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 → … |
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique 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 AccessFile217 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 AccessFile163 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 AccessFile239 Downloads (Pure)