3D Computer Vision and Wireless Sensor Applications in an-experimental Study on Electric Vehicle Driving in Roundabout Negotiation Scenarios
González-Ortega, David, Scott, Helen, Javier Díaz-Pernas, Francisco and Knowles, Michael (2014) 3D Computer Vision and Wireless Sensor Applications in an-experimental Study on Electric Vehicle Driving in Roundabout Negotiation Scenarios. In: European Electric Vehicle Congress, 3-5 Dec 2014, Brussels, Belgium.
Item Type: | Conference or Workshop Item (Paper) |
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Abstract
In this paper, a 3D computer vision application and a wireless sensor application are presented. They were used in an experimental study on electric vehicle driving to analyse the influence of age on driving style in roundabout scenarios. The 3D computer vision application uses the Kinect device to achieve face tracking of the driver. From the pith, roll and yaw angles of the face, the gaze can be estimated. Thus in each processed image, the region, from the predefined ROIs, where the driver is gazing at can be estimated. Gaze patterns and transitions in driving situations, particularly while negotiating roundabouts, can be determined. The wireless sensor application uses the gyroscope included in a 9DoF (Degrees of Freedom) sensor from the Shimmer platform. The gyroscope was placed on the steering wheel. The signal corresponding to the turn axis of the steering wheel is obtained so that the direction and speed of any turn can be detected. Besides, the heart rate was monitored and the electric car used in the experiments was equipped with an extensive telemetry system. 28 people took part in the experiments. They drove on the same 13-kilometer on-road route in Sunderland (UK) using a Smart Fortwo electric vehicle and on a route with a Forum 8 driving simulator. Only a brief description of the experiments is included. Results and analysis will be presented in the future. Experimental studies with electric cars are needed to support their progressive penetration in the market.
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PDF
3D_Computer_Vision.pdf - Accepted Version Download (354kB) |
More Information
Depositing User: Barry Hall |
Identifiers
Item ID: 5234 |
URI: http://sure.sunderland.ac.uk/id/eprint/5234 | Official URL: http://www.eevc.eu/ |
Users with ORCIDS
Catalogue record
Date Deposited: 20 Jan 2015 16:07 |
Last Modified: 18 Dec 2019 15:37 |
Author: | Helen Scott |
Author: | Michael Knowles |
Author: | David González-Ortega |
Author: | Francisco Javier Díaz-Pernas |
University Divisions
Faculty of TechnologyFaculty of Technology > School of Engineering
Faculty of Technology > School of Engineering > The Institute for Automotive and Manufacturing Advanced Practice
Subjects
Engineering > Automotive EngineeringActions (login required)
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