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

In the recent trend of automotive technologies, active safety systems for vehicles have become one of the key elements to reduce road traffic conditions. Automated vehicles are known as one of the active safety systems to minimize road traffic congestion and unwanted road hazardous situations. Generally, automated vehicles are designed using advanced driving assistance system (ADAS) technology to enhance the safety capability of the vehicles. Moreover, automated vehicles are designed to adopt multiple scenarios with different types of traffic situations. Generally, the performance of automated vehicles is evaluated to adapt with various road conditions and different type of traffic conditions, autonomously. Nonetheless, most of the safety testing was conducted in a controlled environment and with less traffic conditions. Moreover, this technology is tested in developed countries and mostly evaluated for highway driving scenarios, with less pedestrians and motorist's road users. On the other hand, in developing countries such as Malaysia, most of the automotive researchers have initiated research related to automated vehicle based on controlled environment only. One of the primary focuses for the current automotive researchers is to reduce road accidents due to frontal collision. Thus, automated emergency braking systems have been heavily investigated by most developers to minimize road accidents. Most of the researchers analyze the system in terms of theoretical based simulation and tested using actual vehicle for physical testing. However, this type of testing is not sufficient to optimize the performance of automated emergency braking systems for developing countries. Therefore, this study focuses on scenario-based virtual assessment to evaluate the capability of autonomous vehicles using automated emergency braking system without causing road casualties with the distance range is 4.5m to 0.5m depending on vehicle speed.