Automated segmentation and activity identification for intelligent vehicular systems

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Vehicular transportation is a key linchpin of modern infrastructure and the modern economy. Improving our understanding of driver behaviour and situational awareness in traffic conditions can lead to improvements in driver safety, fuel usage and decrease costs. Current systems for analysis of driving behaviour rely on custom in-vehicle sensing systems, which limit the scope to a small subset of vehicles. The aim of this proposal is to develop algorithms for driver behaviour analysis using both on-board and mobile sensors such as smartphones. The proposal would develop algorithms for both off-line and on-line segmentation and identification of driving behaviour from mobile device data. Off-line analysis can be employed for applications such as usage-based insurance, driver training and fleet intelligence. On-line analysis would open new possibilities for interaction with the user, providing a more intuitive and convenient interface, and enabling immediate and interactive feedback.