Research outputs per year
Research outputs per year
Project Details
Description
Investigating all aspects of driving, including:
- driving and sharing driving between a vehicle driver and a sensor system,
- non-model-based control of a wheeled vehicle,
- modelling of a vehicle and a vehicle pulling one or more trailers,
- learning to drive,
- assistance and support with learning to drive,
- the effect of tiredness and time spent driving,
- driving mobile robots,
- and the ability to drive in different situations.
- driving and sharing driving between a vehicle driver and a sensor system,
- non-model-based control of a wheeled vehicle,
- modelling of a vehicle and a vehicle pulling one or more trailers,
- learning to drive,
- assistance and support with learning to drive,
- the effect of tiredness and time spent driving,
- driving mobile robots,
- and the ability to drive in different situations.
Key findings
Sharing driving between a vehicle driver and a sensor system using trust-factors to set control gains
Non-model-based control of a wheeled vehicle pulling two trailers to provide early powered mobility and driving experiences
- Driving and driver learning is different when provided with different levels of sensor support.
- Learning should be adjusted when providing different levels of sensor support
Rule-based system to assist a tele-operator with driving a mobile robot.
- Use of "self-reliance factors" can help, especially in deciding how to share control between humans and sensors
- Varying the level of sensor support varies ability to drive.
- Driving can be shared between a vehicle driver and a sensor system using trust-factors to set control gains.
Non-model-based control of a wheeled vehicle pulling two trailers to provide early powered mobility and driving experiences
- Driving and driver learning is different when provided with different levels of sensor support.
- Learning should be adjusted when providing different levels of sensor support
Rule-based system to assist a tele-operator with driving a mobile robot.
- Use of "self-reliance factors" can help, especially in deciding how to share control between humans and sensors
- Varying the level of sensor support varies ability to drive.
- Driving can be shared between a vehicle driver and a sensor system using trust-factors to set control gains.
| Short title | Vehicle Driving |
|---|---|
| Status | Active |
| Effective start/end date | 13/03/17 → … |
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
Fingerprint
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Sharing driving between a vehicle driver and a sensor system using trust-factors to set control gains
Sanders, D., Gegov, A., Tewkesbury, G. & Khusainov, R., Jan 2019, Intelligent Systems and Applications: Proceedings of the 2018 Intelligent Systems Conference (IntelliSys) Volume 1. Arai, K., Kapoor, S. & Bhatia, R. (eds.). Springer, p. 1182-1195 (Advances in Intelligent Systems and Computing; vol. 868).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile221 Downloads (Pure) -
Adjustment of tele-operator learning when provided with different levels of sensor support while driving mobile robots
Sanders, D., Ndzi, D., Chester, S. & Malik, M., Jan 2018, Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016. Bi, Y., Kapoor, S. & Bhatia, R. (eds.). United Kingdom: Springer, Vol. 2. p. 548-558 11 p. (Lecture Notes in Networks and Systems; vol. 16).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Open AccessFile182 Downloads (Pure) -
Non-model-based control of a wheeled vehicle pulling two trailers to provide early powered mobility and driving experiences
Sanders, D., 10 Jan 2018, In: IEEE Transactions on Neural Systems and Rehabilitation Engineering. 26, 1, p. 96-104 9 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile248 Downloads (Pure)