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Commercial Vehicle Birds of a Feather

A standards-based approach to vehicle fleet telematics data to build a modern transportation ecosystem for all stakeholders.

Ted Guild, Geotab

Thomas Spreckley, ETAS

August 2023

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BoF Kickoff Agenda

The context:

why commercial customers need consistent data to manage their vehicle fleets

The approach:

An agreed “best practices” recommendation to be applied by the ecosystem

The benefits:

Value added products, reduced integration efforts, value for all stakeholders

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Commercial Fleets Run on Data

As data drives their businesses, they have come to rely on and will increasingly require reliable, secure, high quality information platforms

Productivity

Customer service times
Identify unexpected stops
Accurate arrival and departure times
Optimized routes
Reduce time waste and inefficiencies

Optimization

Manage vehicle maintenance
Proactively detect electrical and other issues
Advanced diagnostic data

Safety

Collision notifications
Driver risk management
In-vehicle coaching
Track speeding
Seat belt use
Driving in reverse

Sustainability

Increase fuel efficiency. Decrease Idle
Track CO2 emissions
Fleet electrification
EV performance monitoring and reporting

Compliance

Electronic driver logs
Tax reporting
Vehicle inspection reports DVIR

Expandability

E.g.
Winter operations
Cold chain
Video
…

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The Issue: OEM data currently not suited for all use cases and different across OEMs

To make best possible use of the OEM data, it has to match the data (in quantity and quality) generated by aftermarket devices (including bi-directional communication!)

Safety

Productivity

Fleet Optimization

Compliance

Sustainability

Available Data Points per OEM

Available Rules & Reports per OEM

Data Parity w/ GO

OEM A

OEM B

OEM C

OEM D

OEM A

OEM B

OEM C

OEM D

*Note: percentages not current, analysis as of 2022

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Today: Not leveraging the value of data, but creating complexity with integration efforts

Different types, makes, model, years - and data

OEM

Telematics Service Provider

Fleet Owner

ExVeh

LeaseCos

Insurance

Traffic Infrastructure

Smart cities

Charging Providers

...

Multiple OEM and TSP clouds

Multiple data users

x

TSPs

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Result: enormous efforts to integrate and maintain OEM APIs - not value adding for customers

# of data points / sampling rate

increase “market potential”

increase “product value”

# of integrated OEMs

Target state:

all required data points from all OEMs available

Integration effort #4:

Normalization / Harmonization

Integration effort #3:

Maintenance of integrated APIs

Integration effort #2:

# of different APIs

Integration effort #1:

Data fidelity/quality

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In 2016, McKinsey Report predicted $750 Billion/year revenue for Telematics by 2030

Data monetization: The missed gold rush of the software-defined vehicle

Offered services were not interesting enough to the customer because user experience was tedious. Applied remedy: bundle telematics into vehicle sales
Despite numerous reorgs most OEMs have not restructured their business for information revenue streams
Solutions are one-offs. Scaling across partners or better across OEMs is not established leading to fragmented solutions.

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TS

Commercial fleets rely on advanced fleet management systems powered by high-quality vehicle data to improve fleet safety, sustainability and innovation. As fleets increasingly depend on software, data analytics and AI, the need for reliable data will only grow. While telematics provider have been providing quality data to fleets for many years, there is now a transition towards utilizing OEM-enabled data in the cloud. Geotab has considerable experience with operational collection and practical use for vehicle data and is willing to provide insights to OEMS and facilitate reliable data access.

These recommendations come from our experience querying in-vehicle data signals with an aftermarket device (GO), pre-processing the data using the curve algorithm, and securely transporting the minimum set of data that still aptly describes the underlying vehicle attributes

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Complexity reduction by using standards for non-differentiating and non-competitive tasks

TSP

Different vehicle makes and models in one fleet

For a seamless and value-adding product offering in an ecosystem, interfaces between parties should be frictionless and interoperable based on agreed standards and best practises

Multi-make fleet connectivity solutions

Integration complexity

Fleet Customer

OEM

Fleet connectivity ecosystem

new revenue stream for OEMs
Develop and integrate embedded TCU (OEM competency)
ensure car IT security

Use vehicle data and analytics to manage fleet across multiple brands - in one system
make use of embedded TCU

minimize integration effort
make use of embedded TCU
Data parity with aftermarket device
Bi-directional communication for new use cases

✓

╳

✓

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“Agreed best practice” approach enables revenue generation, innovation and customer satisfaction

OEM & Supplier

Fleet Customer

TSP

collect and provide the right data for their customers’ needs, more efficiently (lower bandwidth and cloud storage)
Safeguard future vehicle sales (customers demand data)
lower product development and integration costs with standardized solutions

get access to similar data / frequency across brands
improve their productivity, safety, sustainability, regulatory compliance and grow their business
Interoperability with other systems, beyond Fleet Telematics (e.g. ins, roadside assistance, fuel card, …)

more pertinent insights and services for (the whole) fleet with the right data
Less investment in API integration
New product creation based on easy shareable data
Easier support leads to better customer experience

easier for any prospective partner to join the ecosystem and to integrate with and consume data - robust data marketplace for all parties

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5 elements of the initial “recommendations”

Sampling Methodology

Fleet Operational Data

Data Model

Validation

Use Cases

Curve logging (maximum error) vs fixed time

Modest set of specific vehicle signals and attributes including importance and preferred units

COVESA / W3C Vehicle Signal Specification (VSS)

Support customers by ensuring that fleet data requirements can be met with certain vehicles

Productivity, Optimization, Safety, Sustainability, Compliance, Expandability

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Why Sampling Methodology is relevant

Typically OEMs provides fixed interval (time or distance), event or both
More data not necessarily better (e.g. GPS @1 sec) - relevant data is needed
Curve logic provides intelligent lossy compression, open sourced under MPL
Produces a better representation and is more efficient (lower cost)

Sampling Methodology

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TG

Commercial fleets rely on advanced fleet management systems powered by high-quality vehicle data to improve fleet safety, sustainability and innovation. As fleets increasingly depend on software, data analytics and AI, the need for reliable data will only grow. While telematics provider have been providing quality data to fleets for many years, there is now a transition towards utilizing OEM-enabled data in the cloud. Geotab has considerable experience with operational collection and practical use for vehicle data and is willing to provide insights to OEMS and facilitate reliable data access.

These recommendations come from our experience querying in-vehicle data signals with an aftermarket device (GO), pre-processing the data using the curve algorithm, and securely transporting the minimum set of data that still aptly describes the underlying vehicle attributes

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Example: U-Turn Detection

GO Device detected a u-turn

15:09:21

15:09:08

15:09:17

15:09:26

15:09:39

15:09:06

15:09:37

15:09:06

15:09:37

The OEM data for the same vehicle logs 2 GPS records (approx 30 seconds apart)

Our algorithm would be able to detect a u-turn based on these GPS records

But the u-turn detected by Geotab on Go device indicates the u-turn was taken at the intersection

While the OEM data misses the context because of unavailability of data for 30 seconds

15:09:06

15:09:37

15:09:17

15:09:26

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Sampling Methodology

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Animation - view in presentation mode

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How Curve logging works

Patented method of moving data efficiently from vehicle to server
Key value-add: Data is analyzed on the server rather than algorithms in the device

More Info: �How it works (blog post)

Whiteboard video with Neil Cawse

Curve Logging @ COVESA

Curve // Github

Sampling Methodology

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Curve logging can be implemented by OEMs on their embedded TCUs

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Most needed Data Points, ~80 to start with

Fleet Operational Data

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Source: Fleet Management Data Set, including Use Cases, frequency and Importance

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Proposal to use COVESA Vehicle Signal Specification (VSS)

Data Model

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The Vehicle Signal Specification (VSS) is an initiative by COVESA to define a syntax and a catalog for vehicle signals. In short this means that VSS introduces:

A syntax for defining vehicle signals in a structured manner.
A catalog of signals related to vehicles.

It focuses on vehicle signals, in the sense of classical attributes, sensors and actuators with the raw data communicated over vehicle buses

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Representing sampling campaigns in VSS

Data Model

3

A proposed initial deliverable will be to produce recommended signals, leveraging overlays, in VSS with sampling guidelines. Easy to use as configuration or generate code from.

Example signal in YAML:

Vehicle.LowVoltageBattery.CurrentVoltage:

datatype: float

description: Current Voltage of the low voltage battery.

type: sensor

unit: V

audiences: FLEET,SERVICE

purpose: MAINTENANCE_07

collection: 0.033HZ

categories: MAINTENANCE,PRODUCTIVITY

importance: MUST

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Fleet Customers benefits from recommendations

Data consistency - enables vehicle integration across vehicle manufacturers

Simplified integration and analysis - unified data structure enables scalability for fleets to easily change and expand type and number of vehicles.

Interoperability & vendor independence - freedom to choose best in class vehicles, software/cloud platform, telematics services and analytics

Scalability - future proofing their business

Collaborative industry-wide standardization - enable better decision making, improved efficiency, better able to adapt to evolving industry trends

Pay for product value, not technology integration

✓

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Benefits for OEM and Supplier

Create additional, continuous revenue streams

Be fleet ready and meet customer requirements - Provide the needed information for fleet management

Lower cost (bandwidth, cloud storage) by being more efficient in data collection and storage

Conventions applicable to other industry verticals (insurance, maintenance, regulatory compliance) - future growth and returns on investment

Standards and consistency reduces vendor lock-in as well as supplier and solution provider integration costs

Vehicles as information platforms will drive future vehicle sales

✓

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Ecosystem Benefits from these recommendations

Creates a vibrant data ecosystem and lowers entry hurdles / increases competition

Fosters innovation by allowing TSPs to allocate more resources to product creation

Building a sustainable transportation future based on data

Interoperability in the ecosystem avoids vendor lock-in

Safeguarding vehicle security by making expert knowledge available for all participants

Increasing competition creates customer value

✓

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More to come…

Other verticals

processes

Remote functions

TSP software on OEM hardware

Harmonized VIN eligibility and vehicles activation APIs + consent management

E.g. door lock / unlock, immobilizer, preheating, remote charging, charging presets, remote reset of headunit ..

common/standardized API (e.g. COVESA + AutoSAR effort)

These conventions can be applied to other vertical industries’ data interests: insurance, ev charging, maintenance, regulatory compliance...

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What can you do now? �

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Inform yourself

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Contribute and provide feedback

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Implement and endorse recommended best practice

Commercial Vehicle BoF Charter

OEM enabled Fleet Management Data Recommendations - defined set of specific vehicle signals

Eclipse Fleet-Management blueprint

COVESA Commercial Vehicle Birds of a Feather (BoF)

Join (attend the regular meetings), refine scope, provide input, contribute, join plugfests & SDV hackathons

Direct interested colleagues towards this effort

Reach out to ETAS and Geotab if you are looking for support and experience in implementing “best practices” or curve algorithm on your TCU.

Fleet operators can encourage OEM and others to adopt through their procurement process