How Far Ahead Should Autonomous Vehicles Start Resolving Predicted Conflicts? Exploring Uncertainty-Based Safety-Efficiency Trade-Off

Resolving predicted conflicts is vital for safe and efficient autonomous vehicles (AV). In practice, vehicular motion prediction faces inherent uncertainty due to heterogeneous driving behaviours and environments. This spatial uncertainty increases non-linearly with prediction time horizons, leading AVs to perceive more road space occupied by...

Safe & Intelligent Control: Fault-tolerant Flight Control with Distributional and Hybrid Reinforcement Learning using DSAC and IDHP

The critical challenge for employing autonomous control systems in aircraft is ensuring robustness and safety. This study introduces an intelligent and fault-tolerant controller that merges two Reinforcement Learning (RL) algorithms in a hybrid approach: the Distributional Soft Actor-Critic (DSAC) and the Incremental Dual Heuristic Programming ...

Powered haulage safety, challenges, analysis, and solutions in the mining industry: a comprehensive review

Satisfying safety issues plays a critical role in mining operations. Although the use of emerging technology became a new trend in preventing powered haulage hazards in the mining industry, these technologies themselves posed new hazards to the problem that are necessary to be identified, assessed, and managed together with common hazards....

PEM: Perception Error Model for Virtual Testing of Autonomous Vehicles

Even though virtual testing of Autonomous Vehicles (AVs) has been well recognized as essential for safety assessment, AV simulators are still undergoing active development. One particular challenge is the problem of including the Sensing and Perception (S&P) subsystem into the virtual simulation loop in an efficient and effective manner....

Benchmarking Behavior Prediction Models in Gap Acceptance Scenarios

Autonomous vehicles currently suffer from a time-inefficient driving style caused by uncertainty about human behavior in traffic interactions. Accurate and reliable prediction models enabling more efficient trajectory planning could make autonomous vehicles more assertive in such interactions. However, the evaluation of such models is...

Reinforcement Learning for Switching Control of Semi-automated Vehicles with Driver Fatigue

Automated driving is a rapidly growing technology nowadays. Semi-automated driving is a subpart of automated driving which has multiple driving modes where both driver and automated module can take control. But full safety and comfort guarantees cannot still be given to the drivers. In this project, research has been done to ensure driver safety...

Safety of Automated Driving in Mixed-Traffic Urban Areas: Considering Vulnerable Road Users and Network Efficiency

The establishment of areas for safe automated driving in mixed-traffic settings is one major barrier in the development and adoption of Autonomous Vehicles (AVs). This work investigates safety in the interactions between AVs, human-driven vehicles, and vulnerable road users such as cyclists and pedestrians in a simulated urban environment in the...

Potential health and well-being implications of autonomous vehicles

Transportation's effects on health and well-being are widely recognized. In the near future, autonomous vehicles (AVs) are expected to revolutionize transportation options and ways of travel. Consequently, the effect of AVs on population health and well-being is a crucial topic of interest for transportation policymaking, one that has...

Exclusivity through Conduct: A vision for Mercedes-Benz private ownership in 2035

This master thesis was executed for Mercedes-Benz; a subsidiary of Daimler AG. Its goal was to design a holistic interior concept for level 4 premium autonomous driving, aimed at:‘’Purpose-driven people, expressing confidence in their success, who reluctantly accept novelty framed by tradition’’, using a context based design approach. In the...

Compositional and contract-based verification for autonomous driving on road networks

Recent advances in autonomous driving have raised the problem of safety<br/>to the forefront and incentivized research into establishing safety guarantees. In this paper, we propose a safety verification framework as a safety standard for driving controllers with full or shared autonomy based on compositional and contract-based principles. Our...