342
Views
3
CrossRef citations to date
0
Altmetric
State of the Art

Potential applications of connected vehicles in pavement condition evaluation: a brief review

, ORCID Icon, &
Pages 889-913 | Received 04 Jan 2023, Accepted 26 Jun 2023, Published online: 19 Jul 2023
 

Abstract

Road authorities are concerned with maintaining the road condition at a high level of service to minimise user and agency costs. For this purpose, they have to monitor the road condition regularly. Pavement condition monitoring with automated data collection vehicles is costly. One emerging technology that has been widely applied in transportation is connected vehicles. They have various sensors to monitor their ambient condition and transfer the data to infrastructure or other vehicles. They could be employed as a cost-effective method in pavement condition evaluation which has been taken for granted. This study aims to review research studies investigating the potential of connected vehicles collected data in assessing pavement conditions. Moreover, the sensors used in these vehicles, data types collected, and analysis methods utilised are being scrutinised. It is concluded that the connected vehicles have excellent potential to be applied as a crowd-sourced-based and cost-effective approach in pavement data evaluation.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 204.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.