Fuzzy Logic Approaches for Pedestrian Collision Avoidance in Intelligent Vehicles


Authors : Parth Mody; Maanaav Motiramani; Param Sejpal

Volume/Issue : Volume 8 - 2023, Issue 2 - February

Google Scholar : https://bit.ly/3IIfn9N

Scribd : https://bit.ly/3YTKYxz

DOI : https://doi.org/10.5281/zenodo.7645261

Abstract : An automated braking decision or steering decision and control framework is proposed in this paper to avoid pedestrian collisions. Collision avoidance is an importantprerequisite for safe and automated driving in modern traffic systems. This paper explores intelligent and safe obstacle avoidance in complex traffic scenarios with main focus on pedestrian collision avoidance. The driver's purpose is important in collision avoidance, when the driver intends to avoid a collision by relying only on braking a safe stopping distance is 0.5 meters. But, when a driver intends to avoid collision by relying only on steering, for the most part, it is necessary to ensure that automated braking intervention will not occur.

Keywords : Obstacle Avoidance, Fuzzy Logic, Pedestrian Protection, Steering Control, Automated Braking, Kalman Filter, ANFIS, Complex Traffic Scenarios.

An automated braking decision or steering decision and control framework is proposed in this paper to avoid pedestrian collisions. Collision avoidance is an importantprerequisite for safe and automated driving in modern traffic systems. This paper explores intelligent and safe obstacle avoidance in complex traffic scenarios with main focus on pedestrian collision avoidance. The driver's purpose is important in collision avoidance, when the driver intends to avoid a collision by relying only on braking a safe stopping distance is 0.5 meters. But, when a driver intends to avoid collision by relying only on steering, for the most part, it is necessary to ensure that automated braking intervention will not occur.

Keywords : Obstacle Avoidance, Fuzzy Logic, Pedestrian Protection, Steering Control, Automated Braking, Kalman Filter, ANFIS, Complex Traffic Scenarios.

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