Research on Longitudinal Active Collision Avoidance of Autonomous Emergency Braking Pedestrian System (AEB-P)

Abstract

The AEB-P (Autonomous Emergency Braking Pedestrian) system has the functional requirements of avoiding the pedestrian collision and ensuring the pedestrian’s life safety. By studying relevant theoretical systems, such as TTC (time to collision) and braking safety distance, an AEB-P warning model was established, and the traffic safety level and work area of the AEB-P warning system were defined. The upper-layer fuzzy neural network controller of the AEB-P system was designed, and the BP (backpropagation) neural network was trained by collected pedestrian longitudinal anti-collision braking operation data of experienced drivers. Also, the fuzzy neural network model was optimized by introducing the genetic algorithm. The lower-layer controller of the AEB-P system was designed based on the PID (proportional integral derivative controller) theory, which realizes the conversion of the expected speed reduction to the pressure of a vehicle braking pipeline. The relevant pedestrian test scenarios were set up based on the C-NCAP (China-new car assessment program) test standards. The CarSim and Simulink co-simulation model of the AEB-P system was established, and a multi-condition simulation analysis was performed. The results showed that the proposed control strategy was credible and reliable and could flexibly allocate early warning and braking time according to the change in actual working conditions, to reduce the occurrence of pedestrian collision accidents.

Gain-Scheduled Model Predictive Control for a Commercial Vehicle Air Brake System

“…The form of the brake system transfer function did not vary with the different reference pressures. Therefore, the discretetime transfer function of the linearized pneumatic brake system could be generated as Equation (3). The coefficients θ 1 , θ 2 , θ 3 , and θ 4 in Equation (3) varied with the different target pressures.…”

“…For braking, an excellent response time, a shorter delay time, and a faster response time are always preferred [3]. The research on the theoretical knowledge of pneumatic and hydraulic brake systems is now very mature [3,4], but many theoretical studies only considered the static characteristics of the pneumatic system, such as the braking force distribution of the front and rear axles and the related braking performance. From the practical point of view, the instantaneous braking response needs to be considered.…”

Prioritizing Safety or Traffic Flow? Qualitative Study on Highly Automated Vehicles’ Potential to Prevent Pedestrian Crashes with Two Different Ambitions

“…Consequently, time-to-collision (TTC) analysis is applied to evaluate whether there is enough time to decelerate and avoid the collision by the HAV, when the pedestrian steps to a roadway in pedestrian crossing crashes and crashes outside pedestrian crossings. TTC is calculated as presented in Equation (1) and rounded to the nearest 0.5 s. The crash is analyzed as unlikely preventable, if TTC is smaller than 1.5 s, because it represents a high collision risk and TTC = 1.5 s is when the system should apply the brakes at the latest [24,25]. If TTC is less than 1.5 s, there is likely too little time to avoid a collision.…”

Feasibility of Using a MEMS Microphone Array for Pedestrian Detection in an Autonomous Emergency Braking System

“…All these systems are of particular interest in autonomous vehicles. Among these systems, there are AEB systems specifically focused on pedestrian detection, the so-called AEB-P (AEB for Pedestrians), whose studies are heavily focused on trying to reduce the number of accidents involving pedestrians, either by using monocular cameras [ 11 ], analyzing time-to-collision (TTC) [ 12 , 13 ], mapping the positions of detected pedestrians [ 14 ], including vacuum emergency braking (VEB) [ 15 ], or developing protocols for testing emergency braking systems [ 16 , 17 ].…”