Blog: On the path towards autonomous vehicles

On the path towards autonomous vehicles

-Click for reading part II-

Most new web services are deployed from a Mobile First philosophy.

Everything is connected, everything is mobile, but where is everything?

Put a note in your calendar to remember something, not when, but where you are to do the thing.

Wireless communication is perfect for moveable objects. Yet, during the 20th century we connected things upside down: A heavy TV was needing mains supply, but was receiving airborne TV-signals via antenna. When someone called you on the phone, they called the place of the phone; a living room or the kitchen, but not a specific person, as the phone cord was tying the device to the wall outlet.

Today huge (flat) TV’s are on cable while phones are cordless and mobile. However, the increase in wireless bandwidth even allows TV viewed on the move – streaming via the ubiquitous internet connection. We bring everything along.

But from where and to where?

Positioning via GPS will – for every one of us having a pair of eyes – be adequate even though the accuracy is often not better than 8-10 meter off the target coordinate. Such accuracy is not sufficient to determine whether you walk on the pavement or on the street, or if a car is occupying the right or left lane.

And further, if physical objects obstruct the signal, you are lost. For cars driving through high rise urban areas, in tunnels, or navigating between several decks in a parking house, this means loss of navigational capabilities; how to find out again?

Next step is self-driving vehicles

As devices now mostly know where they are, the next logical step is ensuring moveable objects will know where and how to go. For the automotive industry a set of definitions categorise a manually operated vehicle; a vehicle with few assisted functions such as taking the foot off during cruise control or hands off during parking assist; both foot and hands off while driving with aided lane keeping, or even eyes off once fully autonomous systems are mature. But roads, as we know them, are mixed zones with pedestrians, bicyclists, animals all behaving randomly (I once hit a boar on a German Autobahn at 2 am. My Volvo survived!). Hence the autobahn or motorway with its simple rules and no crossing objects (boars beware!) will most likely be the first place where autonomous cars are set free.

Certain autonomous applications are basically under centralised control such as unmanned metro trains or automated container handling at harbour terminals: people and other random encounters are kept entirely out of the premises.

For industrial purposes autonomous solutions appear promising to reduce operational cost: Extend the assembly or handling robot to let autonomous vehicles move parts to and from the assembly line. Move goods into, around and out of a storage. Discharge, sort and repackage from inbound containers to lorries delivering the last mile to customers.

In most cases one single and simple system of determining the position will not suffice. To make the system robust, different technologies will cooperate and recalibrate themselves by adding relative input (such as accelerometer and gyroscopic sensing of a vehicle) to e.g. a wireless positioning system.

Plenty of proven and operational automation technologies exist to track and steer equipment and goods. The challenge is selecting the optimal method to balance up-front investment and operational cost – while providing ample business opportunities to separate from competition and assuring the instalment is not leading to a dead end as technologies further mature.

-Click for reading part II-

More information:

Senior Advisor Jesper Meulengracht, jesper.meulengracht@glaze.dk, +45 70 23 50 05

Positioning technologies currently applied across industries:

Global Navigational Satellite System: Outdoor positioning requires line-of-sight to satellites, e.g. GPS: the tracking device calculates its position from 4 satellites’ timing signals then transmits to receiving network
–    via local data network, e.g. wifi, proprietary Wide Area Network
–    via public/global data network, e.g. 3G/4G

Active RFID: A local wireless positioning infrastructure built on premises indoor or outdoor calculates the position based on Time of Flight from emitted signal & ID from the tracking device to at least 3 receivers or when passing through a portal. The network is operating in frequency areas such as 2.4 GHz WiFi, 868 MHz, 3.7 GHz (UWB – Ultra Wide Band), the former integrating with existing data network, the latter promising an impressive 0.3 m accuracy. Tracking devices are battery powered.

Passive RFID: Proximity tracking devices are passive tags detected and identified by a reader within close range. Example: Price tags with built-in RFID will set off an alarm if leaving the store. Numerous proprietary systems are on the market. NFC (Near Field Communications) signifies a system where the reader performs the identification by almost touching the tag.

Beacons: Bluetooth Low Energy (BLE) signals sent from a fixed position to a mobile device, which then roughly calculates its proximity based on the fading of the signal strength. For robotic vacuum cleaners an infrared light beacon can be used to guide the vehicle towards the charging station.

Dead Reckoning: Measure via incremental counting of driving wheels’ rotation and steering wheel’s angle. Small variations in sizes of wheel or slip of the surface may introduce an accumulated error, hence this method is often combined with other systems for obtaining an exact re-positioning reset.

Scan and draw map: Laser beam reflections are measured and used for calculating the perimeter of a room and objects. Used for instance when positioning fork-lifts in storage facilities.

Visual recognition: The most advanced degree of vision is required in fully autonomous vehicles using Laser/Radar (Lidar) for recognition of all kinds of object and obstructions. A much simpler method can be used for calculating a position indoor tracking printed 2D barcodes placed at regular intervals in a matrix across the ceiling. An upwards facing camera identifies each pattern and the skewed projection of the viewed angle.

Inertia: A relative movement detection likewise classical gyroscopes in aircrafts now miniaturised to be contained on a chip. From a known starting position and velocity this method measures acceleration as well as rotation in all 3 dimensions which describes any change in movement.

Magnetic field: a digital compass (on chip) can identify the orientation provided no other magnetic signals are causing distortion.

Mix and Improve: Multiple of the listed technologies supplement each other, well-proven or novel, each contributing to precision and robustness of the system. Set a fixpoint via portals or a visual reference to reset dead reckoning & relative movement; supplement satellite signal with known fixpoint: “real time kinematics” refines GPS accuracy to mere centimetres; combine Dead Reckoning and visual recognition of 2D barcodes in the ceiling.

LoRaWAN: A low power wide area network with wide reach. An open standard that runs at unlicensed frequencies, where you establish a network with gateways.

Sigfox: A low power wide area network reminiscent of LoRa. Offered in Denmark by IoT Danmark, which operates the nationwide network that integrates seamlessly to other national Sigfox networks in the world.

NFC: Used especially for wireless cash payments.

Zigbee: Used especially for home automation in smart homes, for example. lighting control.

NB-IoT: Telecommunications companies’ IoT standard. A low-frequency version of the LTE network.

2-3-4G Network: Millions of devices are connected to a small SIM card, which runs primarily over 2G, but also 3G and 4G.

Wifi: The most established standard, especially used for short-range networks, for example. in production facilities.

CATM1: A low power wide area network, especially used in the United States.

Glaze IoT Cloud Project Process

Beacon Tower is Glaze’s Industrial IoT Cloud Platform that can act as either a stepping stone (Platform-as-a-Service, PaaS) or as a out-of-the-box solution (Software-as-a-Solution, SaaS) for collection of IoT-data.

Beacon Tower resides in Microsoft Azure and is designed as a customisable and cost-effective IIoT Cloud Platform that helps simplify deploying, managing, operating, and capturing insights from internet-of things (IoT)-enabled devices. Our customers have the full ownership of their data.

When running it as a PaaS we utilise the design and can run it on our customers’ Azure tenant and customise it fully to their requirements.

Beacon Tower connects to all sensors, PLC, DCS, SCADA, ERP, Historians and MES to gain maximum automation flexibility and ​prevent vendor lock-in.

For more information visit www.beacontower.io or read the PDF.

Edge Computing Categories and Questions

Device:
o    Sensors
o    Internet connectivity
o    Battery consumption
o    Field Gateway
o    Communication protocols (HTTP, AMQP, MQTT, Gateway)
o    Format of the telegrams sent to the cloud (JSON, Avro, etc.)

Data:
o    Number of devices & number of signals
o    Amount of data to transfer per day
– Event-based or batched or mix
– Transfer rate (every second, minute, hour)
o    Device timestamps
– Synchronized timestamps with cloud or not
– Local buffering on device, late and/or repeated data
o    Any time-critical notifications / alarms
– Latency expectations for non-time critical data
– Alarms generated by device and/or by cloud platform
o    Cloud-to-device messages & commands
o    Analytics
– Results from time-series data / Streaming analytics
– Analytics workflows on data, machine learning etc.
– Edge analytics / intelligence

Cost expectations:
o    Retention periods (for reporting purposes)
o    Aggregation of data, possibilities for cost saving

External integrations:
o    Reference data / online data

Administration, rights and access:
o    Requirements for multi-tenancy (segregated owners)
o    Owners/tenants and operators/technicians
o    Administrating access to data, auditing use
o    API management, consumption of data, 3rd party integrators

Operation:
o    KPI measurements for device
o    KPI measurements for cloud platform
o    Requirements on operators and SLA’s

User-interfaces and functions:
o    Operators/technicians
o    Customers/end-users

Glaze Business Innovation and Development Framework (BIDF)

1. Strategy

Creating an IoT Strategy that aligns with the existing company strategy and/or points out any discrepancies that needs to be addressed. The IoT Strategy should pinpoint type of IoT opportunities that should be sought and how they can support the Company delivering on their overall strategies.

2. Ideation

The Ideation phase is an innovative and creative phase where we identify the IoT opportunities within the company. This is done by using existing assets, industry expertise, industry analysis, strategy and IoT expertise to find opportunities for IoT endeavors. This is done in an structured but open-minded and creative setting.

3. Refinement

In Refinement the opportunities are detailed, prioritized and evaluated in a series of steps with the goal of finding a short list of initiatives the company want to pursue. These steps takes strategy, competence, risk level, customer maturity etc into account during prioritization.

4. Valuation

The short list of opportunities are detailed even further and business cases are created for each of them. This will lead to a decision which opportunity to pursue further.

Moving on from the Business Innovation phases to Development activities we focus on taking the minimum possible risk of building the wrong solution by using agile development practices.

5. Exploration

Proof of Concepts carried out in this phase in order to map out technology as well as user-oriented risks. This also refines the budget and thus valuation and business case. Also giving valuable input to baseline system architecture and eco system involvement.

6. Planning

Moving to Planning phase, the most promising business case has been selected and now it is time to plan the Minimal Viable Product (MVP), in terms of timeline, resources and detailed design.

7. Foundation

Implementing the baseline architecture, toolchains and most critical points of the project.

8. Development

Full MVP is developed using these three principles: Start small, don’t over-engineer; Agile software development – late changes welcomed; Continuous delivery – every change is immediately visible.

9. Operations

Operations in an IoT-project is more than just keeping the product alive. It is life-long updates and continous sharpening of features and business model, meaning new ideas are fed back in the Innovation and Development Framework.

Heat map example on a typical business case: