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AOSP VHAL: Evaluation Table of Use Cases
Thanks to Stefan and the team involved for providing a description of the Insurance Use Cases!
ToDo Sabine: Integrate Insurance Use Cases in the Table, High-Level Summary of arguments so far.
Next Steps:
fill the table,
extract the OEM argumentary
present to COVESA Board
aim: start a PoC with two use cases in February, might be a good idea to do it in an (online) workshop.
In-car app to live understand driving behaviour and risks | Save costs: | Easier/better way to sell usage based/customised insurance contracts. | Better (risk adjusted, fair, comprehensible) insurance tarif for better driving behaviour. | 1:1 contracts / legal stuff | knowledge reasoning group | Stefan Sellschopp, Allianz; | ||
| Argument 1: Serve the fragmented market for a lot of insurance companies / regions (without OEM proprietary implementations). Save development cost and complexity | Data as of today are collected from a phone → collection moved to the car which is to be insured, less efforts for the 3rd party if done directly from the car. Servier based integration has proven costly and complex (first OEM integration 2016, twas multi year project) still overly complex and heterogenous data is key problem | & user permissions / transparency | DEG architecture & infrastructure (Stephen, Renesas) |
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| Understanding of risks and liabilities involved in insurance cases. |
| & Terms and Conditions |
| OEMs? | ||
| Argument 2: Lead generation possible- create/enable risk score and provide opportunitiy to sell insurance (retail market); sale of crash/claims data to insurers- create revenue/commissions | OEM fragmentation leading to different implementations, which until now are often cost prohibitive. | Driving style, km driven, location, time of day, braking, speed, acceleration | all depending on the region | MDS (mobility data space) proposed to create a UBI minimum set of data - this could be a COVESA profile from VSS |
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| Total Cost of Ownership reduction: |
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| Crash detection, part of emergencyy assistance discussion |
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| low insurance fees is a "feature" of the vehicles OEMs want to sell. |
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| ADAS insurance use cases | Argument 1: Serve the fragmented market for a lot of insurance companies / regions (without OEM proprietary implementations). Save development cost and complexity | ability to provide ADAS based risk evaluation to customer | Better (risk adjusted, fair, comprehensible) insurance tarif for better driving behaviour, for using ADAS systems. | in addition to UBI: availability, activation, interaction of ADAS systems | as above | as above |
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Use Case | Description | Benefit for OEM | Benefit for 3rd party | Benefit for end customer | Properties needed | Further needs | adjacent COVESA activities | Volunteers to |
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In-car app to live understand driving behaviour and risks
ADAS use cases | Save costs: TBD business involved Total Cost of Ownership: | Easier way to sell usage based/customised insurance contracts. Data as of today are collected from a phone → moved to the car which is to be insured, less efforts for the 3rd party if done directly from the car. Understanding of risks and liabilities involved in insurance cases. OEM fragmentation leading to different implementations.
| Better insurance tarif for better driving behaviour, for using ADAS systems. | 1:1 contracts / legal stuff & user permissions / transparency & Terms and Conditions all depending on the region |
| Stefan Sellschopp, Allianz; | ||
Rental cars, trucks, etc. |
| Notification of service for Fleet Managers Vehicle Health Status for Fleet managers Service Need Details |
| android.location perf_odometer tire_pressure EV_battery_level, EV_current_battery_capacity Fuel_level etc.
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| involve Geotab? |
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see also |
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| Connected Safety discussions, BOF, Tim VanGoethem - ESS Emergency Safety Solutions
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