AVPark: Reservation and Cost Optimization-Based Cyber-Physical System for Long-Range Autonomous Valet Parking (L-AVP)
- Submitting institution
-
University of Northumbria at Newcastle
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 22062009
- Type
- D - Journal article
- DOI
-
10.1109/access.2019.2930564
- Title of journal
- IEEE Access
- Article number
- -
- First page
- 114141
- Volume
- 7
- Issue
- -
- ISSN
- 2169-3536
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2019
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
5
- Research group(s)
-
F - Cyber Security and Network Systems (CyberNets)
- Citation count
- 1
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- In the UK, on average six to twenty minutes are spent finding a suitable car park, which increases fuel consumption, leaving a long-term impact on the environment. The work in AVPark presents a Long-range Autonomous Valet Parking (LAVP) model to act as a baseline for the autonomous parking in the connected autonomous vehicle industry. This work has a long-term positive impact on an individual by improving quality of travelling, addressing urban transportation challenges and preserving the environment from pollution. This work has led to further study on autonomous navigation and ride-sharing services.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -