Development of Test Equipment for Pedestrian-Automatic Emergency Braking Based on C-NCAP (2018)

Song, Zhiqiang; Cao, Libo; Chou, Clifford C.

doi:10.3390/s20216206

Cited by 8 publications

(3 citation statements)

References 22 publications

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“…Another field of application is presented in [24]. Here, the combination of a pedal and steering robot is used for testing emergency braking assistants for pedestrians to provide a realistic simulation of critical scenarios.…”

Section: Driving Robots: Pedal and Steering Robotsmentioning

confidence: 99%

Driving Robot for Reproducible Testing: A Novel Combination of Pedal and Steering Robot on a Steerable Vehicle Test Bench

et al. 2022

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Shorter development times, increased standards for vehicle emissions and a greater number of vehicle variants result in a higher level of complexity in the vehicle development process. Efficient development of powertrain and driver assistance functions under comparable and reproducible operating conditions is possible on vehicle test benches. Yet, the realistic simulation of real driving environments on test benches is a challenge. Current test procedures and new technologies, such as Real Driving Emission tests and Autonomous Driving, require a reproducible and even more detailed simulation of the driving environment. Due to this, the simulation of curve driving in particular is gaining in importance. This results from its significant influence on energy consumption and Autonomous Driving functions with lateral guidance, such as lane departure and evasion assistance. Reproducibility can be additionally increased by using a driving robot. At today’s vehicle test benches, pedal and shift robots are predominantly used for longitudinal dynamic tests in the performed test procedures. In order to meet these new test automation requirements for vehicle test benches, the cooperative operation of pedal and steering robots is needed on a test bench setup suitable for this purpose. In this publication, the authors present the setup of a vehicle test bench to be used in automated and reproducible vehicle-in-the-loop tests during steering events. The focus is on the test-bench-specific setup with steerable front wheels, the actuators for simulating the wheel steering torque around the steering axle and the robots used for pedals and steering wheel. Results from various test series are presented and the potential of the novel test environment is shown. The results are reproducible in various test series due to the closed-loop operation without human driving influences at the test bench.

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Section: Driving Robots: Pedal and Steering Robotsmentioning

confidence: 99%

Driving Robot for Reproducible Testing: A Novel Combination of Pedal and Steering Robot on a Steerable Vehicle Test Bench

et al. 2022

View full text Add to dashboard Cite

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“…Cicchino [9] suggested that an AEB system with pedestrian detection could reduce crash risks by 25-27%. Song et al [10] and Zhou et al [11] optimized the AEB for different crashes to further improve driver and occupant protection.…”

Section: Introductionmentioning

confidence: 99%

Driver Injury from Vehicle Side Impacts When Automatic Emergency Braking and Active Seat Belts Are Used

Dao-wen

Liu

2023

Sensors

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As an advanced driver assistance system, automatic emergency braking (AEB) can effectively reduce accidents by using high-precision and high-coverage sensors. In particular, it has a significant advantage in reducing front-end collisions and rear-end accidents. Unfortunately, avoiding side collisions is a challenging problem for AEB. To tackle these challenges, we propose active seat belt pretensioning on driver injury in vehicles equipped with AEB in unavoidable side crashes. Firstly, records of impact cases from China’s National Automobile Accident In-Depth Investigation System were used to investigate a scenario in which a vehicle is impacted by an oncoming car after the vehicle’s AEB system is triggered. The scenario was created using PreScan software. Then, the simulated vehicles in the side impact were devised using a finite element model of the Toyota Yaris and a moving barrier. These were constructed in HyperMesh software along with models of the driver’s side seatbelt, side airbag, and side curtain airbag. Moreover, the models were verified, and driver out-of-position instances and injuries were evaluated in simulations with different AEB intensities up to 0.7 g for three typical side impact angles. Last but not least, the optimal combination of seatbelt pretensioning and the timing thereof for minimizing driver injury at each side impact angle was identified using orthogonal tests; immediate (at 0 ms) pretensioning at 80 N was applied. Our experiments show that our active seatbelt with the above parameters reduced the weighted injury criterion by 5.94%, 22.05%, and 20.37% at impact angles of 90°, 105°, and 120°, respectively, compared to that of a conventional seatbelt. The results of the experiment can be used as a reference to appropriately set the collision parameters of active seat belts for vehicles with AEB.

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“…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 ].…”

Section: Introductionmentioning

confidence: 99%

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

Izquierdo

Val

Villacorta

2021

Sensors

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Pedestrian detection by a car is typically performed using camera, LIDAR, or RADAR-based systems. The first two systems, based on the propagation of light, do not work in foggy or poor visibility environments, and the latter are expensive and the probability associated with their ability to detect people is low. It is necessary to develop systems that are not based on light propagation, with reduced cost and with a high detection probability for pedestrians. This work presents a new sensor that satisfies these three requirements. An active sound system, with a sensor based on a 2D array of MEMS microphones, working in the 14 kHz to 21 kHz band, has been developed. The architecture of the system is based on an FPGA and a multicore processor that allow the system to operate in real time. The algorithms developed are based on a beamformer, range and lane filters, and a CFAR (Constant False Alarm Rate) detector. In this work, tests have been carried out with different people and in different ranges, calculating, in each case and globally, the Detection Probability and the False Alarm Probability of the system. The results obtained verify that the developed system allows the detection and estimation of the position of pedestrians, ensuring that a vehicle travelling at up to 50 km/h can stop and avoid a collision.

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Development of Test Equipment for Pedestrian-Automatic Emergency Braking Based on C-NCAP (2018)

Cited by 8 publications

References 22 publications

Driving Robot for Reproducible Testing: A Novel Combination of Pedal and Steering Robot on a Steerable Vehicle Test Bench

Driving Robot for Reproducible Testing: A Novel Combination of Pedal and Steering Robot on a Steerable Vehicle Test Bench

Driver Injury from Vehicle Side Impacts When Automatic Emergency Braking and Active Seat Belts Are Used

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

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