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THE WHICHEV VIEW: Stellantis buys in Ai technologies to improve EV experience

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Stellantis, a global automotive giant, has taken a significant step towards enhancing its electric vehicles’ driving experience by acquiring key artificial intelligence (AI) technologies and intellectual property (IP) from CloudMade, a company known for its innovative big data-driven automotive solutions.

This move is aimed at bolstering the mid-term development of the STLA SmartCockpit and aligns with Stellantis’ comprehensive software strategy, Dare Forward 2030. It follows on from the previous purchase of AiMotive.

Take a deep dive on this story over at WhichEV.

Ford and Hermes partner on autonomous delivery vehicles

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Ford has announced a new Self-Driving Vehicle Research Programme designed to help businesses in Europe understand how autonomous vehicles can benefit their operations.

Hermes is the first business to partner with Ford on the programme. Using a customised Ford commercial vehicle, the research aims to better understand how other road users would interact with an apparently driverless delivery van.

The specially adapted Ford Transit features sensors that mimic the look of an actual self-driving vehicle plus a “Human Car Seat” in control of the vehicle – this enables an experienced, hidden driver to drive while giving the impression to others around that there is no one at the wheel.

“As we plan to bring autonomous vehicles to the roads, it is important that we focus not only on enabling the technology, but on enabling our customers’ businesses,” said Richard Balch, director, Autonomous Vehicles and Mobility, Ford of Europe. “Clearly, there is no better way to identify how they may need to adapt than to experience those processes in real life.”

Ford has for six years been Europe’s market leader in commercial vehicles. 1 By harnessing this experience with expertise from delivery firms, the company intends to identify new opportunities and models for autonomous vehicle operations – in particular understanding how existing processes and human interactions can work alongside automated vehicles. Commercial vehicles’ planned operations and many human interactions are an ideal test case.

A commercial vehicle driver’s responsibilities sometimes extend beyond simply driving from one destination to another. In a delivery or logistics operation, for example, the driver may also be tasked with sorting and loading goods, manually handing packages over to recipients – or reloading them onto the van if delivery is not possible.

However, in this research, the driver will play an entirely passive role, simply driving the vehicle. Pedestrian couriers who support the delivery van are equipped with a smartphone app that lets them hail the vehicle and remotely unlock the load door after it is safely parked at the roadside. Once inside, voice prompts and digital screens direct the courier  to their locker, containing the parcels to be delivered.

Understanding and designing how humans will interact with the vehicle will ensure that business processes are able to continue safely without a driver present.

The two-week research project with Hermes builds on the success of Ford’s “last mile delivery” trials in London, in which a team of pedestrian couriers collects parcels from a delivery van and fulfils the last leg of the delivery by foot resulting in fast, sustainable and efficient deliveries in cities.

The research vehicles will enable Hermes and other businesses to begin designing how their teams could work alongside driverless vehicles. For Hermes, this user design research has included developing an app that enables the pedestrian couriers to access the van to collect parcels, once again, this is a role that the human driver would normally fulfil.

“We’re excited to collaborate with Ford on this proof of concept trial, which is all about understanding the potential for autonomous vehicles and if they have a role in delivery in the longer-term future,” said Lynsey Aston, head of product, Innovation and Onboarding. “We’re constantly innovating to incubate and then explore concepts like this, and we look forward to the initial findings, which will no doubt be useful on an industry-wide level.”

Ford researchers are already investigating how self-driving vehicles will integrate seamlessly into our daily lives, including developing a light-based visual language to convey to other drivers, pedestrians and cyclists what autonomous vehicles intend to do next.

Ford has been testing self-driving technology in major cities across the U.S. and plans to invest around $7 billion in autonomous vehicles during 10 years through to 2025 – $5 billion of that from 2021 forward – as part of its Ford Mobility initiatives.

In collaboration with Ford’s self-driving technology partner, Argo AI, autonomous test vehicles operate daily in six U.S. cities. Last year, Argo AI’s comprehensive self-driving system enabled address-to-address autonomous deliveries of fresh produce and school supplies through a charitable goods pilot in Miami, Florida, in the United States.

AI likely to be used to identify common fleet documents

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The first widespread use of artificial intelligence in fleet management is likely to be to identify common documents.

That’s according to Neil Avent, IT director at FleetCheck, who explained that AI was good at looking for patterns within clearly defined boundaries, so would work well for this kind of task.

“The important factor to understand about current AI technology is that it has no innate sense of context. It works well in situations where there are a limited number of possibilities and outcomes,” said Avent.

“For example, if you give it a thousand pictures and ask it to find all the ones that include kittens, you could teach it to do this pretty effectively by providing enough examples of pictures containing a kitten.

“This is why it is likely to first find its practical use when it comes to documentation. When different sorts of document arrive into a fleet department, it could be used to simply answer a series of questions – is it an invoice? A driver’s licence? A speeding fine notification?

“AI is good at a singular type of task such as this. It can be taught to identify some of the key features of each kind of document and then place them in the appropriate queue for action with a high degree of accuracy. This saves a lot of administrative time and effort.”

However, Avent also explained that the current boundaries of AI were revealed by the fact that the technology was not currently sophisticated enough to then manage the documents.

“A separate process would be needed to know what to do with those documents in terms of the next action. That is because a more general type of software-driven intelligence, in terms of the technology available, is a long way away.

“Going back to the pictures of kittens, AI’s intelligence about kittens would end with being able to identify images. It knows nothing more about kittens than the visual characteristics of the example images containing kittens. It does not know what a kitten is.”

Several paradigm shifts would be needed before AI could take over even some quite basic fleet management processes, Avent added.

“In a sense, it is a shame that AI as a term includes the word ‘intelligence’ because it provides a very misleading picture of its capability. It has no intelligence of its own and is, in many ways, just a further development and refinement of existing IT processes that gives the illusion of intelligence to users not aware of its constraints.

“However, it does have potential for some pretty significant gains and one of the things we’ll be looking at within FleetCheck later into 2019 is how some of those can be incorporated into our fleet management software.”

Motorola splashes $445m on AI license plate tracking specialist

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Motorola Solutions has paid $445 million for VaaS International Holdings (VaaS), which provides global data image analytics for vehicle location.

The deal includes a combination of cash and equity. VaaS’s image capture and analysis platform, which includes fixed and mobile license plate reader cameras driven by machine learning and artificial intelligence, provides vehicle location data to public safety and commercial customers.

Its subsidiaries include Vigilant Solutions for law enforcement users and Digital Recognition Network (DRN) for commercial customers. The company’s 2019 revenues are expected to be approximately $100 million.

Greg Brown, chairman and CEO, Motorola Solutions, said: “Automated license plate recognition is an increasingly powerful tool for law enforcement.

“VaaS will expand our command centre software portfolio with the largest shareable database of vehicle location information that can help shorten response times and improve the speed and accuracy of investigations.”

VaaS’s platform also enables controllable, audited data-sharing across multiple law enforcement agencies. Vehicle location information can help accelerate time to resolution and improve outcomes for public safety agencies, particularly when combined with police records. For example, law enforcement has used VaaS’ solutions to quickly apprehend dangerous suspects and find missing persons.

“We are very excited to be joining Motorola Solutions,” said Shawn Smith, co-founder of VaaS and president of Vigilant Solutions.

“This acquisition enables us to continue to serve our existing customers and expand our footprint globally, while at the same time supporting a company with a commitment to innovation and growth, guided by a common purpose that aligns with our mission and culture: ‘To help people be their best in the moments that matter.’ It doesn’t get any better than that.”