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The Multi-Area Connected Automated Mobility (MACAM) project is a collaborative initiative. It encompasses a multi-city, multi-operator, and multi-purpose self-driving trial.
GILL will be implemented through an iterative co-creation approach structured on a four-phases cycle - understand, co-design, implement, evaluate - repeated twice to incorporate the feedbacks and evaluation results in fine-tuned and validated results.
TInnGO, the Transport Research Observatory, is a pan European observatory for gender smart transport innovation, that provides a nexus for data collection, analysis, dissemination of gender mainstreaming tools and open innovation, encouraging smart mobility.
Our PACE-AI method is only using vehicle shape and pedestrian anthropometry. It can extract, in seconds, not only the vehicle impact speed (which takes the Police days), but also the pedestrian crossing speed, gait and crossing direction (impossible using Searle).
The goal of SIMUSAFE following the FESTA-V model methodology is to develop realistic multi-agent behavioural models in a transit environment where researchers will be able to monitor and introduce changes in every aspect, gathering data not available in real world conditions.
The objective of the REACTOR project is to develop and evaluate a suite of technologies in support of reduced cockpit workload and improved situational awareness.
This explored the use of augmented reality in the context of manufacturing assembly workers required to conduct complex product assemblies (such as high performance battery packs for electric vehicles) with increased efficiency.
This research investigates the cyber security, human factors and trust aspects of screen failures during automated driving.
IFTC’s role in MFM supports future CAV testbed trials by developing guidance and case studies to assist users with test definition and planning.