G-Active Success Stories

Built a low-cost device to collect naturalistic driving data

Developed an adaptive driver model to represent real-world driver speed and acceleration choice

Provides a framework to trade-off driver preferences, fuel consumption and emissions reduction

Developed an intelligent air conditioning controller that saves 9% of A/C fuel usage (1-2% of vehicle fuel usage).

Novel heuristic control algorithms for hybrid vehicle energy management 2-4% more fuel efficient than state-of-the-art

Implementable solutions to intractable joint optimization of energy management and vehicle speed profiles

Developed a driver assistance system to recommend actions to a driver to assist eco-driving

Smart user-interface design using cognitive work analysis

System evaluated through extensive simulator testing at the University of Southampton

Novel approaches to prediction of traffic flow in real time from historical and V2X traffic data

Incorporation of traffic prediction into real-time optimisation of vehicle speed profiles