Operational Design Domain Requirements for Improved Performance of Lane Assistance Systems: A Field Test Study in The Netherlands

Reddy, Nagarjun; Farah, Haneen; Huang, Yilin; Dekker, Thijs; Arem, Bart van

doi:10.1109/ojits.2020.3040889

Cited by 16 publications

(6 citation statements)

References 20 publications

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“…This can be proved helpful for further research on roads' geometric design or road infrastructure requirements for AVs. Another prominent gap that we identified concerning the AVs' simulations is that the current methodologies cannot capture severe weather conditions or road gradients, impacting vehicles' efficiency and performance (Khoury, Amine, & Abi Saad, 2019;Zang et al, 2019), especially the performance of lane-keeping systems (Farah et al, 2020;García and Camacho-Torregrosa, 2020;Reddy, Farah, Huang, Dekker, & Van Arem, 2020).…”

Section: Discussionmentioning

confidence: 99%

Safety implications of higher levels of automated vehicles: a scoping review

et al. 2021

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Automated vehicles (AVs) promise to improve road safety, reduce traffic congestion and emissions, and enhance mobility. However, evidence regarding their safety benefits has not been systematically investigated and documented. In this study, we utilise a scoping review approach to investigate and synthesise the existing literature on higher levels of AVs' safety implications. This aids future relevant studies by identifying the research gaps and reporting the methodological approaches used. The review focused not only on peer-reviewed articles but also on grey literature to provide a comprehensive overview of the current research state. In total, 5724 articles were identified, and 4167 records were screened after duplicates and dual publications removal, from which 27 were found eligible for review. Ultimately, 24 studies met all the inclusion criteria and were considered for the review. The reported evidence was focused on changes in road safety levels after the deployment of AVs in transport networks. The data was extracted and charted by one reviewer using tables to create a descriptive summary of the results and address the scoping review's questions and objectives. In general, the findings suggest that AVs hold the potential to improve the overall safety on roads, although the existing evidence is not mainly based on real data but assumptions regarding vehicles' capabilities and behaviour. The limited number of studies and the fact that all of them were published or conducted after 2014 indicate that the research on AVs' safety impacts is just emerging.

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Section: Discussionmentioning

confidence: 99%

Safety implications of higher levels of automated vehicles: a scoping review

et al. 2021

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“…García et al [133] found that the horizontal curvature of roads limited the maximum speed that vehicles could attain without disengaging the ADS. Reddy et al [110] and García and Camacho-Torregrosa [134] found that the lane width affected the ability of LKSs to detect the lane markings, 2.5 m was the maximum width which always required the intervention of the driver.…”

Section: F Physical and Digital Infrastructurementioning

confidence: 99%

“…Cafiso and Pappalardo [109] conducted a field test to evaluate vision-based systems in detecting lane markings and found that lane keeping system (LKS) functioned in over 97% under optimal conditions. Similarly, Reddy et al [110] evaluated the performance of detecting lane markings of a LKS under different visibility and speed conditions. Their findings showed that the best performance was achieved in dark, dry conditions without streetlights, while the lowest performance was during wet, dark conditions with streetlights.…”

Section: Vehicle Sensor-based Perceptionmentioning

confidence: 99%

Modeling Automated Driving in Microscopic Traffic Simulations for Traffic Performance Evaluations: Aspects to Consider and State of the Practice

Farah

Postigo²,

Reddy

et al. 2023

IEEE Trans. Intell. Transport. Syst.

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The gradual deployment of automated vehicles on the existing road network will lead to a long transition period in which vehicles at different driving automation levels and capabilities will share the road with human driven vehicles, resulting into what is known as mixed traffic. Whether our road infrastructure is ready to safely and efficiently accommodate this mixed traffic remains a knowledge gap. Microscopic traffic simulation provides a proactive approach for assessing these implications. However, differences in assumptions regarding modeling automated driving in current simulation studies, and the use of different terminology make it difficult to compare the results of these studies. Therefore, the aim of this study is to specify the aspects to consider for modeling automated driving in microscopic traffic simulations using harmonized concepts, to investigate how both empirical studies and microscopic traffic simulation studies on automated driving have considered the proposed aspects, and to identify the state of the practice and the research needs to further improve the modeling of automated driving. Six important aspects were identified: the role of authorities, the role of users, the vehicle system, the perception of surroundings based on the vehicle's sensors, the vehicle connectivity features, and the role of the infrastructure both physical and digital. The research gaps and research directions in relation to these aspects are identified and proposed, these might bring great benefits for the development of more accurate and realistic modeling of automated driving in microscopic traffic simulations.

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“…• The specific conditions under which a given driving automation system or feature thereof is designed to function, including, but not limited to, driving modes [4] • Everything that an automotive system can be exposed to on the road [5] • A subset of all the possible situations that could be dealt with by a human driver [6] • A set of driving conditions under which a certain Automatic Driving System (ADS) is designed to function [7] • An abstraction of the operational context for an ADS [8] • The domain over which an automated vehicle can operate safely [9].…”

Section: A the Operational Domain Modelmentioning

confidence: 99%

Defining an Effective Context for the Safe Operation of Autonomous Systems

Osborne,

Hawkins

2024

Communications in Computer and Information Science

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The safety of a system can only be demonstrated to have been achieved in a defined context. This is true whether it is a 'traditional' or autonomous system (AS). For traditional systems, a human is trusted to provide an oversight of operations, and react safely to unexpected scenarios that occur. For AS we cannot necessarily rely on human oversight to handle unexpected events, and must therefore be more confident that all possible hazardous scenarios are understood prior to operation. This makes the task of defining the context of safe operation (CSO) precisely and completely even more important for an AS so that unexpected scenarios can be limited. Attempting to define the CSO completely for an AS operating in a complex openworld environment could be an intractable task. It is therefore imperative that an effective and efficient way to define the CSO for AS can be found.Existing approaches to defining the CSO for AS are generally seen to be disjoint (in that each of the elements is considered and specified in isolation) and lacking in focus (in that the level of detail is found to be inconsistent and often inappropriate). What is required therefore is a targeted, iterative and integrated approach for defining the CSO for an AS. We provide an example of how this approach can be used to deliver an effective CSO for an autonomous robot.

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Operational Design Domain Requirements for Improved Performance of Lane Assistance Systems: A Field Test Study in The Netherlands

Cited by 16 publications

References 20 publications

Safety implications of higher levels of automated vehicles: a scoping review

Safety implications of higher levels of automated vehicles: a scoping review

Modeling Automated Driving in Microscopic Traffic Simulations for Traffic Performance Evaluations: Aspects to Consider and State of the Practice

Defining an Effective Context for the Safe Operation of Autonomous Systems

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