Vehicle Asset Management System

The Challenge

Vehicle Asset Management System (VAM) products enable efficient management of vehicular fleets (e.g. fleets, emergency services and heavy equipment/machinery) and offer driver-behaviour monitoring for the vehicle insurance markets. This is achieved through incorporating cellular modems and GPS modules, both of which require antennas to function effectively.

There is often enormous market pressure to reduce the size of products of this kind, for example, so they can fit into a cramped location in the vehicle. This can transform the development of the antenna system from a straightforward integration of individual designs, focussed on particular frequency bands, to a highly complex custom development. Each antenna interacts strongly with other antennas and with components of the product (PCB, battery etc). In many ways, it can be said that the entire product becomes the antenna. Plextek began working on this technology in 1993 and since the initial brief works with multiple clients in this area through our spinout business Redtail Telematics.

The Approach

Fortunately, we have the ability to model the electromagnetics of the entire product, allowing us to predict the impact of design changes and reduce the need to iterate. The antenna design process used by Plextek also takes account of the VAM product placement in the vehicle and, in particular, consideration of materials close to the VAM unit that might affect the performance of the antenna system.

The VAM product uses a custom designed a multiband-band cellular antenna, integrated onto a PCB substrate together with a custom GPS antenna. This solution exceeds the performance requirements set out in the standards, resulting in a lower product cost than the equivalent COTS antennas and allows integration into a tiny product package.  Plextek is responsible for the design and manufacture of the Redtail Telematics range of Vehicle Asset Management (VAM) products.

The Outcome

In 2015, Plextek Ltd formally spun out Redtail Telematics, which provides turnkey vehicle telematics services to the fleet management and automotive insurance markets. Since 1993, Redtail have shipped more than six million tracking devices into line fit and aftermarket vehicles for stolen vehicle recovery. Redtail’s expertise in working collaboratively to answer challenging questions directs our efforts in working with OEMs to fulfil the potential of the connected vehicle, from line fit vehicle tracking with Mercedes Benz, through golf-cart battery health with Columbia Vehicle, to pothole detection with Jaguar Land Rover & Synaptiv.

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Intelligent Mobility

The Challenge

Autonomous vehicles must be capable of sensing their environment, including moving objects and people, so that they can move safely with little to no human input or risk. The de-risking exercise involves testing and validation using real life scenarios in a controlled environment. The health of the decisions taken by the vehicles on-board systems need to be validated by external sources of information.

Cranfield University’s on campus test road equipped with Cameras and Lidars provides that environment. However, these external sources have limitations that needed complementary solutions to enhance the data set required for decision making.

In pursuit of achieving the next level of vehicle autonomy, Plextek assisted Cranfield University in its £1.2 million pound HumanDrive Connected and Autonomous Vehicle project. The aim of which was to test and validate the full autonomy of a vehicle as it completes an end-to-end journey.

The Approach

Plextek provided Cranfield University with 12 electronic-scanning radars to form a robust testing process for their advanced vehicle control system. Compact and low power consumption, the radars were spaced along the University’s “smart road” to detect and localise vehicles, unmanned aerial systems and people from up to 120 metres, providing vital data for the project.

The advanced vehicle control system, designed to emulate a ‘natural’ human driving style using machine learning and artificial intelligence, was challenged in a variety of environments and weather conditions. Situations that would test the ability of a human driver were simulated, including densely populated sidewalks and navigating roads with low visibility, such as rain and darkness. The data provided by radars installed on the test road was used to test and validate the decisions made by autonomous vehicles.

The Outcome

In late 2019, HumanDrive will complete a complex real-world journey that is both driverless and human-like for other road users.

The autonomous vehicle will perform a 200+ mile route across the UK through country roads, A-roads, traffic junctions and motorways.

This marks a pivotal point for the successful deployment of an autonomous vehicle solution in the UK. https://humandrive.co.uk/

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Tyre Pressure Monitoring

The Challenge

A market leader in tyre pressure monitoring was going through a transformation of their product from Analog to Digital. A product that worked in their labs and limited trials failed when put to test in the real environment.

The designers and developers were all baffled by the tricky engineering conundrum they were facing. With contracts already signed and customers waiting for the product, the client wanted to bring on board a consultant with a strong background in accelerometers and signal processing.

The Approach

Plextek consultants audited the design and conducted a thorough analysis of the data and algorithms. Professional tools and standards were used for analysing the data that helped identify the errors at different stages of the design.

Detailed interviews highlighted the disconnect between technical and business functions that resulted in the gradual introduction of errors at different stages rendering the product unusable for real environments.

A new build-measure-learn approach was introduced along with actionable metrics.

The Outcome

Design faults were identified and the product redesigned to required standards. Process improvements were put in place for long term gains. This resulted in saving major contracts and mitigated the potential financial loss for our client.

The new build-measure-learn approach reduced the development cycle from months to weeks and the actionable metrics helped streamline the right actions at the right time.

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A Passive Radar Identification Tag for Unambiguous Object Localisation

The Challenge

Practical object and vehicle recognition in intelligent and autonomous transport systems remains a data-first problem.

The more unique data that is captured and identified, the more accurate the decisioning models can be.

As part of the Department for Transport’s Transport Technology Research Innovation Grant (T-TRIG), Plextek produced a comprehensive study on a low size, weight and power tagging system and PoC which can bounce back a unique radar signal in order to provide exact object and vehicle localisation and recognition.

The Approach

Plextek have successfully developed a low-cost proof of concept demonstrator. This retroreflector ID tag has been lab tested at two typical ranges for its application, 30m – 60m with successful results. Implementing a radar system with optimized power and ramp waveforms would enable the tagging system to continue to work at longer ranges.

The Outcome

The retroflector ID tag study suggests that it can act as a high visibility jacket for high frequency signals and extends the capability of standard automotive radars.

In a smart city landscape, this tag could recognise road signage and infrastructure, other road vehicles and support autonomous convoy operation.

In addition, the tagging system could enable the identification of drones, small aircraft and the monitoring of small craft at sea in poor weather conditions.

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Smart City Parking System

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- Philip Handley, Smart DCC Ltd.

The Challenge

Finding a parking space in a busy city can be frustrating. It is also a leading contributor to traffic congestion and air pollution within urban environments.

Gorizont Telecom approached Plextek to deliver the key enabling technologies for a system to detect occupancy in on-street parking spaces. This real-time data could notify drivers of the available slots to enable smarter parking and alleviate congestion.

This required a highly accurate in-road parking sensor, citywide radio coverage and a secure back-end server with ultra-high availability.

The solution would be implemented in Moscow, Russia and due to the winter weather, the entire project had to be compressed into six months, from initial research through to city-wide deployment. As a result, our sensors would have to cope with harsh temperatures and road conditions.

The Approach

After investigating a number of sensing methods, a magnetometer was selected as the primary sensor. Because neighbouring vehicles, passing vehicles or parallel-parked vehicles can produce false results, we developed signal processing algorithms, threshold manipulation and self-calibration programs to achieve the false trigger rate specified by the client.

The sensors had no external power supply, so they were designed to operate on a low cost internal battery with a five-year lifespan. The radio communications design was a challenge as the top of the sensor had to be flush with the road surface requiring a unique antenna created to fit around other components.

Plextek was also responsible for the design of the base station infrastructure and server that gathered the sensor data and distributed it to user facing Apps and signage.

The Outcome

The whole system was delivered and installed just before the winter freeze, allowing Gorizont Telecom to complete all acceptance criteria.

The radio design allowed a relatively sparse network of base stations to be used to save cost and the straightforward sensor deployment and calibration procedure allowed 11,000 in-road parking sensors to be deployed in two just weeks.

The technology has been successfully re-deployed in other Russian cities, including St. Petersberg.

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