Automated urban train control with hybrid EventB: xe2x80x98Tacklingxe2x80x99 the rugby club problem Abstract   Normally, the passengers on urban rail systems remain fairly stationary, allowing for a relatively straightforward approach to controlling the dynamics of the system, based on the total rest mass of the train and passengers. However, when a mischievous rugby club board an empty train and then run and jumpstop during the braking process, they can disrupt the automatic mechanisms for aligning train and platform doors. This is the Rugby Club Problem for automated urban train control. A simple scenario of this kind is modelled in Hybrid EventB, and sufficient conditions are derived for the prevention of the overshoot caused by the jumpstop. The challenges of making the model more realistic are discussed, and a strategy for dealing with the Rugby Club Problem, when it cannot be prevented, is contemplated.

Pedestrian Collision Avoidance System for Scenarios with Occlusions Safe autonomous driving in urban areas requires robust algorithms to avoid collisions with other traffic participants with limited perception ability. Current deployed approaches relying on Autonomous Emergency Braking (AEB) systems are often overly conservative. In this work, we formulate the problem as a partially observable Markov decision process (POMDP), to derive a policy robust to uncertainty in the pedestrian location. We investigate how to integrate such a policy with an AEB system that operates only when a collision is unavoidable. In addition, we propose a rigorous evaluation methodology on a set of well defined scenarios. We show that combining the two approaches provides a robust autonomous braking system that reduces unnecessary braking caused by using the AEB system on its own.