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Vandalism of road furniture in Kenya roads has been alarming over the years. For instance, KeNHA reported that 150 out of 200 (75%) road signages placed in the period between July to September 2022 had been vandalized posing danger to motorists who ply along the Nairobi –Narok busy highway. Despite its usefulness, there has been a challenge on how this data is collected and analyzed to give a clear picture of the road assets management. The manual methods of road assets data collection do not guarantee accuracy, are time consuming and output requires manipulation to achieve recording quality. The manipulations of data collected using manual methods does not give a fair value of road assets hence poor budgeting practices by the road agencies. Therefore, the main objective of the study was to evaluate mobile LiDAR technology use in road assets management with a case study of KeNHA highways in Nairobi City Metropolis Road network. Specifically, the study sought to assess mobile LiDAR technology use in the management of road surface pavement condition of KeNHA highways within Nairobi City Metropolis, to evaluate mobile LiDAR technology use in the management of road furniture inventory along KeNHA highways within Nairobi City Metropolis and to assess the effectiveness of Road Inventory and Condition Survey (RICS) data quality in Road Asset Management (RAM) of KeNHA Highways within the Metropolis. The research covered nine (9) dualled KeNHA highways spanning a total of approximately 277 Km, out of which a distance of 253 Km (91%) with assorted road surface conditions and furniture was sampled. The study adopted a correlational survey design. Data for this study was obtained through site visits through which spatial and non-spatial data was captured, and processed using a set of Mobile LIDAR technology gadgets. The cloud points in the sensor’s coordinate system were advanced to Universal Transverse Mercator (UTM) which presents measurements in meters. Descriptive statistics was used to explain the features of data collected. According to the findings detected across the sampled roads the average length, width and depth of potholes was 14.1cm, 8.7cm and average 3.8cm respectively. The pothole dimensions were significant in that they were easily detected. Some of the cracks and rusting were severe with an average length of 1-4meters and average width of 20cm. However, for the cracks and ruttings, the depth was not significant and hence detected but not applied as the units of measure were very minimal. The findings revealed that the accuracy level of data collection using mobile LiDAR was high at 86.6 % accuracy rate. The false hit and false miss percentages were 7.8 % and 5.6 % respectively. The interpretation of the high level of hits was that KeNHA had reasonably ensured maintenance of road assets on various highways in Nairobi City Metropolis despite the cited cases of vandalism. Pavement Surface Evaluation and Rating (PASER) findings revealed that most of the roads in the study area are in Good or Fair condition. However, some areas had poor score with visible slippage, cracks and potholes. The study concluded that automation of road asset management practices using the Mobile LiDAR technology presents an opportunity to improve the reliability, validity and timeliness of inventory data for effective decision-making, budgeting and planning purposes. Based on the findings, the study recommends that road agencies in Kenya make routine use of mobile LiDAR to collect accurate data on various road conditions as this will aid in corrective planning and accuracy in budgeting. |
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