Distracted driving — the stats are alarming

I was driving to work the other day when I heard something on the radio that almost made me drop my smartphone. The Ontario Provincial Police (OPP) announced that, for the first time, deaths attributable to driver distraction outnumber those caused by impaired driving. So far this year, on roads patrolled by the OPP, distraction has led to 47 deaths, while impaired driving has led to 32.

This stat drives home the need for dramatically better head-unit integration of services that drivers would otherwise use their phones to access. This isn't anything new to QNX. We've been working with our partners to provide all the necessary elements to enable this integration through technologies such as HTML5, Qt, iPod out, MirrorLink, and Bluetooth. All these technologies can help create systems that minimize driver distraction but they represent only part of the solution. Pushing buttons on your head unit, combined with smart HMI design, does help, but it's not a panacea.

To truly help drivers keep their eyes on the road we have to minimize the time they spend looking at the infotainment display. Multi-modal HMIs built from the ground up with the assumption that high-quality speech recognition and text-to-speech are available will drastically change the way drivers interact with their infotainment systems. For instance, such HMIs could read your texts and emails aloud to you; they could even let you dictate responses at the appropriate time. But really, the possibilities are endless. And on the topic of talking to your car, we're constantly working with our partners to enrich the speech capabilities of the QNX CAR Platform. But more on that in an upcoming post.

By the way, I wasn't really using my smartphone while I was driving. That's illegal here. Not to mention incredibly dumb.

Seminar: managing the growing amount of software in cars

It’s no secret that the amount of software in automobiles is growing rapidly — as is the challenge of maintaining it reliably and efficiently. At QNX Software Systems we focus on areas like infotainment, telematics, clusters, and ADAS, but our long-term FOTA partner, Red Bend Software, takes a more holistic view, working with companies like Vector Informatik to extend FOTA all the way down to ECUs.

To help automakers and tier one suppliers manage their software deployments more efficiently, Red Bend is hosting a seminar Friday September 27 at the Westin Southfield Detroit. Speakers will include representatives from Strategy Analytics, Texas Instruments, and Vector, not to mention our own Andy Gryc. You can register on the Red Bend website.

New Mercedes-Benz Concept S-Class Coupé sports QNX-powered infotainment system

Paul Leroux

All-digital instrument cluster and head unit based on QNX CAR Platform

Did you ever lay your eyes on something and say, “Now, that is what I want for Christmas”? Well, I just said it — in response to a set of wheels. But holy turbochargers, what wheels! Not to mention everything else.

If you’re wondering what fueled this sudden rush of automotive desire, here’s a glimpse:



And here’s a bird’s-eye view:



And here’s a peak at the oh-so-gorgeous interior:


All images copyright Daimler AG

Mercedes-Benz took the wraps off this car, the new Concept S-Class Coupé, earlier this week. And just a few minutes ago, QNX and Mercedes revealed that the car’s infotainment system is based on the QNX CAR Platform.

This isn’t the first time QNX and Mercedes-Benz have worked together. Besides providing the OS for various Mercedes infotainment systems, the QNX automotive team has worked with Mercedes-Benz Research & Development North America since the early 2000s, providing the group with advanced technologies for the specification and prototyping of next-generation vehicle electronics. The infotainment system in the Concept S-Class Coupé is the latest — and arguably coolest — product of this long collaboration.

The Concept S-Class Coupé also packs a serious power plant: a 449 hp Biturbo V8 with peak torque of 516 lb-ft. And it offers driver-assistance technologies that are, quite literally, forward looking. Here is a sampling of what's inside:

• Two 12.3-inch displays
• Touchscreen showing four world clocks
• Stereo camera offering 3D view of the area in front of the car
• "6DVision" to detect the position and movement of objects in front of the car
• Variety of assistance systems to monitor surrounding traffic

I’m only touching the surface here. For more details on the car, visit the Mercedes-Benz website. And before you go, check out the press release that QNX issued this morning.

Why doesn’t my navigation system understand me?

A story where big is good, but small is even better.

Yoshiki Chubachi

My wife and I are about to go shopping in a nearby town. So I get into my car, turn the key, and set the destination from POIs on the navigation system. The route calculation starts and gives me today’s route. But somehow, I feel a sense of doubt every time this route comes up on the system...

Route calculation in navigation uses Dijkstra's algorithm, invented by Edsger Dijkstra in 1956 to determine the shortest path in a graph. To save calculation time, navigation systems use two directional searches: one as the starting point and the other as the destination point. The data scheme that navigation systems use to represent maps consists of nodes, links, and attributes. Typically, a node represents a street intersection; a link represents the stretch of road, or connection, between two nodes; and attributes consist of properties such as street name, street addresses, and speed limit (see diagram).

Features of a map database. From Wikipedia.

As you may guess, it can take a long time to calculate the shortest path from all of the routes available. The problem is, automakers typically impose stringent requirements on timing. For example, I know of an automaker that expected the route from Hokkaido (in northern Japan) to Kyushu (in southern Japan) to be calculated in just a few seconds.

To address this issue, a system can use a variety of approaches. For instance, it can store map data hierarchically, where the highest class consists of major highways. To choose a route between two points, the system follows the hierarchical order, from high to low. Another approach is to use precalculated data, prepared by the navigation supplier. These examples offer only a glimpse of the complexity and magnitude of the problems faced by navigation system vendors.

An encouraging trend
Big data is the hot topic in the navigation world. One source of this data is mobile phones, which provide floating car data (current speed, current location, travel direction, etc.) that can be used by digital instrument clusters and other telematics components. A system that could benefit from such data is VICS (Vehicle Information and Communication System), a traffic-information standard used in Japan and supported by Japanese navigation systems. Currently, VICS broadcasts information updates only every 5 minutes because of the bandwidth limitations of the FM sub-band that it uses. As a result, a navigation system will sometimes indicate that no traffic jam exists, even though digital traffic signs indicate that a jam does indeed exist and that service is limited to the main road. This delay, and the inconvenience it causes, could be addressed with floating car data.


An example of a VICS-enabled system in which traffic congestion, alternate routes, and other information is overlaid on the navigation map. Source: VICS

During the great earthquake disaster in East Japan, Google and automotive OEMs (Honda, Nissan, Toyota) collaborated by using floating car data to provide road availability — a clear demonstration of how can big data can enhance car navigation. Leveraging big data to improve route calculation is an encouraging trend.

Small data: making it personal
Still, a lot can be accomplished with small data; specifically, personalization. I may prefer one route on the weekend, but another route on a rainy day, and yet another route on my wife's birthday. To some extent, a self-learning system could realize this personalization by gauging how frequently I've used a route in the past. But I don’t think that's enough. As of now, I feel that my navigation system doesn't understand me as well as Amazon, which at least seems to know which book I’d like to read! Navigation systems need to learn more about who I am, how well I can drive, and what I like.

Personalization resides on the far side of big data but offers more convenience to the driver. The more a navigation system can learn more about a driver (as in “Oh, this guy has limited driving skills and doesn’t like narrow roads”), the better. It is best to store this data on a server; that way, the driver could benefit even if he or she switches to a different car or navigation system. This can be done using the latest web technologies and machine learning. Currently, navigation systems employ a rule-based algorithm, but it would be interesting to investigate probability-based approaches, such as Bayesian networks.

I’m looking forward to the day when my navigation system can provide a route that suits my personal tastes, skills, and habits. Navigation suppliers may be experiencing threats from the mobile world, including Google and Apple, but I think that returning to the original point of navigation — customer satisfaction — can be achieved by experienced navigation developers.

Yoshiki Chubachi is the automotive business development manager for QNX Software Systems in Japan

QNX and the W3C: setting a new standard

For almost two years, you’ve heard us talk about HTML5 in the car, particularly as it applies to the QNX CAR Platform for Infotainment. And now, we're taking the next step: working with the entire automotive community to develop a standard set of JavaScript APIs for accessing vehicle sensor information.

Andy Gryc (that’s me of course) and Adam Abramski (from Intel and representing GENIVI) are co-chairs in the World Wide Web Consortium (W3C) Automotive and Web Platform Business Group. Yes, our group name is a mouthful. But the translation is that Adam and I are working with W3C group members to create a standard that everyone can agree on.

Between GENIVI, Tizen, Webinos, and QNX, four different APIs are in use today. So what’s the process? All of these APIs have been submitted to the W3C group members as contributions. Those contributions form the groundwork, creating a baseline for where we need to go. Collectively as a group, we need to merge these four APIs — figure out the commonalities and harmonize the differences to create a new standard that takes the best features of all the proposals.

This effort takes some time, but the group intends to complete a first draft by December this year. Either Tina Jeffrey (my colleague, who’s doing some of the heavy lifting) or myself will be posting our progress here, so keep an eye out for our updates!