Standard Grant: Ethical Algorithms in Autonomous Vehicles

标准拨款：自动驾驶汽车中的道德算法

• 批准号: 1734521
• 负责人: Nicholas Evans
• 金额: $ 55.67万
• 依托单位: University of Massachusetts Lowell
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1734521&HistoricalAwards=false
• 关键词: Standard; Grant; Ethical; Algorithms; Autonomous

This project supports a team of researchers, including experts in moral philosophy and transportation engineering, who plan to address ethical issues that arise in the development of computer algorithms for autonomous (self-driving) vehicles. The project will address concerns over the expression of ethical values in self-driving vehicle when (for example) the vehicle detects an imminent and unavoidable crash and must select among navigation options, such as colliding with a crowded bus or with a lone motorcyclist. It aims to develop algorithmic representations of ethical decision-making frameworks for autonomous vehicles, and then model these frameworks over a range of contexts for their effect on risk management in traffic networks and for their expected public health impact. The overarching aim of the project is to promote principled approaches to ethical decision-making in complex, autonomous systems, and to prepare designers and engineers to encode ethical behavior into such systems. Research mentoring is to be coordinated through the host institution that will enable undergraduate and graduate engineers to participate in the project. A summer intensive will bring together students from diverse backgrounds to work with the project team and invited scholars. A postdoctoral fellow will conduct research on the ethics of autonomous vehicles, and assist in project administration.The project has two specific aims. It aims to develop ethical algorithms that can be converted into computer code for use in autonomous vehicles. Team members will review the literature on existing decision-making for autonomous vehicles, and then develop conceptual, algorithmic representations of ethical behavior that can be converted into computer code. They will also model changes in traffic risk profiles and expected public health impact of these algorithms; specifically, they will apply injury severity and crash frequency modeling using algorithms developed in meeting the first aim in a range of traffic contexts and market penetration scenarios. They will also develop a model for the expected public health benefits from these algorithms using model of resource and time-based triaging as a starting point. Both aims support training of scholars and practitioners sensitive to the ethical implications of autonomous vehicles. These pedagogical aspects have been designed to promote diverse interactions between STEM students and practitioners, and they will serve to improve STEM education and educator development.

该项目支持一组研究人员，包括道德哲学和运输工程专家，他们计划解决在开发用于自动驾驶（自动驾驶）车辆的计算机算法时出现的道德问题。当车辆检测到迫在眉睫且不可避免的崩溃时，该项目将解决对自动驾驶车辆中道德价值的担忧，并且必须在导航选项中进行选择，例如与拥挤的公共汽车或孤独的摩托车手相撞。它的目的是为自动驾驶汽车开发道德决策框架的算法表示，然后在一系列环境中对这些框架进行建模，从而对交通网络中的风险管理产生影响以及预期的公共卫生影响。该项目的总体目的是促进复杂，自主系统中道德决策的原则方法，并准备设计师和工程师将道德行为编码为这样的系统。研究指导将通过主机机构进行协调，这将使本科和研究生工程师能够参加该项目。夏季密集型将使来自不同背景的学生与项目团队合作，并邀请学者。博士后研究员将对自动驾驶汽车的道德规范进行研究，并协助项目管理。该项目具有两个具体的目标。它旨在开发可以将其转换为用于自动驾驶汽车的计算机代码的道德算法。团队成员将审查有关自动驾驶汽车现有决策的文献，然后开发可转换为计算机代码的道德行为的概念性算法表示。他们还将建模这些算法的交通风险概况的变化和预期的公共卫生影响；具体而言，他们将使用在各种交通环境和市场渗透方案中达到第一个目标时开发的算法进行伤害严重性和崩溃频率建模。他们还将使用资源模型和基于时间的三角列表作为起点，从而为这些算法从这些算法带来预期的公共卫生益处。两者都支持对学者和从业者对自动驾驶汽车的道德影响敏感的培训。这些教学方面旨在促进STEM学生和从业者之间的各种互动，它们将有助于改善STEM教育和教育工作者的发展。

项目成果

Reinforcement Learning based cooperative longitudinal control for reducing traffic oscillations and improving platoon stability

• DOI: 10.1016/j.trc.2022.103744
• 发表时间: 2022-06-09
• 期刊: TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
• 影响因子: 8.3
• 作者: Jiang, Liming;Xie, Yuanchang;Chen, Danjue
• 通讯作者: Chen, Danjue

Long covid and disability: a brave new world

• DOI: 10.1136/bmj-2021-069868
• 发表时间: 2022-08-01
• 期刊: BMJ-BRITISH MEDICAL JOURNAL
• 影响因子: 105.7
• 作者: Hereth, Blake;Tubig, Paul;Evans, Nicholas G.
• 通讯作者: Evans, Nicholas G.

Cooperative Highway Work Zone Merge Control Based on Reinforcement Learning in a Connected and Automated Environment

• DOI: 10.1177/0361198120935873
• 发表时间: 2020-07-17
• 期刊: TRANSPORTATION RESEARCH RECORD
• 影响因子: 1.7
• 作者: Ren, Tianzhu;Xie, Yuanchang;Jiang, Liming
• 通讯作者: Jiang, Liming

Cooperative Car-Following and Merging: A Novel Merge Control Strategy Considering Cooperative Adaptive Cruise Control and Courtesy

协作跟车与并道：一种考虑协作自适应巡航控制和礼让的新型并道控制策略

• 发表时间: 2021
• 期刊: Proceedings of the 100th Transportation Research Board Annual Meeting
• 作者: Jiang, L.

New England merge: a novel cooperative merge control method for improving highway work zone mobility and safety

• DOI: 10.1080/15472450.2020.1822747
• 发表时间: 2020-09-22
• 期刊: JOURNAL OF INTELLIGENT TRANSPORTATION SYSTEMS
• 影响因子: 3.6
• 作者: Ren, Tianzhu;Xie, Yuanchang;Jiang, Liming
• 通讯作者: Jiang, Liming