National

CA DMV's comment period for light-duty delivery AVs ends on May 27th and could usher in a slew of delivery AVs on roads in the state.

Why it matters: Smaller AVs and bots could cover last-mile and even last-meter delivery and possibly reduce the cost of delivering individual packages down to 4 to 7 cents. But the tech's biggest draw is the data it could collect on customer behavior by location. 

What’s happening: Companies are experimenting with different delivery bots for different purposes. 

Last-mile delivery vehicles, roughly the size of passenger cars, travel on public roads, and would generally require customers to go to the curb to pick up deliveries from the vehicle. AV developer Nuro and Kroger, the giant grocery chain, are among those partnering to deliver goods this way. 

Last-meter delivery bots, which are smaller, can travel on sidewalks and deliver packages door to door. These are being deployed in pilot tests including Postmates' Serve, in Los Angeles, and Amazon's Scout in Seattle.

Yes, but: These delivery systems could collect far more data about a customer's location and residence than, say, Amazon's locker delivery program. And they're designed to make delivery cheaper and more appealing, which could result in customers ordering more purchases via delivery, giving companies even more data about their buying habits. 

Armed with such data, retailers could, for instance, limit investment in neighborhoods where households spend less than average on groceries, potentially creating food deserts in less affluent areas.

What we are watching: San Francisco, a major early testing ground for small, sidewalk-bound delivery bots banned them on most streets due to a public outcry that they obstruct sidewalks, and has created a permit process for limited testing. 

It remains to be seen if customers will put up with increasing data collection and possible road congestion, and even sidewalk congestion, for convenience. 

Sudha Jamthe is director of DriverlessWorldSchool and teaches AV Business at Stanford Continuing Studies. 

Editor’s note: This post has been corrected to reflect that the California DMV's proposed regulations address only autonomous delivery vehicles under 10,001 pounds that will use public roads (not sidewalk delivery bots).

Delivery AVs and bots could pick up data, too

Neighborhood purchasing data could be used to determine store locations.

Front view with digital face of Kiwi self driving autonomous package delivery robot parked in Berkeley, California

A Kiwi self driving autonomous package delivery robot parked in Berkeley, California. Photo: Smith Collection/Gado/Getty Images

Transportation

Autonomous vehicle technology

Expert Voices

Technology

Future

CA DMV&#x27;s <a class="gtmContentClick" data-vars-link-text="comment period" data-vars-click-url="https://www.dmv.ca.gov/portal/dmv/detail/pubs/newsrel/2019/2019_12" data-vars-content-id="205b7938-284a-443f-b08b-e220810fc98b" data-vars-headline="Delivery AVs and bots could pick up data, too" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.dmv.ca.gov/portal/dmv/detail/pubs/newsrel/2019/2019_12" target="_blank">comment period</a> for light-duty delivery AVs ends on May 27th and could usher in a slew of delivery AVs on roads in the state.Why it matters: Smaller AVs and bots could cover last-mile and even last-meter delivery and possibly <a class="gtmContentClick" data-vars-link-text="reduce the cost" data-vars-click-url="https://www.axios.com/autonomous-vehicles-could-be-used-for-deliveries-3fb12a24-3e66-4d8b-b678-a2fbb47d05cb.html" data-vars-content-id="205b7938-284a-443f-b08b-e220810fc98b" data-vars-headline="Delivery AVs and bots could pick up data, too" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.axios.com/autonomous-vehicles-could-be-used-for-deliveries-3fb12a24-3e66-4d8b-b678-a2fbb47d05cb.html" target="_self">reduce the cost</a> of delivering individual packages down to 4 to 7 cents. But the tech&#x27;s biggest draw is the data it could collect on customer behavior by location.

From the Valley to D.C., Big Tech players like Facebook, Google and Amazon are under more scrutiny than ever as new technology develops and privacy and antitrust concerns grow in lockstep with companies’ ambitions.

Tesla's new proprietary chip for self-driving software is key to CEO Elon Musk's promise of a driverless robotaxi fleet by 2020. The chip alone won't deliver fully autonomous cars that can operate anywhere but it could help to increase the value of Tesla vehicles. 

The big picture: Other carmakers are focused on autonomous driving for ride-sharing, but Tesla isn't accepting that consumers will abandon car ownership and is chasing a hybrid model of individual car ownership with the option for owners to earn money by sharing their vehicles via robotaxis.

What's happening: Tesla says it has deployed its Hardware 3 chip — which uses a neural network designed to support its self-driving software — in many of its 41,000 employees' Tesla vehicles since December 2018. 

The company is collecting driving data from these cars to feed into its self-driving AI. It has also begun to deploy the new chip into all new Teslas, so that the company can collect data from all Teslas sold since March.

Musk suggested the speed of the chip is comparable to Nvidia’s top-of-the-line AV AI chip — that Tesla and its competitors have been using — and, because it was custom built for their self-driving AI, it can run it faster.

Hardware 3 is designed to exclusively run software that is cryptographically signed by Tesla. This would prevent hackers from controlling Teslas remotely or compromising them via fraudulent software.

The value of the cars could go up, Musk says: Tesla says it will send out self-driving software via over the air update by 2020, which would make vehicles with Hardware 3 capable of full autonomy. It would allow a Tesla owner to potentially add their car to the company's robotaxi pool and earn money off of rides.

Yes, but: Tesla's self-driving software is not yet fully developed, and Musk has missed ambitious deadlines in the past. 

His cars likely will not reach the promised full, hands-free-anywhere driving capability — known as Level 5 autonomy — that soon but they could achieve limited, local mobility (level 3 or 4).

Even when the software is shared, state and local regulation will not allow Teslas to begin driving autonomously everywhere. 

Additionally, it's not clear whether Tesla car owners who are not employees will consent to their cars being tracked at all times by the company and its ridesharing platform, and to having their driving data collected and used.

The bottom line: The move is disruptive to the AV industry, even if Musk misses the 2020 deadline. It marks a departure from Tesla relying on Nvidia chips, lays claim to a technological leap for AVs that would disrupt the rideshare industry as well, and aims to increase the value of Teslas by using them as robotaxis.  

Sudha Jamthe is director of DriverlessWorldSchool and teaches AV Business at Stanford Continuing Studies. Jamthe owns a Tesla and shares of the company's stock.

How Tesla's new chip could increase the value of its cars

Older models could be retrofitted to attain the same level of autonomy.

A coin with Elon Musk's face on it grows in size

Tesla

Business

Electric vehicles

Tesla&#x27;s new proprietary chip for self-driving software is key to CEO Elon Musk&#x27;s promise of a driverless robotaxi fleet by 2020. The chip alone won&#x27;t deliver fully autonomous cars that can operate anywhere but it could help to increase the value of Tesla vehicles. The big picture: Other carmakers are focused on autonomous driving for ride-sharing, but Tesla isn&#x27;t accepting that consumers will abandon car ownership and is chasing a hybrid model of individual car ownership with the option for owners to earn money by sharing their vehicles via robotaxis.

Ominous forecasts about the impact of climate change serve as the backdrop for the world — led by U.S. lawmakers and companies — to debate big action on the problem, which could upend energy systems and our way of life.

Energy & Environment

The shift towards automation in transportation and mobility is expected to eliminate jobs, but it could also create opportunities, like training the artificial intelligence that powers machines. 

The big picture: Members of the workforce who will be impacted need to be trained in the key areas of data literacy, higher cognition decision making and emotional skills — but currently there are few organizations providing that training.

The impact: Changes to all kinds of professions are likely to result from new mobility technology. 

A Brookings study estimated that in 2017, 9.5 million jobs were impacted by such technology — only 3.9 million of which were driver jobs. 

What's happening: As artificial intelligence is integrated into professions ranging from administrative work to customer support, people will need to be trained to work alongside machines — but also on non-technological skills, like customer service and decision making. 

Organizations like the Michigan Mobility Institute, the Center on Rural Innovation and ARM Institute are focused on skills training for workers traditionally employed in manufacturing.

Training courses offered by Coursera, EdX and more teach data science and how to build AI-powered tech, including autonomous vehicles.

Stanford Continuing Studies offers opportunities for product and business managers to re-skill for mobility-related jobs impacted by AI. 

Yes, but: Higher cognitive and emotional skills are expected to be in demand in new jobs that require humans to act as intermediaries between customers and machines, and training on these skills is not receiving the same kind of programatic investment.

Training AV safety drivers, work that is taxing and involves higher cognitive decision-making, remains a challenge. 

The bottom line: Re-skilling programs should help provide job security to current members of the workforce — but it's also crucial to establish a longterm pipeline for future members of the workforce who will train and work alongside machines.

Sudha Jamthe is director of DriverlessWorldSchool and teaches AV Business at Stanford Continuing Studies.

Automation in mobility is outpacing skills re-training programs

Autonomous technologies are placing new demands on workers across industries.

Illustration of a robot hand diagram on a chalkboard

Automation

Automation and AI

The shift towards automation in transportation and mobility is expected to eliminate jobs, but it could also create opportunities, like training the artificial intelligence that powers machines. The big picture: Members of the workforce who will be impacted need to be <a class="gtmContentClick" data-vars-link-text="trained" data-vars-click-url="https://www.axios.com/self-driving-cars-skills-gap-166bbba3-736d-495e-a444-f306b06d88f1.html" data-vars-content-id="5c5a6929-7478-483e-8663-25a8df5180dd" data-vars-headline="Automation in mobility is outpacing skills re-training programs" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.axios.com/self-driving-cars-skills-gap-166bbba3-736d-495e-a444-f306b06d88f1.html" target="_self">trained</a> in the key areas of data literacy, higher cognition decision making and emotional skills — but currently there are few organizations providing that training.

As mobility data is amassed from ride-hailing, dockless bikes and e-scooters, cities need tools to responsibly track, store, and analyze it. 

The big picture: With cities collecting that mobility data, in some cases as a condition for transportation companies to operate, they are facing a new challenge: how to be responsible stewards of this influx of data.

What's needed: It's imperative that cities anonymize data and store it securely — but it's also important for cities to be transparent about what data they're collecting and make it available for analysis by city officials, residents, academics, and other stakeholders.

The city of Los Angeles developed the Mobility Data Specification which establishes how data could be uniformly formatted and shared among multiple stakeholders. 

A group of cities, including LA, and private and non-profit organizations recently partnered to form the Open Mobility Foundation, which aims to use new mobility technology to improve safety, equity, and quality of life while adhering to strict privacy and security practices in how data is collected and managed.

Between the lines: These programs establish best practices around user privacy and transparency, and foster the use of data to ensure equal mobility access to all residents, even when data is initially collected by private companies. 

If companies and cities adhere to the Mobility Data Specification, which is promoted by the Open Mobility Foundation, then cities could compare their data analysis and make common policy decisions in a collaborative and transparent way. 

Cities could also use mobility data to plan infrastructure updates that could expand mobility options and accessibility, and ensure that available mobility services are equitable and that no neighborhoods are left behind.

Efficient and accurate data collection will be crucial for enforcing policies around mobility services, including the number of vehicles or devices allowed in a given city.

As mobility data is combined with other data sources such as census findings and retail data, cities could begin to make planning decisions and investments differently.

Mobility data could give cities new tools to improve equity

But they will need systems to share and protect the data.

Illustration of arrows going in different directions, casting shadows with binary code in them

Cities

Data

As mobility data is amassed from ride-hailing, dockless bikes and e-scooters, cities need tools to responsibly track, store, and analyze it. The big picture: With cities collecting that mobility data, in some cases as a <a class="gtmContentClick" data-vars-link-text="condition" data-vars-click-url="https://ladot.lacity.org/sites/g/files/wph266/f/LADOTDocklessCP.pdf" data-vars-content-id="9d1670c3-a08e-4dcb-b87c-bc1ad7a576d4" data-vars-headline="Mobility data could give cities new tools to improve equity" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://ladot.lacity.org/sites/g/files/wph266/f/LADOTDocklessCP.pdf" target="_blank">condition</a> for transportation companies to operate, they are facing a new challenge: how to be responsible stewards of this influx of data.

This week, Ford, BMW, Mercedes Benz and Volvo announced a major data sharing partnership focused on road safety that includes European service providers and the transportation ministries of several EU member states.

Why it matters: Shared data from connected vehicles on weather and road conditions will ideally improve safety in real-time, and it could represent a major step forward for vehicle to vehicle communication. 

What's happening: This latest partnership, overseen by the European Data Task Force, is one of several recent efforts by automakers to collaborate in order to share data. 

The idea here is to collect data when a vehicle, say, turns on its hazard warning lights, then share that data with vehicles nearby via cloud technology.

BMW, GM, Ford and Renault have also formed a research group that aims to use blockchain to share customer data to develop shared mobility options.

Between the lines: These data sharing partnerships will allow car companies to test cloud-based and blockchain technology in use cases that could pave the way for communication between autonomous cars.

They also offer opportunities to experiment with transparently sharing anonymized vehicle data, by holding automakers accountable to not misuse it.

European data privacy law ensures that customers will be informed as to how their data is being used, but the U.S. lacks similar protections. 

What we're watching: If customers experience increased safety and convenience, it could ultimately build greater public trust in AVs that eventually have V2V capabilities. 

Automakers are finally starting to share road safety data

Ford, BMW, Mercedes Benz and Volvo are all involved.

Traffic cone with binary running across as stripes

Automakers

This week, Ford, BMW, Mercedes Benz and Volvo <a class="gtmContentClick" data-vars-link-text="announced" data-vars-click-url="https://www.autoexpress.co.uk/volvo/v60/107029/bmw-ford-mercedes-and-volvo-to-share-live-road-safety-data-car-to-car" data-vars-content-id="adbcc9f1-efcf-4e07-8a6d-d6b9af9bb185" data-vars-headline="Automakers are finally starting to share road safety data" data-vars-event-category="story" data-vars-sub-category="story" data-vars-item="in_content_link" href="https://www.autoexpress.co.uk/volvo/v60/107029/bmw-ford-mercedes-and-volvo-to-share-live-road-safety-data-car-to-car" target="_blank">announced</a> a major data sharing partnership focused on road safety that includes European service providers and the transportation ministries of several EU member states.Why it matters: Shared data from connected vehicles on weather and road conditions will ideally improve safety in real-time, and it could represent a major step forward for vehicle to vehicle communication.

Sections

Axios Local

Axios gets you smarter, faster with news & information that matters.

About

Subscribe

Sudha Jamthe

Stories

Mobility data could give cities new tools to improve equity

Automation in mobility is outpacing skills re-training programs

Automakers are finally starting to share road safety data

Delivery AVs and bots could pick up data, too

How Tesla's new chip could increase the value of its cars