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,, +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.