JOURNAL ARTICLE

Ethical Decision-making for Autonomous Driving based on LSTM Trajectory Prediction Network

Wen WeiJiankun Wang

Year: 2023 Journal:   Procedia Computer Science Vol: 226 Pages: 134-140   Publisher: Elsevier BV

Abstract

The development of autonomous vehicles has brought a great impact and changes to the transportation industry, offering numerous benefits in terms of safety and efficiency. How ever, one of the key challenges that autonomous driving faces is how to make ethical decisions in complex situations. To address this issue, in this article, a novel trajectory prediction method is proposed to achieve ethical decision-making for autonomous driving. Ethical considerations are integrated into the decision-making process of autonomous vehicles by quantifying the utility principle and incorporating them into mathematical formulas. Furthermore, trajectory prediction is optimized using LSTM network with an attention module, resulting in improved accuracy and reliability in trajectory planning and selection. Through extensive simulation experiments, we demonstrate the effectiveness of the proposed method in making ethical decisions and selecting optimal trajectories.

Keywords:
Computer science Trajectory Reliability (semiconductor) Key (lock) Process (computing) Selection (genetic algorithm) Artificial intelligence Ethical decision Operations research Machine learning Computer security Law

Metrics

5
Cited By
2.03
FWCI (Field Weighted Citation Impact)
18
Refs
0.85
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Ethics and Social Impacts of AI
Social Sciences →  Social Sciences →  Safety Research
Autonomous Vehicle Technology and Safety
Physical Sciences →  Engineering →  Automotive Engineering
Adversarial Robustness in Machine Learning
Physical Sciences →  Computer Science →  Artificial Intelligence

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