Connect with us

Cars

How pizza can teach self-driving cars

Published

on

Domino’s Pizza and Ford are launching an collaboration to understand the role that self-driving vehicles can play in pizza delivery.

As part of the testing, researchers from both companies will investigate customer reactions to interacting with a self-driving vehicle as a part of their delivery experience.  This research is important as both companies begin to examine and understand customers’ perspectives around the future of food delivery with self-driving vehicles.

“As delivery experts, we’ve been watching the development of self-driving vehicles with great interest as we believe transportation is undergoing fundamental, dramatic change,” said Patrick Doyle, Domino’s president and CEO. “We pride ourselves on being technology leaders and are excited to help lead research into how self-driving vehicles may play a role in the future of pizza delivery. This is the first step in an ongoing process of testing that we plan to undertake with Ford.”

As Ford builds out its business enabled by self-driving vehicles, conducting research with companies, like Domino’s, will be crucial to ensuring that the technology is applied in ways that enhance the customer experience. With a plan to begin production of self-driving vehicles in 2021, Ford is taking steps to design a business to meet the needs of both partner companies and their customers.

“As we increase our understanding of the business opportunity for self-driving vehicles to support the movement of people and goods, we’re pleased to have Domino’s join us in this important part of the development process,” said Sherif Marakby, Ford vice president, Autonomous and Electric Vehicles. “As a company focused on the customer experience, Domino’s shares our vision for a future enabled by smart vehicles in a smart environment that enhance people’s lives.”

Over the next several weeks, randomly-selected Domino’s customers in Ann Arbor will have the opportunity to receive their delivery order from a Ford Fusion Hybrid Autonomous Research Vehicle, which will be manually-driven by a Ford safety engineer and staffed with researchers. Customers who agree to participate will be able to track the delivery vehicle through GPS using an upgraded version of Domino’s Tracker®. They will also receive text messages as the self-driving vehicle approaches that will guide them on how to retrieve their pizza using a unique code to unlock the Domino’s Heatwave Compartment™ inside the vehicle.

“We’re interested to learn what people think about this type of delivery,” said Russell Weiner, president of Domino’s USA. “The majority of our questions are about the last 50 feet of the delivery experience. For instance, how will customers react to coming outside to get their food? We need to make sure the interface is clear and simple. We need to understand if a customer’s experience is different if the car is parked in the driveway versus next to the curb. All of our testing research is focused on our goal to someday make deliveries with self-driving vehicles as seamless and customer-friendly as possible.”

Local partner Roush Enterprises fabricated the prototype vehicle’s pizza container, Domino’s Heatwave Compartment, based on its experience working with Domino’s on the DXP® delivery vehicle in 2015. Ford and Domino’s completed preliminary testing of the delivery process using the vehicle in self-driving mode at Mcity, the simulated urban environment on the University of Michigan’s campus. The city of Ann Arbor also has been supportive of the testing process.

“I’m delighted that Ann Arbor continues to be at the forefront of autonomous-vehicle research,” said Ann Arbor Mayor Christopher Taylor. “While it’s pizza delivery today, my hope is that collaborations such as this will enable even more innovations tomorrow.”

Cars

Project Bloodhound saved

The British project to break the world landspeed record at a site in the Northern Cape has been saved by a new backer, after it went into bankruptcy proceedings in October.

Published

on

Two weeks ago,  and two months after entering voluntary administration, the Bloodhound Programme Limited announced it was shutting down. This week it announced that its assets, including the Bloodhound Supersonic Car (SSC), had been acquired by an enthusiastic – and wealthy – supporter.

“We are absolutely delighted that on Monday 17th December, the business and assets were bought, allowing the Project to continue,” the team said in a statement.

“The acquisition was made by Yorkshire-based entrepreneur Ian Warhurst. Ian is a mechanical engineer by training, with a strong background in managing a highly successful business in the automotive engineering sector, so he will bring a lot of expertise to the Project.”

Warhurst and his family, says the team, have been enthusiastic Bloodhound supporters for many years, and this inspired his new involvement with the Project.

“I am delighted to have been able to safeguard the business and assets preventing the project breakup,” he said. “I know how important it is to inspire young people about science, technology, engineering and maths, and I want to ensure Bloodhound can continue doing that into the future.

“It’s clear how much this unique British project means to people and I have been overwhelmed by the messages of thanks I have received in the last few days.”

The record attempt was due to be made late next year at Hakskeen Pan in the Kalahari Desert, where retired pilot Andy Green planned to beat the 1228km/h land-speed record he set in the United States in 1997. The target is for Bloodhound to become the first car to reach 1000mph (1610km/h). A track 19km long and 500 metres wide has been prepared, with members of the local community hired to clear 16 000 tons of rock and stone to smooth the surface.

The team said in its announcement this week: “Although it has been a frustrating few months for Bloodhound, we are thrilled that Ian has saved Bloodhound SSC from closure for the country and the many supporters around the world who have been inspired by the Project. We now have a lot of planning to do for 2019 and beyond.”

Continue Reading

Cars

Motor Racing meets Machine Learning

The futuristic car technology of tomorrow is being built today in both racing cars and
toys, writes ARTHUR GOLDSTUCK

Published

on

The car of tomorrow, most of us imagine, is being built by the great automobile manufacturers of the world. More and more, however, we are seeing information technology companies joining the race to power the autonomous vehicle future.

Last year, chip-maker Intel paid $15.3-billion to acquire Israeli company Mobileye, a leader in computer vision for autonomous driving technology. Google’s autonomous taxi division, Waymo, has been valued at $45-billion.

Now there’s a new name to add to the roster of technology giants driving the future.

DeepRacer on the inside

Amazon Web Services, the world’s biggest cloud computing service and a subsidiary of Amazon.com,  last month unveiled a scale model autonomous racing car for developers to build new artificial intelligence applications. Almost in the same breath, at its annual re:Invent conference in Las Vegas, it showcased the work being done with machine learning in Formula 1 racing.

AWS DeepRacer is a 1/18th scale fully autonomous race car, designed to incorporate the features and behaviour of a full-sized vehicle. It boasts all-wheel drive, monster truck tires, an HD video camera, and on-board computing power. In short, everything a kid would want of a self-driving toy car.

But then, it also adds everything a developer would need to make the car autonomous in ways that, for now, can only be imagined. It uses a new form of machine learning (ML), the technology that allows computer systems to improve their functions progressively as they receive feedback from their activities. ML is at the heart of artificial intelligence (AI), and will be core to autonomous, self-driving vehicles.

AWS has taken ML a step further, with an approach called reinforcement learning. This allows for quicker development of ML models and applications, and DeepRacer is designed to allow developers to experiment with and hone their skill in this area. It is built on top of another AWS platform, called Amazon SageMaker, which enables developers and data scientists to build, train, and deploy machine learning quickly and easily.

Along with DeepRacer, AWS also announced the DeepRacer League, the world’s first global autonomous racing league, open to anyone who orders the scale model from AWS.

DeepRacer on the outside

As if to prove that DeepRacer is not just a quirky entry into the world of motor racing, AWS also showcased the work it is doing with the Formula One Group. Ross Brawn, Formula 1’s managing director of Motor Sports, joined AWS CEO Andy Jassy during the keynote address at the re:Invent conference, to demonstrate how motor racing meets machine learning.

“More than a million data points a second are transmitted between car and team during a Formula 1 race,” he said. “From this data, we can make predictions about what we expect to happen in a wheel-to-wheel situation, overtaking advantage, and pit stop advantage. ML can help us apply a proper analysis of a situation, and also bring it to fans.

“Formula 1 is a complete team contest. If you look at a video of tyre-changing in a pit stop – it takes 1.6 seconds to change four wheels and tyres – blink and you will miss it. Imagine the training that goes into it? It’s also a contest of innovative minds.”

AWS CEO Andy Jassy unveils DeepRacer

Formula 1 racing has more than 500 million global fans and generated $1.8 billion in revenue in 2017. As a result, there are massive demands on performance, analysis and information. 

During a race, up to 120 sensors on each car generate up to 3GB of data and 1 500 data points – every second. It is impossible to analyse this data on the fly without an ML platform like Amazon SageMaker. It has a further advantage: the data scientists are able to incorporate 65 years of historical race data to compare performance, make predictions, and provide insights into the teams’ and drivers’ split-second decisions and strategies.

This means Formula 1 can pinpoint how a driver is performing and whether or not drivers have pushed themselves over the limit.

“By leveraging Amazon SageMaker and AWS’s machine-learning services, we are able to deliver these powerful insights and predictions to fans in real time,” said Pete Samara, director of innovation and digital technology at Formula 1.

  • Arthur Goldstuck is founder of World Wide Worx and editor-in-chief of Gadget.co.za. Follow him on Twitter on @art2gee and on YouTube

Continue Reading

Trending

Copyright © 2018 World Wide Worx