Analysis of Automated Emergency Braking System to Investigate Forward Collision Condition Using Scenario-Based Virtual Assessment

Abstract

In the recent trend of automotive technologies, active safety systems for vehicles have become one ofthe key elements to reduce road traffic conditions. Automated vehicles are known as one of the active safetysystems to minimize road traffic congestion and unwanted road hazardous situations. Generally, automatedvehicles are designed using advanced driving assistance system (ADAS) technology to enhance the safetycapability of the vehicles. Moreover, automated vehicles are designed to adopt multiple scenarios with differenttypes of traffic situations. Generally, the performance of automated vehicles is evaluated to adapt with various roadconditions and different type of traffic conditions, autonomously. Nonetheless, most of the safety testing wasconducted in a controlled environment and with less traffic conditions. Moreover, this technology is tested indeveloped countries and mostly evaluated for highway driving scenarios, with less pedestrians and motorist’s roadusers. On the other hand, in developing countries such as Malaysia, most of the automotive researchers haveinitiated research related to automated vehicle based on controlled environment only. One of the primary focusesfor the current automotive researchers is to reduce road accidents due to frontal collision. Thus, automatedemergency braking systems have been heavily investigated by most developers to minimize road accidents. Mostof the researchers analyze the system in terms of theoretical based simulation and tested using actual vehicle forphysical testing. However, this type of testing is not sufficient to optimize the performance of automatedemergency braking systems for developing countries. Therefore, this study focuses on scenario-based virtualassessment to evaluate the capability of autonomous vehicles using automated emergency braking system withoutcausing road casualties with the distance range is 4.5m to 0.5m depending on vehicle speed. &nbsp

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