Next Road Rerouting: A Multiagent System for Mitigating Unexpected Urban Traffic Congestion
- Submitting institution
-
Manchester Metropolitan University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 2330
- Type
- D - Journal article
- DOI
-
10.1109/TITS.2016.2531425
- Title of journal
- IEEE Transactions on Intelligent Transportation Systems
- Article number
- -
- First page
- 2888
- Volume
- 17
- Issue
- 10
- ISSN
- 1524-9050
- Open access status
- Out of scope for open access requirements
- Month of publication
- March
- Year of publication
- 2016
- URL
-
https://e-space.mmu.ac.uk/609043/
- 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
-
3
- Research group(s)
-
D - Smart Infrastructure
- Citation count
- 48
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This paper proposed a novel vehicle re-routing system ‘Next Road Rerouting (NRR)’, to help drivers to avoid unexpected congestion. NRR addressed problems usually overlooked within the ITS research community and led to a significant increase in the number of papers proposing re-routing (more than 150 new publications in IEEE’s digital library and 34% of them cite NRR). Examples: Z. Wang et al. (IEEE Access 2020) who extended NRR to cover off-road urban events; D. L. Guidoni et al. (IEEE Access 2020) Re-Route Service was inspired by NRR. Our follow-on paper enhanced NRR’s responsiveness to traffic conditions using connected vehicles technology.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -