Browsing by Author "Jayaratne, DND"

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item: Conference-Abstract
Evaluation of level of service for two-lane roads in Sri Lanka
Jayaratne, DND; Jayasinghe, PWPR; Pasindu, HR
Two-lane roads form a major part of Sri Lanka‟s road network. The ability to accurately estimate lane capacity and Level of Service (LOS) is a key element in highway planning and manage-ment, which is essential to develop an efficient road network. The current methodologies to estimate capacity and level of service do not satisfactorily incorporate the traffic and roadway characteristics in Sri Lanka. Speed-density models were developed using traffic flow data from surveys carried out at 14 locations, where the speed, flow, vehicle type was recorded. In addition, PCU factors were derived for eight vehicle types. The speed-flow model was derived from the results to calculate the capacity for a two-lane road, which was also adopted to define new threshold values for parameters such as average travel speed, volume to capacity ratio to evaluate LOS. The capacity estimate and new LOS evaluation criteria offers more applicable parameters to assess the existing highway condition for highway upgrading and it can be incorporated into transport planning models as an input when de-fining road network parameters.
item: Conference-Abstract
A simulation-based framework for connected vehicle cybersecurity impact assessment
(Transportation Engineering Group, Department of Civil Engineering, University of Moratuwa, 2023-12-08) Jayaratne, DND; Kamtam, SH; Lu, Q; Abdur, R; Ramli, MA; Mepparambath, RM; Shaikh, SA; Nguyen, HN; Jayantha, WRAN
As connected vehicle technologies become increasingly prevalent, offering groundbreaking capabilities for vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, the promise for improved traffic safety, efficiency, and sustainability has never been higher. However, this new frontier of transportation also brings unprecedented cybersecurity challenges that can compromise not just individual vehicles but entire traffic ecosystems. Vulnerabilities in these systems have the potential to cascade through transport networks, causing disruptions that extend beyond the initially affected vehicles to impact public safety, traffic flow, and operational efficiency. Incidents like the 2015 Jeep Cherokee hack by Miller and Valasek and the 2022 cyberattack on Russia's Yandex Taxi service demonstrate the severity of these challenges. In both cases, individual vulnerabilities escalated to disrupt broader systems—whether that meant remote control over a single vehicle's functions or sending hundreds of taxis to a single location, paralyzing a city's transportation grid. The ISO/SAE 21434 standard for Road Vehicles — Cybersecurity Engineering has emerged as a critical guideline in response to the growing threats posed by cyber vulnerabilities in the automotive sector. ISO/SAE 21434 focuses primarily on the in-vehicle system and delineates the structure of cybersecurity processes, providing detailed guidance on risk mitigation. However, this current framework has limitations. For instance, its risk assessment clause mainly addresses components within or on the vehicle's perimeter and is not designed to consider the systemic impact on broader transport networks. Additionally, the risk quantification based on the standard predominantly relies on assessor expertise, posing challenges for evaluating risks at the complex, interconnected transport systems level. To address these gaps, our study introduces a novel simulation-based framework to assess cybersecurity threats' operational impact on intelligent transport systems. While the existing ISO/SAE 21434 standard serves as a vital starting point, it falls short of capturing the cascading effects of cyber threats across an entire transportation network. Our framework aims to overcome this limitation by simulating realistic attack scenarios and their ripple effects throughout a transport system, capturing the immediate and cumulative operational impacts. The framework would offer insights to transport planners and automotive cybersecurity analysts, allowing for the development of more effective mitigation strategies. Our proposed simulation-based framework is designed to incorporate real-world cyber-attack scenarios from incident reports and academic literature for impact assessment. Currently, our development efforts are concentrated on the traffic layer simulation; however, it is planned to extend the framework to incorporate the network layers to create a robust representation of a connected vehicle ecosystem. The simulation has attacker models that interact with the simulated environment to trigger specific attack scenarios, which in turn gives rise to damage scenarios. We derive incident impact metrics based on the fundamental traffic flow parameters: speed, flow and density, focusing on operational disruptions within the transportation network. These metrics provide an impact assessment that captures the consequences of a cyberattack, offering critical insights into 17 the potential cascading effects on a transport system's operational integrity. In summary, our simulation-based framework provides an innovative approach to assess the operational impact of cybersecurity threats on intelligent transport networks. By integrating real-world attack scenarios, multi-layer simulations, and a tailored attacker model, the framework offers a deeper view of the potential consequences of cyber threats. This enables a more in-depth understanding of vulnerabilities and informs the development of more effective, context-sensitive mitigation strategies. Given the increasing prevalence and complexity of connected vehicle technologies, our framework will be valuable for researchers and industry stakeholders in evaluating the potential consequences of cyber-attacks on intelligent transport systems.
item: Conference-Full-text
Study of the impact roadside parking has on traffic flow characteristics - a vissim simulation based approach
(IEEE, 2020-07) Madushanka, PHS; Jayaratne, DND; Pasindu, HR; Edussooriya, C; Weeraddana, CUS; Abeysooriya, RP
With the increase in private vehicle ownership and urban space limitations, roadside parking has become a common sight in urban areas. Even though provision for parking is considered in an economic background, lesser attention has been paid for designing and planning of on-street parking lots. Due to this phenomenon effective lane widths have reduced causing reductions in capacity. Further, due to entry/exit movements of vehicles to and from the traffic stream shockwaves propagate causing additional delays, especially during high flow periods. Studies focused on the effects roadside parking manoeuvres have on traffic flow are sparse. Hence this study attempts to find the effects such movements have. With the evolution of micro simulation software, advanced traffic flow models can be employed for research studies. The PTV-VISSIM micro simulation software which adopts the ‘Wiedemann 74’ car following model was used to simulate heterogeneous traffic conditions observed on local roads. A location along the A3-Colombo Negombo road was selected for the study. Through simulation it was observed that capacity dropped by a value of approximately 17% when there were 250 parking manoeuvres per hour.
item: Conference-Full-text
Study on the applicability of capacity estimation methods to evaluate multilane highway capacity under heterogeneous conditions
(IEEE, 2021-07) Uswaththa, ULMA; Pasindu, HR; Bandara, JMSJ; Jayaratne, DND; Adhikariwatte, W; Rathnayake, M; Hemachandra, K
Highway capacity is an essential element in highway planning and traffic management. There are a number of methods developed to estimate highway capacity. Most of them focus on identifying the maximum flow or throughput using a traffic speed-flow model. However, it has been found that these capacity estimates are not practical as they cannot be sustained for long, under normal flow conditions. This research mainly focuses on using the breakdown probability approach, in capacity estimation methods which are currently used to estimate the capacity mainly for freeways. Breakdown probability methods such as the Product Limit Method (PLM), the Sustained Flow Index (SFI), the Highway Capacity Manual (HCM) method are used to check the applicability of the breakdown probability approach in calculating highway capacity under heterogeneous conditions. These breakdown probability methods were applied for data collected from two multilane highway locations where heterogeneous flow conditions were observed. The capacity values obtained through the breakdown probability approach were compared with the capacity values obtained from the Greenberg model which is the considered conventional method. The breakdown approach resulted in capacity values which are less by an overall range of 7.4% to 30.9% for both locations.
item: Conference-Abstract
Trazer video image processing software as a tool for heterogeneous traffic data collection
(Department of Civil Engineering, University of Moratuwa., 2017-07) Jayaratne, DND; Pasindu, HR; Pasindu, HR
Empirical traffic data is the basic input of any traffic related venture be its traffic management, transport planning, or research in the field of traffic engineering. According to its application different types of traffic data are required. The fundamental types of macroscopic traffic data are speed (km/h), flow (veh/h), and density (veh/km). Microscopic traffic data include dynamics of individual vehicles and how they interact with neighbouring vehicles and the road geometry in a traffic stream. Various traffic data collection methods are available for these purposes. Manual traffic data collection is the primary and oldest method used for data collection. But this method is neither cost effective nor consistently accurate. To overcome these issues alternate traffic data collection technologies such as pneumatic road tubes, Induction loops, Videography, Infrared detection were developed. Videography as a method for data collection is popular because the traffic condition can be visually observed later on. But extraction and analysis of traffic data from a video is a tedious process. Hence software programs such as TRAIS, COUNTcam, TrafficVision, TRAZER, MediaTD, Picomixer STA etc. have been developed. In this research, the software program TRAZER is used for traffic data collection, and its performance as a traffic data collection tool is analysed. The version of the TRAZER software used for this research provides the user with the facility to detect 4 main vehicle categories; namely, Light moving vehicles (LMV), Heavy moving vehicles (HMV), Three Wheelers (3W) and Two wheelers (2W). HMV’s are further classified as Buses (BUS) and Trucks (TRUCK). Two 1-hour videos were recorded according to the specifications for analysis in this research. One at Pannipitiya (video 1) overlooking the A4 highway from an overhead foot bridge and one at the Colombo-Katunayake (video 2) Expressway overlooking the expressway from an overpass near Peliyagoda. The software offers options to delete, reclassify and add vehicles to its output thereby giving the user the ability to rectify software errors and raise the accuracy of the count to 100%. Video 1’s initial vehicle count was 62.3% greater than the actual value. (4503 as opposed to the actual flow of 2774 vehicles) This was mainly due to phantom detection of motor cycles. The primary reason for this being the recognition of vehicle side mirrors as motor cycles. Once the incorrectly detected vehicles were deleted the flow value reduced to 2073, which is 25.3% less than the actual value. This was rectified by adding the overlooked vehicles manually. Video 2’s output was more accurate. The main reason for this is the absence of motor cycles and three wheelers in the expressway. The initial flow value was 1104 vehicles. Once accidental recognitions were removed, the value reduced to 953 which was 23.9% less than the actual value of 1252 vehicles. From this, it can be seen that the software provides vehicle counts to an accuracy of approximately 75% once accidental recognitions are removed. An advantage of using the software is that the accuracy can be raised to 100% manually. But a significant amount of time must be spent to identify the vehicles that are not captured by the software. TRAZER also gives individual speeds and trajectories of each vehicle. The speed estimations were checked by manually calculating the speed of selected vehicles from each category by observing the recorded video. The estimated speeds were found to be similar to the values derived manually. From this research, it can be concluded that TRAZER is an acceptable tool to collect and analyse traffic data even though conclusive results were not observed in the initial runs. This may partly be due to user errors in handling the software and capturing the video or issues unique to the analysed videos. Further studies should be done to analyse the speeds more accurately as well the vehicle trajectories.