DriveFuzz

Kim, Seulbae; Liu, Major; Rhee, Junghwan; Jeon, Yuseok; Kwon, Yonghwi; Kim, Cheol

doi:10.1145/3548606.3560558

Cited by 26 publications

(11 citation statements)

References 39 publications

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“…Currently, the more popular method is fuzz testing based on multi-objective optimization (Huai et al, 2023;Cheng et al, 2023;Kim et al, 2022;Li et al, 2020;Tian et al, 2022). The general process of such fuzz testing is as follows:…”

Section: Ads Testing Based On Violated Scenarios Searchmentioning

confidence: 99%

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TM-fuzzer: fuzzing autonomous driving systems through traffic management

Lin,

Chen,

et al. 2024

Preprint

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Simulation testing of Autonomous Driving Systems (ADS) is crucial for ensuring the safety of autonomous vehicles. Currently, scenarios searched by ADS simulation testing tools are less likely to expose ADS issues and highly similar. In this paper, we propose TM-fuzzer, a novel approach for searching ADS test scenarios, which utilizes real-time traffic management and diversity analysis to search security-critical and unique scenarios within the infinite scenario space. TM-fuzzer dynamically manages traffic flow by manipulating non-player characters near autonomous vehicle throughout the simulation process to enhance the efficiency of test scenarios. Additionally, the TM-fuzzer utilizes clustering analysis on vehicle trajectory graphs within scenarios to increase the diversity of test scenarios. Compared to the baseline, the TM-fuzzer identified 29 unique violated scenarios more than four times faster and enhanced the incidence of ADS-caused violations by 26.26%. Experiments suggest that the TM-fuzzer demonstrates improved efficiency and accuracy.

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Section: Ads Testing Based On Violated Scenarios Searchmentioning

confidence: 99%

“…DriveFuzz proposed by Kim et al (2022), is another search-based test differing from the aforementioned methods. Unlike previous tests, DriveFuzz's scenarios are set in a complete small-town map, providing a more realistic and diverse environment.…”

Section: Search-based Testingmentioning

confidence: 99%

TM-fuzzer: fuzzing autonomous driving systems through traffic management

Lin,

Chen,

et al. 2024

Preprint

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“…R3: Reaching Destination. Following existing works [23,27], reaching the assigned destination is one of the most important requirements for an ADS. The violation of reaching the destination is not expected and should be forbidden.…”

Section: Specifications For Adssmentioning

confidence: 99%

BehAVExplor: Behavior Diversity Guided Testing for Autonomous Driving Systems

Cheng

Zhou

Xie

2023

Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis

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Testing Autonomous Driving Systems (ADSs) is a critical task for ensuring the reliability and safety of autonomous vehicles. Existing methods mainly focus on searching for safety violations while the diversity of the generated test cases is ignored, which may generate many redundant test cases and failures. Such redundant failures can reduce testing performance and increase failure analysis costs.In this paper, we present a novel behavior-guided fuzzing technique (BehAVExplor) to explore the different behaviors of the ego vehicle (i.e., the vehicle controlled by the ADS under test) and detect diverse violations. Specifically, we design an efficient unsupervised model, called BehaviorMiner, to characterize the behavior of the ego vehicle. BehaviorMiner extracts the temporal features from the given scenarios and performs a clustering-based abstraction to group behaviors with similar features into abstract states. A new test case will be added to the seed corpus if it triggers new behaviors (e.g., cover new abstract states). Due to the potential conflict between the behavior diversity and the general violation feedback, we further propose an energy mechanism to guide the seed selection and the mutation. The energy of a seed quantifies how good it is. We evaluated BehAVExplor on Apollo, an industrial-level ADS, and LGSVL simulation environment. Empirical evaluation results show that BehAVExplor can effectively find more diverse violations than the state-of-the-art. CCS CONCEPTS• Software and its engineering → Software testing and debugging.

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“…For example, a random approach might select a role, a drone and its configuration, a mission, a sequence of HITs and their preconditions, and an associated interaction device. While random fuzzing can provide coverage of a large problem space, it can be inefficient at targeting specific problem scenarios [27,31,36]. Scenario-driven fuzz testing addresses this challenge by directing resources to explore known problem areas in greater detail.…”

Section: Test Fuzzermentioning

confidence: 99%

Reconstruction of Aleppo, Syria: A Design Studio at the University of Notre Dame, Usa

CHAMBERS

2022

Islamic Heritage Architecture IV

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As we think about how to rebuild communities that have suffered destruction, it is imperative to discuss the recovery of architecture and culture. As the world of architectural education trends towards teaching the design of buildings that create "placelessness", we must teach students to look deeply at history, to synthesize its lessons, and apply them sensitively and appropriately. Aleppo in Syria has a rich heritage of Islamic architecture that spans millennia. While the destruction of Aleppo has left a scar in the hearts of its people, it is possible to rebuild using the lessons and forms of traditional architecture. At the University of Notre Dame, our current studio of fourth year students is studying and proposing how a neighborhood in the historic city center might begin to be rebuilt. This studio is a teaching tool that allows students to engage with a culture that is foreign to them; to see and apply universal principles adapted for climate, culture, and building technologies that have been honed locally over thousands of years. The core of the studio is analysis of traditional Syrian architecture, looking at how the architecture supports the community and engages with the unique climate. The students study how traditional building technologies, like dome and vault construction, support the functions housed within these forms. They delve into the distinguished history of craft as they study architectural ornament. All these lessons are ultimately applied to a building project, which they program, conceptually develop, and design at the scales of the urban, building, and detail. These students, while they may be practicing far away from Aleppo, are preserving the heritage of a place that has seen so much destruction. Their work is a testament to the power of design in recovering the memory of a city.

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DriveFuzz

Cited by 26 publications

References 39 publications

TM-fuzzer: fuzzing autonomous driving systems through traffic management

TM-fuzzer: fuzzing autonomous driving systems through traffic management

BehAVExplor: Behavior Diversity Guided Testing for Autonomous Driving Systems

Reconstruction of Aleppo, Syria: A Design Studio at the University of Notre Dame, Usa

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