Study the Influence of Distance in Artificial Potential Field (APF) for Autonomous Emergency Braking System (AEB) on Longitudinal Motion

Abdullah, Zuhaira; Heerwan, P. M.; Izhar, I. M.; Zakaria, Muhammad Aizzat

doi:10.1088/1757-899x/1068/1/012015

Cited by 4 publications

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many drivers lost their lives due to the unsafe and limitations of ADAS. Therefore, the public and government pay more attention on the safety and reliability performance of ADAS [2] . The reliability and safety performance of the autonomous driving system (AVS) will be tested by real vehicle test and simulation test [3] , which need massive and effective scenarios to reveal the limitations and defects of the AVS.…”

Section: Introductionmentioning

confidence: 99%

Research on cut-in scenario identification algorithm based on risk assessment

Zeng,

Ding,

et al. 2024

Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023)

View full text Add to dashboard Cite

The boundaries of typical scenes need to be extracted from the original scene data occurring in real roads, but the manual scene labeling method is inefficient and costly. Therefore, it is important to study the acquisition of autonomous driving scenes in real roads for the testing of autonomous vehicles, and the cut-in scenes are typical hazard scenes. In this paper, a scenario acquisition system with multi-source heterogeneous sensors is modified based on a vehicle equipped with L2- level autonomous driving system for acquiring natural road driving scenario data. Subsequently, a cut-in scenario automatic recognition algorithm based on risk assessment is proposed, and a recognition algorithm evaluation test platform is constructed, and a large number of test case generation procedures are designed to simulate and test the algorithm. And a large amount of natural driving data is used to verify the proposed recognition algorithm. The results show that the algorithm proposed in this paper can effectively identify the cut-in scenes occurring in front of the collection vehicle and has high accuracy.

show abstract

Section: Introductionmentioning

confidence: 99%

Research on cut-in scenario identification algorithm based on risk assessment

Zeng,

Ding,

et al. 2024

Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023)

View full text Add to dashboard Cite

show abstract

Research on Obstacle Avoidance of Small Cruise Vehicle Based on Improved Artificial Potential Field Method

Liu

Dou

2021

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

To enhance the small cruise vehicle in the complex environment under the ice autonomous obstacle avoidance ability, the artificial potential field algorithm was improved in this paper. Firstly, the idea and principle of the traditional artificial potential field obstacle avoidance algorithm as well as its existing defects such as local minimum are analyzed. Then the local minimum defect of the traditional artificial potential field method is solved by optimizing the repulsive potential field function and adjusting the repulsive force component’s direction on the coordinate axis. Then, the improved artificial potential field obstacle avoidance algorithm is simulated by using MATLAB software. The experimental results show that the improved algorithm can make the cruiser safely and accurately sail to the target position without falling into the local minimum value, which proves that the improved artificial potential field obstacle avoidance algorithm can work safely and stably.

show abstract