This paper describes the current version of the Low Adhesion Braking Dynamic Optimisation for Rolling Stock (LABRADOR) simulation tool that can predict the train brake system performance and support decision-making in the design and optimisation of the braking system including wheel slide protection, sanders and the blending and control of friction and dynamic brakes in low adhesion conditions. The model has been developed in MATLAB/Simulink and is intended to mimic the braking performance of both older and newer generations of multiple unit passenger trains. LABRADOR models have been initially validated by comparing simulation results for a single car train (Class 153) and two-car train (Class 158) in dry conditions with experimental tests, for tare and crush laden vehicles. This project is supported by RSSB and a technical steering group composed of railway braking experts, suppliers and train operators and manufacturers.

Abstract-A real-time collision avoidance algorithm is developed based on parameterizing an optimal control problem with B-spline curves. The optimal control problem is formulated in output space rather than control or input space, this is feasible because of the differential flatness of the system for a fixed wing aircraft. The flat output trajectory is parameterized using a Bspline curve representation. In order to reduce the computational time of the optimal problem, the aircraft and obstacle constraints are augmented in the cost function using a penalty function method. The developed algorithm has been simulated and tested in MATLAB/Simulink.

The operation of Unmanned Aerial Vehicles (UAVs) in civil airspace is restricted by the aviation authorities, which require full compliance with regulations that apply for manned aircraft. This paper proposes control algorithms for a collision avoidance system that can be used as an advisory system or a guidance system for UAVs that are flying in civil airspace under visual flight rules. A decision-making system for collision avoidance is developed based on the rules of the air. The proposed architecture of the decision-making system is engineered to be implementable in both manned aircraft and UAVs to perform different tasks ranging from collision detection to a safe avoidance manoeuvre initiation. Avoidance manoeuvres that are compliant with the rules of the air are proposed based on pilot suggestions for a subset of possible collision scenarios. The proposed avoidance manoeuvres are parameterized using a geometric approach. An optimal collision avoidance algorithm is developed for real-time local trajectory planning. Essentially, a finite-horizon optimal control problem is periodically solved in real-time hence updating the aircraft trajectory to avoid obstacles and track a predefined trajectory. The optimal control problem is formulated in output space, and parameterized by using B-splines. Then the optimal designed outputs are mapped into control inputs of the system by using the inverse dynamics of a fixed wing aircraft.

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This paper describes the current version of the LABRADOR simulation tool that can predict the train brake system performance and support decision-making in the design and optimisation of the braking system including WSP, sanders, and the blending and control of friction and dynamic brakes. The model has been developed in MATLAB/SIMULINK and is intended to mimic the braking performance of both older and newer generations of multiple unit passenger trains. It provides a quantitative simulation tool to test different designs and support the optimisation of the brake systems for contemporary and future trains.