自主导航中不确定性下的风险感知决策博士研究员
Risk-aware decision-making under uncertainty for autonomous navigation
原帖优先：申请材料、截止时间与资格以原帖和学校官方说明为准。
博士招生与资助公告
- 申请年度
- 2027；原帖说明：How to apply Apply now You need to: • choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences • select Full time or Part time • search for programme PhD Engineering & the Environment (7175) • add name of the supervisor in section 2 of the application Applications should include: • your CV (resumé) • 2 academic references • degree transcripts and certificates to date • English language qualification (if applicable)
- 最近申请截止
- 2027-01-10
- 全部申请截止
- （Europe/London）
- 资助原文
- Fees and funding We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students. Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants. Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants. Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered. For more information, please visit our postgraduate research funding pages.
- 资助条件
- 原帖为竞争性或附条件资助说明，未确认本项目获资助及申请人能获奖；不作为保证全奖。
- 原帖材料说明
- • your CV (resumé)
- • 2 academic references
- • degree transcripts and certificates to date
- • English language qualification (if applicable)
确定性信息来自对应版本的完整原帖。原帖只提供日期，日末和学校当地时区为本站转换假设。筛选使用最后申请截止；资助与录取以学校审核结果为准。
AI 中文速览
- 研究内容
- 本项目将开发结合预测交通情况、航行风险、不确定性、国际海上避碰规则（COLREGs）及操作约束的风险感知决策方法，以支持自主船的安全导航决策，包括避碰、操作调整、监督和后备方案。研究将探讨如何将动态航行风险明确纳入自主决策过程，研究船舶相遇期间的决策，并考虑持续自主运行不再适用的情况。
- 申请条件
- 申请人需具备英国2:1荣誉学士学位或其国际同等学历。
- 待遇
- 提供竞争性资助，针对顶尖申请者通常涵盖英国级别的学费和生活费津贴；提供总统奖学金和Horizon Europe学费减免等机会。
- 申请方式
- 申请人需通过在线系统申请，选择研究型项目、2027/28学年、工程与物理科学学院，选择全职或兼职，搜索PhD Engineering & the Environment (7175)项目，并在申请表第二部分添加导师姓名。
- 材料清单
- 简历（CV）
- 2封学术推荐信
- 迄今为止的学位成绩单与证书
- 英语语言资格证明（如适用）
由 gemini-2.5-flash-lite 生成，博士岗判定置信度 100%。
岗位信息
- 最终轮次截止
- 2027-01-10
- 学科
- 工程
- 合同类型
- 项目资助
- 本站收录
- 内容更新
- 原帖导师候选（待核验）
- Dr Huanhuan Li
- 来源
- 南安普顿大学博士研究项目招生 · 最近核对 2026-10-17
- 详情核验
判定依据（原文摘录）
- 这是一个博士项目
Type of degree Doctor of Philosophy
- 学术背景要求
A UK 2:1 honours degree, or its international equivalent.
原文
View all current projects
Postgraduate research project
Risk-aware decision-making under uncertainty for autonomous navigation
Funding
Competition funded
Competition funded
View fees and funding
Type of degree
Doctor of Philosophy
Entry requirements
2:1 honours degree
2:1 honours degree
View full entry requirements
Faculty graduate school
Faculty of Engineering and Physical Sciences
Closing date
10 Jan 2027
On this page
About the project
Potential supervisors
Entry requirements
Fees and funding
How to apply
Contact us
About the project
Potential supervisors
Entry requirements
Fees and funding
How to apply
Contact us
About the project
How should an autonomous ship respond when navigational risk is uncertain and continuously changing? This project will develop risk-aware decision-making methods that combine predicted traffic situations, navigational risk, uncertainty, international regulations for preventing collisions at sea (COLREGs) and operational constraints to support safe navigation decisions, including collision avoidance, operational adjustment, supervision and fallback.
Autonomous ships must make navigation decisions in complex environments where the behaviour of other vessels, future traffic developments and associated risks are uncertain. Avoiding collision alone is not sufficient: decisions must also consider navigational rules, operational constraints, safety margins and the consequences of uncertainty.
This project will investigate risk-aware decision-making for safe autonomous navigation. The research will explore how dynamic navigational risk can be incorporated explicitly into autonomous decision processes, enabling navigation actions to respond to both the estimated level of risk and confidence in that assessment.
The project will investigate decision-making during vessel encounters, including crossing, head-on and overtaking situations. Potential actions may include maintaining course and speed, altering course, reducing speed or increasing separation. The research will examine how these decisions can balance navigational safety, COLREGs compliance and operational efficiency, particularly when the intentions or future trajectories of surrounding vessels remain uncertain.
The project will also consider situations in which continued autonomous operation may no longer be appropriate. Methods will be investigated for linking changing risk conditions to operational responses such as increased safety margins, function degradation, remote supervision, mode switching or fallback. Potential approaches include:
• probabilistic decision-making
• multi-objective optimisation
• risk-constrained planning
• model predictive methods
• machine learning
Methods will be evaluated using representative maritime traffic scenarios and simulation environments.
The project will advance autonomous navigation from collision avoidance towards risk-informed decision-making, contributing to safer and more explainable autonomous ship operations under complex and uncertain conditions.
The School of Engineering is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
Potential supervisors
Lead supervisor
Dr Huanhuan Li
PhD (Eng.), FHEA
Lecturer in Maritime Engineering
Research interests
• Maritime safety and security
• AI-driven autonomous shipping
• Decarbonisation and green shipping
Entry requirements
A UK 2:1 honours degree, or its international equivalent.
Fees and funding
We offer a range of funding opportunities for both UK and international students. Horizon Europe fee waivers automatically cover the difference between overseas and UK fees for qualifying students.
Competition-based Presidential Bursaries from the University cover the difference between overseas and UK fees for top-ranked applicants.
Competition-based studentships offered by our schools typically cover UK-level tuition fees and a stipend for living costs for top-ranked applicants.
Funding will be awarded on a rolling basis, so apply early for the best opportunity to be considered.
For more information, please visit our postgraduate research funding pages.
How to apply
Apply now
You need to:
• choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences
• select Full time or Part time
• search for programme PhD Engineering & the Environment (7175)
• add name of the supervisor in section 2 of the application
Applications should include:
• your CV (resumé)
• 2 academic references
• degree transcripts and certificates to date
• English language qualification (if applicable)
Contact us
Faculty of Engineering and Physical Sciences
For questions about applying, email our Doctoral College (doctoralcollege-admissions@soton.ac.uk).
Project leader
For an initial conversation, email Dr Huanhuan Li (Huanhuan.Li@soton.ac.uk).