This certificate program focuses on the importance of predicting and mitigating potential safety risks, reducing accidents, and enhancing overall safety performance.
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โข Safety Prediction Models: An overview of various safety prediction models and techniques, including Accident Prediction Program (APP), Safety Performance Function (SPF), and Surrogate Safety Measures (SSM). This unit will cover the basics of each model, their strengths, and limitations, and when to use them.
โข Data Collection and Analysis: This unit will cover the best practices for collecting and analyzing data for safety prediction techniques. Topics will include data sources, data quality, and data analysis methods using statistical software.
โข Highway Safety Improvement Program (HSIP): This unit will cover the HSIP process, including data-driven approaches to highway safety, prioritizing hazardous locations, and selecting effective countermeasures.
โข Crash Modification Factors (CMFs): This unit will cover the concept and application of CMFs, including the latest research and databases. The unit will also cover how to use CMFs in safety prediction and decision-making.
โข Safety Prediction Tools and Software: This unit will cover the latest safety prediction tools and software, including SPF, HSM, and other commercial products. The unit will cover the features, benefits, and limitations of each tool and when to use them.
โข Safety Performance Functions (SPFs) Development: This unit will cover the development of SPFs, including selecting the appropriate data, model selection, and calibration. The unit will also cover the latest research and trends in SPF development.
โข Human Factors in Safety Prediction: This unit will cover the role of human factors in safety prediction, including driver behavior, road user characteristics, and safety culture. The unit will cover how to incorporate human factors into safety prediction techniques and decision-making.
โข Safety Prediction in Work Zones: This unit will cover the unique challenges and solutions for safety prediction in work zones. The unit will cover the latest research and best practices for predicting and mitigating work zone crashes.
โข Safety Prediction in Intelligent Transportation Systems (ITS): This unit will cover the role of ITS in safety prediction, including connected and automated vehicles, traffic management systems, and traveler
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