Structure, Systems and Autonomy
Structure, Systems and Autonomy is a research theme within the Centre for Future Transport and Cities.
Research within this theme focuses on understanding the safety, efficiency and effectiveness of (connected and autonomous) transportation systems to design novel, safe, efficient and sustainable vehicles, including their structures, communication and control systems delivering future mobility solutions within an ever-evolving environment.
This includes but isn’t limited to:
- Developing and exploring efficient and effective numerical analysis and optimisation methods incorporating methods such as Finite Element Analysis, Reduced Order Modelling, Artificial Intelligence as well as heuristic and deterministic optimisation methodologies.
- Exploiting these methods to design and engineer lightweight highly efficient energy absorbing structures improving safety across all modes of transport whilst positively contributing to a sustainable greener future.
- Leveraging communication, cooperation and automation capabilities through adaptation and learning and cognitive decision-making to support vertical industries.
- Exploiting traffic forecasting, simulation and management to reduce the impact of congestions and investigate the deployment and impact of vehicular and infrastructure electrification.
- Designing path planning and control systems to operate vehicles safely, effectively and efficiently for conventional as well as electric powertrains.
- Creating digital twins to speed up the development and testing of novel intelligent and adaptive systems.
To create innovative state-of-the-art modelling, simulation, analysis, control, communication and optimisation methods and algorithms; delivering safe and efficient structures and systems rooted in research excellence, validated through experimentation whilst informed by industry, academia and government.
To maximise the societal, industrial and environmental benefits of future transport and communication systems
|Dr Jesper Christensen||Associate Professorfirstname.lastname@example.org|
|Dr Olivier Haas||Associate Professoremail@example.com|
|Dr Mike Blundell||Professor of Vehicle Dynamics and Impactfirstname.lastname@example.org|
|Dr Mauro Innocente||Assistant Professoremail@example.com|
|Dr Thomas Statheros||Assistant Professorfirstname.lastname@example.org|
|Dr Hamid Taghavifar||Assistant Professoremail@example.com|
|Dr Brandon Ballard||Research Fellowfirstname.lastname@example.org|
|Dr Faouzi Bouali||Assistant Professoremail@example.com|
|Dr Qian Lu||Assistant Professorfirstname.lastname@example.org|
|Dr Seongki Yoo||Assistant Professoremail@example.com|
Our research aims to increase our understanding of how safe, sustainable, efficient and effective transport systems of the future can be created. Find out more about some of our projects:
Simplified Modelling Strategies for Energy Absorbing Vehicle Structures. High computational costs required for crash analysis is a major challenge in the design and optimization of vehicle crash structures.
To maximize crash performance through innovative and safe vehicle architecture it is imperative that energy absorbing structural concepts can be implemented and optimized at early stages of vehicle design. This potential can be maximized through the development of rapid modelling strategies. This project explores modelling approaches for this particular application.
Automated annotation for Advance Driver Assistance Systems. Autonomous vehicles (AV) are using Advance Driver Assistance Systems exploiting information from camera and LiDAR to recognise actors and infrastructure in their environment in order to take appropriate actions. Training AV control systems require good and accurately annotated images.
This consultancy project, funded by L&T Technology Services Limited (LTTS), is developing machine learning methods to automatically annotate images, videos and LiDAR data by identifying road users, traffic signs, lane and road marking as well as the scene, the weather conditions and time of day.
This project will improve the consistency of manual, speed and repeatability of manual annotation.
Communication and positioning from 5G to 6G. Communication speed, effectiveness, robustness, resilience and security are key to realising the expected benefits of a fully connected environment.
This research focuses on visible light communication (VLC) which will be a new physical layer introduced in 6G. VLC can be faster, more secure and robust to interference compared to radiofrequency communication.
We have been looking at algorithms and material to realise the benefits of both VLC and visible light positioning
Traffic simulation and management to inform policy. Traffic is increasing around the world resulting incidents, congestions, wasted productive time and increased emission leading to significant health impacts.
In this area of research we have been developing microscopic traffic simulation models to evaluate the impact of traffic management, vehicle routing, peak spreading and lately wireless charging.
We can replicate current traffic and inform policy decisions on various method of traffic management and the impact of wireless charging for buses as well as electric and plug in hybrid.
5G/6G End-to-end Network Slicing Framework for Vertical Industries. This project aims at constructing a 5G/6G end-to-end (E2E) slicing framework, where “network slices” spanning all relevant domains (e.g., user devices, base stations and network infrastructure) are created and tailored to meet the heterogeneous needs of target industries.
All the practical aspects (e.g., orchestration, isolation, scalability, and security) associated with the design, deployment, and operation of these slices will be studied, and the required mechanisms will be developed. To demonstrate the benefits of the proposed framework in a real-world environment, a future-proof experimental 5G/6G slicing testbed, based on commodity hardware (e.g., software-defined radios (SDRs) and x86 computers) and open-source solutions, will be built and applied to significant use cases in the automotive industry.