Automatic recognition of driving scenarios for ADAS design

Lucchetti, Alberto; Ongini, Carlo; Formentin, Simone; Savaresi, Sergio M.; Re, Luigi del

doi:10.1016/j.ifacol.2016.08.017

Cited by 9 publications

(4 citation statements)

References 6 publications

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“…Advanced driver assistance system (ADAS) and autonomous driving technologies are constantly evolving. ADAS uses various sensors, such as cameras, radar, and GPS, to perceive the surroundings of vehicles, help drivers to detect potential dangers, with a potential to decrease reaction times, and improve safety through early warning and partial automatic control [1]. Autonomous driving technologies allow vehicles the capability of sensing their environment and moving safely with little or no human input [2].…”

Section: Introductionmentioning

confidence: 99%

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Urban Residents’ Willingness to Choose and Pay for ADAS and Autonomous Driving Functions: Comparison of Two Cities in China

Wang

Jiang

Dong

et al. 2022

Journal of Advanced Transportation

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ADAS and autonomous driving are booming. As technologies continue to innovate and mature, whether travelers understand, accept, and buy them will directly impact the technological development, popularization, and profitability of these products. This study analyzes the influence of urban residents’ personal, family, and commuting characteristics on their willingness to choose and pay for ADAS and autonomous driving functions. Using the questionnaire survey data for Jiading and Meishan in China, Logit models are established for willingness to choose, and linear regression models are established for willingness to pay. Although Jiading and Meishan are similar in terms of city size and population, there are some differences in the influencing factors for willingness to choose and pay because of the differences in industrial structure, city culture, and residents’ commuting habits. The results show that significant influencing factors vary for different levels of ADAS and autonomous driving functions. The findings of this research can provide a reference for city authorities, designers, and sellers of ADAS products or autonomous vehicles to identify potential buyers and promote related products.

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Section: Introductionmentioning

confidence: 99%

“…1 Respondents can select one or more answers 2. Respondents can select one or more answers or none of them.…”

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confidence: 99%

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Urban Residents’ Willingness to Choose and Pay for ADAS and Autonomous Driving Functions: Comparison of Two Cities in China

Wang

Jiang

Dong

et al. 2022

Journal of Advanced Transportation

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“…As the real vehicle testing methods such as naturalistic field operational test (NFOT) [5], ground test [6], do not have good controllability of the surroundings, some researchers use virtual simulation strategy to realize the automatic construction of traffic environment model (e.g., road, weather, and other traffic participants). Lucchetti et al used the off-line data of vehicular sensors collected by real-time simulator Dspace Autobox to realize automatic environment recognition, scenes construction and test execution [7]. Mugur developed a testing tool "TestWeaver" that can form a test matrix (TM) by taking every aspect of the scenario as one dimension, and can also search for the scenarios that have not been covered before [8].…”

Section: Introductionmentioning

confidence: 99%

Automated scenario generation and iterative regression testing method for autonomous driving systems

Duan

Wang²,

Zhao

et al. 2022

International Conference on Smart Transportation and City Engineering (STCE 2022)

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In this paper, we propose a new automatic test and evaluation method that can be used for autonomous driving systems in virtual simulation test. Aiming at the problems that the existing automated test method cannot guarantee coverage and validity of the test scenarios, and evaluation lacks the consideration of the complete development life cycle of the systems, we firstly introduce a new scenarios generation method that can generate scenarios with higher overall effectivity on the premise of ensuring coverage. Then, an integrated test platform is constructed, in which the components can be automatically invoked by test scripts. Finally, the automated iterative regression testing is used to ensure the effectiveness of the whole development and test process. The application and verification of a level three (L3) Traffic Jam Pilot (TJP) system is carried out on the above-stated method. The result shows that the proposed method can effectively detect system defects and significantly improve test efficiency.

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Answering Temporal Conjunctive Queries over Description Logic Ontologies for Situation Recognition in Complex Operational Domains

Westhofen,

Neurohr,

Jung

et al. 2024

Lecture Notes in Computer Science

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For developing safe automated systems, recognizing safety-critical situations in data from their complex operational domain is imperative. This capability is, for example, essential when evaluating the system’s conformance to specified requirements in test run data. The requirements involve a temporal dimension, as the system operates over time. Moreover, the generated data are usually relational and require additional background knowledge about the domain for correctly recognizing the situation. This fact makes propositional temporal logics, an established tool, unsuitable for the task. We address this issue by developing a tailored temporal logic to query for situations in relational data over complex domains. Our language combines mission-time linear temporal logic with conjunctive queries to access time-stamped data with background knowledge formulated in an expressive description logic. Currently, however, no tools exist for answering queries in such settings. We hence also contribute an implementation in the logic reasoner Openllet, leveraging the efficacy of well-established conjunctive query answering. Moreover, we present a benchmark generator in the setting of automated driving and demonstrate that our tool performs well when tasked with recognizing safety-critical situations in road traffic.

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Automatic recognition of driving scenarios for ADAS design

Cited by 9 publications

References 6 publications

Urban Residents’ Willingness to Choose and Pay for ADAS and Autonomous Driving Functions: Comparison of Two Cities in China

Urban Residents’ Willingness to Choose and Pay for ADAS and Autonomous Driving Functions: Comparison of Two Cities in China

Automated scenario generation and iterative regression testing method for autonomous driving systems

Answering Temporal Conjunctive Queries over Description Logic Ontologies for Situation Recognition in Complex Operational Domains

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