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 ...

Coordination and Optimization Control Framework for Vessels Platooning in Inland Waterborne Transportation System

Vessels sailing in a single platoon could reduce resistance from the perspective of the whole platoon and the individual vessel, and contribute to improving energy benefits. Moreover, transportation energy costs and traffic efficiency are essential indicators for measuring waterborne transportation systems. We attempt to minimize...

Bicycle balance assist system reduces roll and steering motion for young and older bicyclists during real-life safety challenges

Bicycles are more difficult to control at low speeds due to the vehicle’s unstable low-speed dynamics. This issue might be exacerbated by factors such as aging, disturbances, and multi-tasking. To address this issue, we developed a prototype ‘balance assist system’ with Royal Dutch Gazelle and Bosch eBike Systems at Delft University of...

Improving safety in Dutch construction projects: An exploratory research on improving safety in the Dutch construction industry: incorporating a third party into the UAC-IC 2005, based on FIDIC’s Engineer

Any industry is focusing on creating an environment that is as safe as possible for everyone that is involved. This is no different for the construction industry. However, the construction industry is placed second in the ranking of most dangerous industries. The Dutch Safety Board, being an independent administrative body, has recommended to...

Hierarchical Model Predictive Control for on-Line High-Speed Railway Delay Management and Train Control in a Dynamic Operations Environment

In practice, the operation of high-speed trains is often affected by adverse weather conditions or equipment failures, which result in delays and even cancellations of train services. In this article, a novel two-layer hierarchical model predictive control (MPC) model is proposed for on-line high-speed railway delay management and train...

Barrier Function-based Safe Reinforcement Learning for Formation Control of Mobile Robots

Distributed model predictive control (DMPC) concerns how to online control multiple robotic systems with constraints effectively. However, the nonlinearity, nonconvexity, and strong interconnections of dynamic system models and constraints can make the real-time and real-world DMPC implementations nontrivial. Reinforcement learning (RL)...

Scenario-Based Trajectory Optimization in Uncertain Dynamic Environments

We present an optimization-based method to plan the motion of an autonomous robot under the uncertainties associated with dynamic obstacles, such as humans. Our method bounds the marginal risk of collisions at each point in time by incorporating chance constraints into the planning problem. This problem is not suitable for online optimization...

Risk Quantification for Automated Driving Systems in Real-World Driving Scenarios

The development of safety validation methods is essential for the safe deployment and operation of Automated Driving Systems (ADSs). One of the goals of safety validation is to prospectively evaluate the risk of an ADS dealing with real-world traffic. ISO 26262 and ISO/DIS 21448, the leading standards in automotive safety, provide an approach...

Quadrotor Fault Tolerant Flight Control and Aerodynamic Model Identification

As Multi-rotor Unmanned Aerial Vehicles, or drones, are gradually becoming more popular in civilian applications, the safety of these flying machines becomes a significant concern. Such drones are powered by multiple rotors to generate lift and control torques. Hence, the failure of rotors can severely threaten their flying safety. Direct...

Safe Reinforcement Learning Applications

Reinforcement Learning (RL) focuses on maximizing the returns (discounted rewards) throughout the episodes, one of the main challenges when using it is that it is inadequate for safety-critical tasks due to the possibility of transitioning into critical states while exploring. Safe Reinforcement Learning (SafeRL) is a subset of RL that focuses...

20th International Symposium on Aviation Psychology (ISAP 2019)

The International Symposium on Aviation Psychology is convened for the purposes of: presenting the latest research on human performance problems and opportunities within aviation systems; envisioning design solutions that best utilize human capabilities for creating safe and efficient aviation systems; and bringing together scientists, research...

Application of critical controls for fatality prevention in mining operations: Case study in an AngloGold Ashanti gold mine

Up until now, global mining companies have failed to create a fatality free environment for their employees, whether it be through increasingly difficult conditions or inadequate safety management approaches. Desiring to maintain the social license to operate, these companies are now looking into alternate ways of safety management with the aim...

Design of a software architecture supporting business-to-government information sharing to improve public safety and security: Combining business rules, Events and blockchain technology

Toensurepublicsafetyandsecurity,itisvitallyimportantforgovernmentstocol- lect information from businesses and analyse it. Such information can be used to determine whether transported goods might be suspicious and therefore require physical inspection. Although businesses are obliged to report some information, they are reluctant to share addi-...

Safe nonlinear trajectory generation for parallel autonomy with a dynamic vehicle model

High-end vehicles are already equipped with safety systems, such as assistive braking and automatic lane following, enhancing vehicle safety. Yet, these current solutions can only help in low-complexity driving situations. In this paper, we introduce a parallel autonomy, or shared control, framework that computes safe trajectories for an...

Agent-Based Modelling and Simulation of Safety and Resilience in Air Transportation

Purpose: In order to improve the safety, capacity, economy, and sustainability of air transportation, revolutionary changes are required. These changes might range from the introduction of new technology and operational procedures to unprecedented roles of human operators and the way they interact. Implementing such changes can introduce both...