Navigant Research Blog

Using Urban Utility Poles To Geo-Locate Vehicles

— September 16, 2016

CarsharingAs engineers around the world work to make the self-driving car a practical reality, one of the biggest challenges still faced is how to precisely locate where those vehicles are in space at any moment in time. This is especially important in scenarios where the sensors can’t actually see the road—for example, when it is snowing. One potential approach to the problem would be to turn traffic signals, street lamps, and utility poles into beacons that could be used to more precisely triangulate position.

As outlined in Navigant Research’s Transportation Outlook: 2025-2050 report from 2Q 2016, a primary application of autonomous vehicles is likely to be providing autonomous mobility on-demand services in urban environments. As more of the world’s population moves into cities in the coming decades, those urban centers are likely to grow both out and up toward the sky. However, while skyscrapers allow more people to live in the same land mass, they also create problems for the satellite-based location systems such as the American GPS, Russian GLONASS, and European GALILEO.

As the low-power signals that are broadcast from satellite constellations bounce off buildings in urban canyons, errors are generated. Current generation systems only have about 5 meters of precision, which is fine for general navigation purposes, but inadequate for an autonomous vehicle that needs to make decisions about where it should be on a given road to make an upcoming turn.

Localized Systems

This is where a new localized position system could be beneficial. Go down the street in any developed city in the world and you will find poles sticking out of the ground every few hundred feet at most. These poles are owned and maintained by utilities, municipal lighting departments, telecommunications providers, and others that connect and power the modern world. Equipping these poles with wireless beacons could enable them to be used for much more precise geolocation than is currently possible.

In 2013, Apple introduced support for its iBeacon technology into the iPhone and iPad. Small beacons using Bluetooth low energy can be used to provide location indoors or out, enabling retailers to track where customers are lingering in stores and food vendors to deliver orders in crowded stadiums. Similar technology could be harnessed on the road to locate vehicles.

In early 2016, Ford conducted the first test of its autonomous Fusion prototypes on snow-covered roads at a Michigan test facility. The car was able to navigate by triangulating landmarks that had previously been mapped out using LIDAR. While this approach worked well enough when the test car was the only vehicle on the track, it could be problematic in a city where the same landmarks could be blocked from the LIDAR’s view by other vehicles or objects. An approach using location beacons would achieve a similar effect in combination with high definition maps while eliminating the line-of-sight problem.

Vehicle-to-Infrastructure

Equipping urban utility poles with beacons could provide the owners of these poles with the first step toward full vehicle-to-infrastructure communications and potentially a mechanism to deploy a variety of other revenue generating services. For example, vehicles equipped with cameras for either driver assist or autonomous systems could be used to gather data about available parking spaces. That could then be fed into a reservation system allowing drivers to find and pay for parking before arriving at the location. The data providers could then get a share of the revenue generated from that service.

The first deployments of these beacons could be done in the next few years as vehicle-to-external communications rolls out in new vehicles followed by 5G wireless systems in the early 2020s.

 

Cyber Security Is Imperative Before Deploying Autonomous Vehicles

— September 1, 2016

Connected VehiclesAugust 2016 brought a flurry of autonomous driving announcements from Delphi, nuTonomy, Ford, Velodyne, Volvo, Uber, Quanergy, and others. News about developments and deployment plans for self-driving vehicles came almost daily. A common thread was that the vehicles will be used as part of autonomous mobility on-demand (AMOD) services that require connectivity in addition to onboard sensing to function. However, something equally (if not more) important to implement before deploying any of these vehicles is beefing up the cyber security.

As the automotive world has raced over the last few years to transform itself into a mobility business, cyber security experts of both the white and black hat variety have also been advancing their own capabilities. In parallel with that, we’ve seen the launch of numerous startups focused on securing increasingly sophisticated vehicles from bad actors, including several based in Israel. Among them are Karamba Security, Argus Cyber Security, and TowerSec.

Hardened Telematics

With external connection points through telematics being the obvious starting point for any malicious attacker trying to infiltrate a vehicle, that’s also the first surface that needs to be hardened. “To provide protection, we have to think like hackers,” said David Barzilai, chairman and co-founder of Karamba. “There are two primary ways to hack a system like this, dropping malicious binary code into the electronic control unit [ECU] or in-memory attacks while the system is running.”

The so-called code-dropper approach involves rewriting some of the code that resides in the flash storage of an ECU with malicious code designed to do something never intended by the manufacturer. Karamba has devised an approach to prevent this that is very straightforward for the software engineers at an automaker to implement without having to change any of their own code.

When building binary files that ultimately get loaded into the ECU, the scripts include calls to the Karamba system to automatically include some of that company’s code. Karamba generates hashes (an encrypted alphanumeric string that uniquely represents the contents of a file) of all the factory binary files which are included. If someone tries to reprogram an ECU with a binary that doesn’t match the hash, it will be rejected.

In-Memory Attacks

Even if the original programming remains intact, in-memory attacks remain the most common attack vector. Control instructions and data get moved from the static flash storage to dynamic memory in order to run in real time. If an attacker manages to inject deliberately corrupted data into a memory address, it is possible to send the control flow off to an instruction never intended by the designers of the system. This is the sort of attack that can enable someone connecting through a vehicle’s telematics system to take control of safety-critical systems like the throttle, brakes, or steering.

Some security providers use heuristic analysis to look for anomalous behavior in real time and stop the activity. This approach creates rules with weighting and probability to detect anomalies based on previously unknown attacks and is utilized by most computer anti-malware programs. Since the in-vehicle electronics should never be running random unknown programs like a computer or smartphone, Karamba has taken a deterministic approach. During the software build, they analyze and map every possible instruction control flow. In the vehicle, any instruction call that doesn’t match the flow map immediately gets discarded, an approach that should not result in any false positives.

Navigant Research’s Autonomous Vehicles report projects that nearly 5 million autonomous vehicles will be sold in 2025, growing to more than 40 million in 2030. Harnessing the safety benefits of this technology requires every vehicle to be secure and resilient against cyber attacks.

 

Mobility Services Target Driving Less (or at Least More Efficiently)

— September 1, 2016

CarsharingThe problem of urban congestion includes both too many cars simultaneously on the road and too few places to park them. New mobility services from Ford and Lyft are using data analytics and last-mile ridesharing to solve these twin challenges.

Increasing urbanization (82% of people now live in urban areas in North America, according to the United Nations) is intensifying the pressure on city streets and roadways and encouraging more urban dwellers to forego owning a car because of the expense and hassle of finding a place to park. Realizing that vehicle sales to city residents may start to flatten, automakers (including Ford) are diversifying their revenue streams with mobility services.

The recently unveiled FordPass app enables any car owner to pre-book a parking space in garages in more than 160 cities. FordPass also includes phone access to humans to help customers get around in traffic or find other mobility options, and the company also opened its first FordHub mobility storefront in San Francisco. When you also consider the company’s FordPay payment service, it’s clear that the automaker isn’t afraid to borrow from a certain Cupertino company’s playbook. (What’s next, the iFordFone?)

Autonomous Future

Ford also continues to march toward releasing a fully autonomous vehicle. The automaker recently invested in lidar manufacturer Velodyne’s autonomous sensing technology. Ford also announced its intention to produce a fully autonomous car by 2021 for use in ridesharing services. Uber, Lyft, and many other companies see taking those pesky compensation-seeking drivers out of the equation as the future of ridesharing.

Navigant Research forecasts that annual mobility services revenue will reach $4.8 billion in 2020. Automakers will play a significant role in these services, which include carsharing and ridesharing services, congestion charging programs, EV charging services, intelligent traffic management, and smart parking systems.

Smart Urban Mobility End-User Services Revenue by Region, World Markets: 2015-2024

Mobility(Source: Navigant Research)

If an autonomous vehicle is electric, it would reduce urban emissions while also addressing the problem of limited parking. If used to get people to and from mass transit stations, ridesharing programs can reduce the overall vehicle miles traveled by removing trips into the city core. Such is the case in the Denver suburb of Centennial, where light rail customers can request a free Lyft ride if they live near the Dry Creek train station. While using tax dollars to put people in private cars may seem counterintuitive, if it increases the utilization of light rail, it can be viewed as a net positive in solving the last mile challenge and reduce the cost when compared to limited-use bus services. Employees who work for XOJET, which provides luxury rides above the clouds, can also now access Lyft to get to and from their hotels and airports while they are accommodating the jet-setter crowd.

 

Ford Sets a Date for Its Autonomous Vehicle Future

— August 19, 2016

Connected VehiclesOn August 16, Ford held a press conference to announce its plan to launch a fully autonomous vehicle in 2021. Even though the response at the live event was strangely unenthusiastic, there were a number of points that were important for the future of autonomous vehicles and the automotive industry in general.

The headline news was that in 2021, Ford intends to launch a Level 4 (SAE Standard J3016) fully autonomous vehicle. To clarify the nature of the car, CEO Mark Fields made it clear that it would not have a steering wheel or control pedals, even though last year Ford said it had no plans to sell wheeled pods in which people are merely along for the ride.

The company also said that it would be several years after 2021 before individuals can buy it; it is aimed at carsharing and ridesharing fleet operators. Ford Smart Mobility LLC may become one of the first customers. Ford and GM are already piloting their own systems on shuttles for their employees, as noted in a blog earlier this year by my colleague Sam Abuelsamid.

Skipping a Step

Ford also said it would continue to develop and improve its driver assistance features up to Level 2 (partial automation), but it would not be introducing any vehicles with Level 3 (conditional automation) because company researchers had concluded that there was no safe way to ensure that drivers would remain alert enough to resume control in an emergency after an extended period of automated driving. Ford vehicles in the future will either have a range of assistance features or be driverless.

This is a change from the gradual automation theme that has prevailed in the industry until now, although Ford has been saying for the past year that it doesn’t believe that Level 3 is viable. Solving the Level 3 handover issue has been an important topic at recent technical conferences, and Ford has now confirmed its position. While most other OEMs have been working on Level 3, many are now coming around to the idea that the Level 2 to 4 jump is inevitable.

Although convenience and mobility were the focus of the announcement, Ford also acknowledged that safety is a big part of the reason to promote more driver assistance and eventually fully autonomous vehicles. Providing mobility to those without access today, such as the elderly and infirm, was another of the high-level goals. There are also potential opportunities in local package delivery.

Future Investments

Also included in the press announcement were investments in a series of companies providing key pieces of the future autonomous vehicle:

  • Velodyne: A supplier of lidar sensors
  • SAIPS: An Israel-based computer vision and machine learning company
  • Nirenberg Neuroscience: A machine vision platform for performing navigation and object recognition
  • Civil Maps: A provider of high-resolution 3D mapping capabilities

However, Ford made it clear that it was not interested in simply installing autonomous driving software developed elsewhere. It sees its future as a system integrator and will keep most of the development and integration roles in-house.

When asked about powertrain for this new vehicle, Ford said that it would leverage one of its global platforms, but would not confirm whether it would be all-electric or not. The company noted that it has experience with hybrid drive as well as electric and the powertrain has not yet been chosen.

Ford intends to expand from being primarily a vehicle manufacturer to become a mobility company and has drafted a timeline for this shift. This aligns with Navigant Research’s Transportation Outlook white paper that was published in early 2016, and the timing validates the forecasts in our Autonomous Vehicle reports. It will be interesting to see how other OEMs react.

 

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