Safety-enhanced autonomous driving using interpretable sensor fusion transformer
Large-scale deployment of autonomous vehicles has been continually delayed due to safety
concerns. On the one hand, comprehensive scene understanding is indispensable, a lack of …
concerns. On the one hand, comprehensive scene understanding is indispensable, a lack of …
Safe driving via expert guided policy optimization
When learning common skills like driving, beginners usually have domain experts standing
by to ensure the safety of the learning process. We formulate such learning scheme under …
by to ensure the safety of the learning process. We formulate such learning scheme under …
Advsim: Generating safety-critical scenarios for self-driving vehicles
As self-driving systems become better, simulating scenarios where the autonomy stack may
fail becomes more important. Traditionally, those scenarios are generated for a few scenes …
fail becomes more important. Traditionally, those scenarios are generated for a few scenes …
A survey on safety-critical driving scenario generation—A methodological perspective
Autonomous driving systems have witnessed significant development during the past years
thanks to the advance in machine learning-enabled sensing and decision-making …
thanks to the advance in machine learning-enabled sensing and decision-making …
Safe real-world autonomous driving by learning to predict and plan with a mixture of experts
The goal of autonomous vehicles is to navigate public roads safely and comfortably. To
enforce safety, traditional planning approaches rely on handcrafted rules to generate …
enforce safety, traditional planning approaches rely on handcrafted rules to generate …
Development methodologies for safety critical machine learning applications in the automotive domain: A survey
Enabled by recent advances in the field of machine learning, the automotive industry pushes
towards automated driving. The development of traditional safety-critical automotive …
towards automated driving. The development of traditional safety-critical automotive …
Safebench: A benchmarking platform for safety evaluation of autonomous vehicles
As shown by recent studies, machine intelligence-enabled systems are vulnerable to test
cases resulting from either adversarial manipulation or natural distribution shifts. This has …
cases resulting from either adversarial manipulation or natural distribution shifts. This has …
Dense reinforcement learning for safety validation of autonomous vehicles
One critical bottleneck that impedes the development and deployment of autonomous
vehicles is the prohibitively high economic and time costs required to validate their safety in …
vehicles is the prohibitively high economic and time costs required to validate their safety in …
Toward trustworthy decision-making for autonomous vehicles: A robust reinforcement learning approach with safety guarantees
While autonomous vehicles are vital components of intelligent transportation systems,
ensuring the trustworthiness of decision-making remains a substantial challenge in realizing …
ensuring the trustworthiness of decision-making remains a substantial challenge in realizing …
Can you trust your autonomous car? interpretable and verifiably safe reinforcement learning
Safe and efficient behavior are the key guiding principles for autonomous vehicles. Manually
designed rule-based systems need to act very conservatively to ensure a safe operation …
designed rule-based systems need to act very conservatively to ensure a safe operation …