Institutional-Repository, University of Moratuwa
Welcome to the University of Moratuwa Digital Repository, which houses postgraduate theses and dissertations, research articles presented at conferences by faculties and departments, university-published journal articles and research publications authored by academic staff. This online repository stores, preserves and distributes the University's scholarly work. This service allows University members to share their research with a larger audience.
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Recent Submissions
item: Thesis-Abstract
Critical factors affecting the practice of alternative dispute resolution methods in building projects in Sri Lanka
(2022) Thilina, KMGR; Devapriya, KAK
The construction industry is a unique and complicated industry that interacts with a variety of stakeholders with differing attitudes, abilities, and degrees of knowledge in the construction process, all of whom must work together to achieve their own objectives and realize their own benefits. Therefore, conflicts, disputes and claims are higher in the construction industry while comparing with other industries. Disputes can arise at any time during the period of a construction project. A dispute is one of the key factors which burdens the successful completion of the project.
Mechanism adopts to resolve any dispute arises during the execution of construction project is vital to the success of a project. There are two main ways of resolving disputes in a construction project which are litigation and Alternative Dispute Resolution methods. Due to the disadvantages in Litigation, ADR mechanisms are commonly used mechanisms to settle dispute in the construction industry. However, existing ADR mechanisms are also have various demerits. It is important to identify the factors which are affecting on building projects in Sri Lanka to promote and effectively use ADR methods as a dispute resolution mechanism.
The literature review was used to develop research framework for this study. Through literature review, twenty-two factors that are affecting the practice of ADR methods in the building projects were found. Then, a questionnaire survey has been undertaken to identify the impact of those factors on the practice of ADR methods in the building projects in Sri Lanka. Data collected through the questionnaire survey was analysed using mean weighted rating and identified twenty two factors were ranked according to the significant level of factors. As an example, the top five factors are savings in cost, the enforceability of the decision, the flexibility of procedure, savings in time, and reduction in project disruption. Finally, the findings of this research can be used to develop a model to select the most suitable ADR method by comparing it with the other available ADR methods and developing new ADR methods to mitigate the drawbacks of existing ADR methods.
item: Conference-Abstract
Proceedings of International Conference on Advances in Highway Engineering & Transportation Systems (ICAHETS) (Online)(Pre-text)
(Transport Engineering Division, Department of Civil Engineering, 2024) Pasindu, H.R.
item: Conference-Abstract
An Economical GPS-Based Driving Cycle for 3-Wheelers: Establishing a Framework for Emission Studies
(Transport Engineering Division Department of Civil Engineering, 2024) Jayawardhana, S.; Aponsu, K; Gamage, S.; Perera, L; Pasindu, H.R.
The research presents a detailed approach to developing a driving cycle tailored for 3-wheelers in Sri Lanka, addressing the need for accurate emission estimation in the context of increasing vehicle populations with a significant proportion of 3-wheelers, and environmental concerns. Previous studies have highlighted the critical role of driving cycles in estimating emissions, particularly in urban environments where traffic patterns are complex and variable. It identifies two primary approaches to emissions modelling: fuel-based and travel-based models. While fuel-based models rely on fuel consumption data, travel-based models, including driving cycles, utilize real-world driving behaviour data to provide a more accurate representation of emissions. The review identifies a notable gap in the development of driving cycles for 3-wheelers in Sri Lanka, despite their prevalence in the transport sector. Therefore it is clear that a dedicated driving cycle is required, leading to enhanced emission inventory estimations through localized emission factors, and informed policy decisions aimed at reducing air pollution.
The study utilizes a micro-trip-based construction method to develop the driving cycle, which is particularly effective for capturing the stop-and-go nature of urban driving. The research involved a representative route selection, focusing on urban and suburban areas in Colombo and Matara, where 3-wheelers are commonly used. The selected routes were designed to reflect typical driving conditions, incorporating a mix of road types and traffic volumes. This careful selection process is crucial, as it ensures that the driving cycle accurately represents the diverse traffic behaviours in real-world scenarios. Data collection was conducted using an onboard GPS device, which recorded driving behaviour with high precision. This method was chosen over the chase car approach due to the unpredictable nature of driver behaviour in Sri Lanka, which can lead to incomplete data in congested traffic. The study gathered over a million data points from five drivers operating Bajaj 4-stroke petrol 3-wheelers, focusing on peak traffic hours to capture the most representative driving patterns. The data was then filtered and pre-processed using Python scripts to eliminate anomalies, ensuring the integrity of the dataset. The construction of the driving cycle involved categorizing driving data into micro-trips, which are segments of driving between stops. This approach allows for a detailed analysis of driving behaviour, capturing variations in speed, acceleration, and deceleration. The study utilized a systematic method to balance the representation of different driving conditions by binning micro-trips based on their average speeds. This technique ensured that the final driving cycle accurately reflected the average driving behaviour of 3-wheelers in the selected regions.
The results of the study revealed an average speed of 15.12 km/h, with significant time spent in acceleration (40.58%), deceleration (33.84%), and cruising or idling (25.58%). These findings highlight the frequent stop-and-go conditions of urban traffic, validating the effectiveness of the micro-trip-based method for driving cycle development. The adaptability of the developed driving cycle methodology across South Asia is emphasized, providing a framework that can be tailored to local conditions in other countries where 3-wheelers are prevalent.
In conclusion, this research not only fills a critical gap in the existing literature regarding driving cycles for 3-wheelers but also offers a methodology for emission estimation that can inform policy decisions aimed at improving air quality and public health in Sri Lanka and beyond. The study's findings advocate for the testing of the developed driving cycle on a chassis dynamometer to obtain precise emission data alongside emission factors, ultimately contributing to more sustainable urban transport solutions.
item: Conference-Abstract
Criteria for Assessing the Effectiveness of a Non Real Time Coordinated Cluster of Signalized Intersections
(Transport Engineering Division, Department of Civil Engineering, 2024) Kapuge, A. B. A.K.V.S.; Bandara, J. M. S. J.; Jayasooriya, N.; Pasindu, H.R.
Given the limited resources available for installing advanced signal controllers, many researchers and professionals believe that well-designed coordinated fixed-time signal control, combined with well-defined corridor coordination, is a cost-effective option. In this study, two closely spaced intersections were considered for analysis. It was identified that a subsystem consists of spatial elements (the link road that connects two signalized intersections) and temporal elements (the relative offset between the signals of the two intersections). Throughput, travel time, delay, queue length, and flow efficiency were considered basic performance measurement parameters. The traffic flow analysis was conducted using the Vissim model, with calibration parameters adjusted to suit Sri Lankan conditions based on previous research. Twenty demand models were evaluated, with volume-to-capacity (v/c) ratios ranging from 0.2 to 0.9 across the two intersections. The traffic flow was analyzed under three scenarios: Scenario 1 consisted of 60% through traffic, 20% left-turn traffic, and 20% right-turn traffic. In Scenario 2, the traffic distribution was 60% through traffic, 30% left-turn traffic, and 10% right-turn traffic. Scenario 3 featured 60% through traffic, 10% left-turn traffic, and 30% right-turn traffic. The Vissim model's link road geometry was kept at 500 meters, and both junctions were identical. The east-west direction was treated as the coordinated direction with three lanes, while the north-south cross streets had two lanes. Base saturation flows and offset optimization were calculated using Akcelik’s (1981) method, and cycle timing was determined based on the Webster formula. The study extended its analysis to compare unsynchronized (Case 1) and synchronized (Case 2) models. Initially, travel time was plotted against throughput. Based on the Elbow method, three clusters were identified as the optimal cluster number and then K-means clustering was performed. Generally, Cluster 1 had low flow and moderate traffic, Cluster 2 had moderate to high flow but moderate travel time, and Cluster 3 had moderate flow and high travel time. When the mean values for each cluster were compared in the unsynchronized and synchronized models, signal synchronization improved all key metrics in each cluster, except for queue length on the link road in Cluster 3, and throughput and flow efficiency in Cluster 2. Based on the Independent-Samples T-Test p-value, statistically significant improvements were found in travel time, with an 8.74% improvement in Cluster 2 and a 14.34% improvement in Cluster 3. Delay improvements were 29% and 30% in Clusters 2 and 3, respectively. However, there was a 35.17% increase in queue length on the link road, suggesting that while flow efficiency and delays improved, congestion remained an issue. As a further performance check, the Min-Max Normalization and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods were used. Both methods ranked Cluster 3 as the highest performer, despite the increase in queue length. Finally, considering the Level of Service (LOS) criteria from the Highway Capacity Manual, Cluster 3 showed an improvement from LOS E and D to LOS C, whereas Cluster 2 showed an improvement from LOS C and B to LOS B and Cluster 1 remained at LOS B and A. The most notable result from this research is the identification of Cluster 3 as the best-performing cluster across multiple scenarios, while Cluster 2 provided moderate improvement and Cluster 1 showed no significant improvement. Therefore, this study suggests that to gain the benefits of synchronization, the intersections considered should initially fall within the range of Cluster 3 or Cluster 2. Further research is required to explore how intersection geometry and coordination direction affect synchronization.
item: Thesis-Abstract
Real-time human detection analytics in constrained image inputs
(2022) Fernando, Heshan; Perera, I; De Silva, C
Real-time video surveillance is a growing trend today. Our surrounding is being monitored daily by an increasing number of surveillance camera systems. Analyzing human movement can be used for the wellbeing of humans. There are a set of analytical tools and algorithms which can be used to detect, track, and analyze humans in images. Human movement analytics has various subdomains including human detection, human recognition, human tracking, human localization, human reidentification, human behavior analysis, and abnormal activity detection. Human detection is the most crucial step among them, and which helps to derive other sub domains.
Human detection analytics in constrained lighting conditions would be a challenging task to apply due to the low contrast of the image context. Currently available systems focused on the daytime. The background light is an essential factor in the camera images, which rigorously affects the quality of the image. We can identify considerable differences if we compare two images at the rich light condition and constrained light condition. Fewer features of the objects can be extracted in constrained light conditions than rich light conditions. Illumination of the background context is an important factor if we focus on such applications. Currently, most researchers have used human detection analytics in visible light. RGB image shows a clear view when there is sufficient light existing, and it is highly sensitive to visible light conditions compared to infrared. In this research, we considered infrared images as constrained image inputs.
Our proposed methodology contains a novel human detection approach based on machine learning and a motion dynamic model. Here we have addressed the problem using a combination of Deep Convolutional Neural Networks (DCNN) for human detection and Kernelized Correlation Filters (KCF) for human tracking. MobileNet pre-trained model is used for frame-wise human detection as the first step. Then the KCF object tracking algorithm is used to increase the human detection accuracy while tracking the human in the context. Furthermore, we applied some preprocessing techniques to reduce the noise effects. Currently, the progress made by this research-based project is sufficient to initiate the development of a complete human detection analysis solution based on live CCTV camera footage. This solution provides the core functionality of human detection analytics and it can be easily adapted to different domain solutions such as customer behavior analytics in a supermarket or worker movement analytics in an industrial premise.