Falls are responsible for a large proportion of serious injuries and deaths among cyclists [1-4]. A common fall scenario is loss of balance during an emergency braking maneuver to avoid another vehicle [5-7]. Automated Vehicles (AV) have the potential to prevent these critical scenarios between bicycle and cars. However, current Threat Assessment Algorithms (TAA) used by AVs only consider collision avoidance to decide upon safe gaps and decelerations when interacting wih cyclists and do not consider bicycle specific balance-related constraints. To date, no studies have addressed this risk of falls in safety critical scenarios. Yet, given the bicycle dynamics, we hypothesized that the existing TAA may be inaccurate in predicting the threat of cyclist falls and misclassify unsafe interactions. To test this hypothesis, this study developed a simple Newtonian mechanics-based model that calculates the performance of two existing TAAs in four critical scenarios with two road conditions. Tue four scenarios are: (1) a crossing scenario and a bicycle following lead car scenario in which the car either (2) suddenly braked, (3) halted or (4) accelerated from standstill. These scenarios have been identified by bicycle-car conflict studies as common scenarios where the car driver elicits an emergency braking response of the cyclist [8-11] and are illustrated in Figure 1. The two TAAs are Time-to-Collision (TTC) and Headway (H). These TAAs are commonly used by AVs in the four critical scenarios that will be modelled. The two road conditions are a flat dry road and also a downhill wet road, which serves as a worst-case condition for loss of balance during emergency braking [12].

Gleichgewichtsstörungen und Stürze gehören zu den wichtigsten Symptomen der Parkinson Krankheit (PD). Bei jungen PD-Patienten werden diese Probleme durch Nebenwirkungen der Medikation zusätzlich verstärkt. Aufgrund des noch sehr limitierten Verständnisses der zugrunde liegenden Mechanismen, die zum erhöhten Sturzrisiko bei jungen PD-Patienten beitragen, mangelt es derzeit an alternativen und effektiven bewegungsbasierten Therapien, um diese Sturzgefahr zu verringern. Diese Arbeit zielt darauf ab, solche Mechanismen zu identifizieren und eine effektive Methode zur Früherkennung des Sturzrisikos bei jungen PD-Patienten zu entwickeln. Es wurde der Beitrag der zentralen und peripheren neuromuskulären sowie sensomotorischen Fähigkeiten, dynamischen Stabilitätskontrolle und Anpassungsfähigkeit der Fortbewegung auf die Sturzrate junger PD-Patienten mittels eines Vergleichs zwischen gesunden Probanden und jungen PD-Patienten mit und ohne Sturzerfahrung (Fallers vs. Non-Fallers) untersucht. Der Vergleich zeigte, dass die PD-Fallers zentral begründete Defizite in der Muskelkraft ihrer Beinstrecker aufwiesen sowie eine verringerte Abfangleistung nach simulierten Vorwärtsstürzen. Die Parameter „Muskelkraft“ und „Annäherung an die vordere Stabilitätsgrenze“ identifizieren gemeinsam 90% der Fälle junger PD-Faller. PD-Patienten zeigten auch eine uneingeschränkte prädiktive Anpassungsfähigkeit auf Gangstörungen, aber ein weniger stabiles Gangmuster und weniger effektive reaktive Antworten auf wiederholte Gangstörungen im Vergleich zu Kontrollpersonen. Diese Arbeit stellt relevante Informationen dar, die für die Entwicklung von alternativen nicht-medikamentösen Therapien zur Reduzierung des Sturzrisikos bei jungen PD-Patienten nützlich sind. Darüber hinaus wurde eine akkurate Methode zur Früherkennung von jungen PD-Patienten mit einem erhöhen Sturzrisiko erarbeitet. Diese Patienten könnten von Training der Beinstrecker und der dynamischen Stabilität profitieren. / Postural instability and falls are some of the main symptoms associated with the Parkinson`s disease (PD). In early-onset patients (diagnosed before the age of 51) these problems are worsened by medication-related side-effects. There is a lack of effective exercise-based training interventions to reduce the risk of falling due to our limited understanding of the underlying mechanisms contributing to falls in early-onset PD. The present thesis aims to identify those mechanisms responsible for falls and to develop a sensitive method of assessment for the early discrimination of patients at risk of falling in early-onset PD. We investigated the contribution of central and peripheral neuromuscular and sensory-motor capacities, dynamic stability control and locomotor adaptability to the increased risk of falling in young PD patients by means of comparing healthy controls and early-onset PD fallers and non-fallers. The comparison revealed that PD fallers have central originated deficits in leg extensors` muscle strength - evidenced by increased antagonistic moments and activation deficit of the agonists - and a reduced increase of the base of support in response to simulated forward falls, both resulting in decreased recovery performance. The factors “muscle strength” and “approach to the anterior limit of stability” together could correctly classify 90% of the PD fallers. In addition, while young PD patients showed unaltered predictive adaptability to gait perturbations, they exhibited less stable gait patterns and less effective reactive responses to repeated gait perturbations compared to controls. This thesis provides relevant information for the development of alternative non-medication based therapies aiming to reduce falls in early-onset PD and an accurate assessment tool for the early identification of young patients at a high risk of falling. These patients may benefit from leg-extensors'' strengthening and dynamic stability training.