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Research Reports

MRR 227: Surrogate Measure Of Estimating Real-Time Traffic Volume


The study aims to estimate  real-time  traffic volume on road networks  by utilising Google Traffic Data. Section 1.0 elaborates on the current state of traffic monitoring in Malaysia. The existing method of traffic monitoring  in Malaysia mostly involves traffic  count  and  classify  the  vehicle  manually  by  enumerators  or  video  camera. With the aim to ease the data collection of traffic volume, the objective of this study is  to estimate real-time traffic volume on road network  by utilising Google Traffic Data. This study will also come in handy where traffic volume study is hard to be conducted at the site, e.g.: site with limited space, or site constraint as long as there is Google Traffic Data present at the location.
 
There are six methods of conduction traffic volume study mentioned. The first one is through toll plaza ticketing. As every vehicle that passes through the toll plaza will have to pay, the number of vehicles can be known by segregating in according to its class. Secondly is by registration offices and in Malaysia is carried out by the Road Transport Department (RTD). Next is by statistical approach whereby only applicable when there  are records  from the past maintained  effectively  and efficiently.  The fourth  method  is  by  interviewing.  However,  this  method  is  not  easily  managing because many of the transporters will not stop for an interview even a second. The fifth method is by check posts and the last method is by Global Positioning System (GPS).
 
According  to  the  methodology  flowchart,  the  project  will  start  with  desk  study followed by site selection, data collection, data analysis/modelling  and lastly report writing.  Analyses   done  are  the  general   analysis,   speed   pattern   by  location   and  also independent sample T-test. Under general analysis, there is descriptive analysis and also correlation analysis. As for speed pattern by location, graphs indication speed pattern of Google Traffic Data and space mean speed were compared differentiating the  site  and  hourly  factor.  Lastly  in  Section  5.0 conclusion  and  recommendation  of the study were discussed.

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