This app is capable of evaluating overall condition of a pavement section based on some commonly found distresses. The app takes distress density as input and provides the evaluated condition of the pavement section in terms of probability. The app also suggest necessary treatment based on combination of the distresses. Currently this app is on a trial version.

How to use: Anyone can use this trial version of the app as a web app. You are required to provide your email address at the beginning or signing is available with your google account. The app has two sements. The “Training” segment gives you idea about different pavement distresses and how you should select density for each distress. Based on your idea from the “Training” segment you can go for field inspection and collect necessary data. Second segment is the “Rating” segment where you select different distress densities according to guideline provided in the “Training” segment. You will get overall condition of the pavement section in term of probability. This probability value basically tells you the probability of the pavement section being an acceptable condition. By default, any probability value of 0.5 or more is considered as “Acceptable.” See the “Recommendation” part at the bottom to see what the app suggests for pavement you inspected.

Note: This app has been built utilizing public opinion survey data of Newfoundland and Labrador conducted by the researcher. Therefore, the application is limited and should be correlated to the municipalities of Newfoundland and Labrador only. Also, this app is workable for the low volume paved roads only. The app still in a trial mode therefore discrepancies can be seen.

Link to the Software: MUNPave App

How to use it: MUNPave Tutorial

Link to the Original Paper: The MUNPave Model Paper

Contact Information:

Dr. Kamal Hossain
Assosiate Professor
Department of Civil and Environmental Engineering
Carleton University, Ottawa
Advanced Road & Transportation Engineering Lab (ARTEL)
Ottawa, Ontario, K1S 5B6, Canada
Email: kamal.hossain@carleton.ca

Shajib Guha
Master’s Candidate
Department of Civil Engineering
Advanced Road & Transportation Engineering Lab (ARTEL)
Memorial University of Newfoundland
St. John’s, NL, Canada
Email: skguha@mun.ca