Projektdetaljer
Beskrivelse
The purpose of this project is to develop, validate and demonstrate the DRIVER COACH advanced supporting system in actual operating environments through state-of-the-art AI algorithms. The DRIVER COACH system is an intelligent driver management system, which nudges the driver towards efficient driving styles and is the drivers ever present helper in achieving and maintaining optimal driving behavior. The system gets to know each driver and adapts intelligently to continuously predict and resolve individual driving style inefficiencies by analyzing large-scale driving-behavior datasets.
The DRIVER COACH system will apply innovative advanced technology to deliver superior fuel efficiency above and beyond the current state-of-the-art. This is achieved by the real-time continuous nudging of drivers towards best-practice performance in driving style through novel machine learning/deep learning prediction and optimization algorithms. The new DRIVER COACH operating model includes an AI supported analysis of the style of the individual driver and exploits infrastructure GIS mapping to predict immediately upcoming infrastructure elements that offer fuel saving opportunities for any driver on any route.
In conclusion, this system is expected to deliver further increase of energy efficiency above what is currently achieved in the passenger and light goods transport sectors. The system further supports quicker and more effective best practice implementation for new drivers or drivers that switch from traditional vehicles to electric vehicles.
The DRIVER COACH system will apply innovative advanced technology to deliver superior fuel efficiency above and beyond the current state-of-the-art. This is achieved by the real-time continuous nudging of drivers towards best-practice performance in driving style through novel machine learning/deep learning prediction and optimization algorithms. The new DRIVER COACH operating model includes an AI supported analysis of the style of the individual driver and exploits infrastructure GIS mapping to predict immediately upcoming infrastructure elements that offer fuel saving opportunities for any driver on any route.
In conclusion, this system is expected to deliver further increase of energy efficiency above what is currently achieved in the passenger and light goods transport sectors. The system further supports quicker and more effective best practice implementation for new drivers or drivers that switch from traditional vehicles to electric vehicles.
Status | Igangværende |
---|---|
Effektiv start/slut dato | 01/02/2022 → 31/01/2025 |
Samarbejdspartnere
- SKANTECH ApS (Projektpartner) (leder)
- Ucplus A/S (Projektpartner)
- A CLOSE SHAVE ApS (Projektpartner)
- Arriva Danmark A/S (Projektpartner)
- KEOLIS DANMARK A/S (Projektpartner)
- Postnord Logistics A/S (Projektpartner)
- SDU Center for Energy Informatics
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