There is something to be said for being in control of your car from instant to instant. First, there is a certain pleasure for most of us in choosing, owning and driving our own vehicle. Our constant attention to the road, its condition, and other vehicles’ behavior is required, so that surprises are minimized and dangerous situations are more readily anticipated and responded to. On the other hand, there are those visionaries who dream of getting into a yet-to-be-developed vehicle that will transport them from their suburban driveway to a parking garage in downtown Manhattan without their needing to touch the steering wheel or depress the gas or brake pedals.
Serious experimentation is underway by Google, Tesla Motors and others to at least approximate this objective-the driverless or “self-driving” car. Optimists cite the successful automated guideway transit (AGT) systems as a rationale for their high expectations for the self-driving car. Yet there are important differences.
AGT systems can be based on traditional running rails serving as the guideway, or the guideway can be separate from the running surface, linked via a slide running along the guideway surface to steer the running wheels. A non-physical “virtual” guideway, detected by sensors on the vehicle, may also be used.
How They Differ
There are major differences between AGT systems and self-driving (autonomous) vehicles that may dampen the enthusiasm of self-driving proponents. First, for the self-driving car there is no physical guideway. If a “guideway” can be construed, it is not fixed, but dependent on external signals, which are subject to change and may sometimes be missing or erroneous.
In urban high-traffic areas, self-driving cars would be sharing the roads with conventional owner-driven vehicles, commercial vehicles, and emergency vehicles. Lane changes would be required at frequent and unpredictable times. Many AGT installations are point to point, as at airports to transport passengers from remote parking areas. Thus they do not encounter the sharp turns and complex routing encountered by self-driving cars.
Automated Subway and Skyway Systems
Several automated urban transit systems are also viewed as positive models by advocates of self-driving cars. Among those that can operate completely automatically are the Paris Metro, the Rome Metro, and the Budapest Metro. Onboard personnel may respond to certain passenger requests, but are not involved in obstacle detection, speed control, door operation, or emergency response.
The San Francisco Bay Area Rapid Transit (BART) system that began operations in 1972 does not quite meet the fully automatic definition. Originally intended to operate its trains without human intervention of any kind, that did not happen-perhaps due in part to an accident in which a two-car train under automatic control ran off the end of the line at Fremont. Staff on board now operate the doors but normally do not control operation of the train itself.
Glitches and Hurdles
Google began road tests of its self-driving Lexus and Prius vehicles in 2009. Beginning in May 2010, these autonomous vehicles were involved in 16 accidents. Most of them occurred in downtown Mountain View, and all were caused by humans, not by the autonomous cars themselves, according to the California DMV. In one case, a Google Lexus was braking for a traffic light and the car behind it rear-ended it at 17 mph.
AGT systems, unlike those for self-driving cars, are designer-controlled and self-contained. But the latter include road signs, lane markings, road damage, etc. When Tesla Motors tested its “autopilot,” designed to adjust speeds, change lanes, and steer automatically, it found the system unable to identify the correct lane on a stretch of the freeway near LAX because of poor lane designation. Infrastructure improvements that might permit successful testing of some self-driving features are notably costly and hard to obtain. (I drive daily past the exit of the local high school on a two-way road whose once prominent center line has been completely worn away. My notification of the town highway superintendent of this fault has been disregarded for weeks. I am hoping that new student and faculty drivers unfamiliar with the road will not stray into oncoming traffic. Yet a self-driving car exiting the high school lot might easily find itself in the wrong lane.)
The “guideway” for self-driving cars is based on pre-programmed route data, so temporary or recently installed traffic lights are ignored. Complex intersections may be problematic, causing the car to switch to a super-cautious mode and, presumably, inviting the real driver to take over. The route cannot be identified in snow or icy conditions. Unexpected but harmless debris on the road may cause the car to veer unnecessarily and without warning. Certain serious obstacles, like potholes, may not be detected. A police officer or emergency worker signaling the car to stop may not be discerned using the present technology. Other problems in a workable self-driving car system might relate to unexpected actors, including cyclists, pedestrians, and dogs and cats, not to mention standby drivers in the autonomous cars who are texting or drug-impaired.
Many critics of driverless vehicles are also concerned that it may be difficult or impossible for the automated system to make appropriate ethical decisions in complex emergency situations-as, for example, when converging on a stalled school bus, electing to brake and possibly ram it at a nominally low speed, as opposed to veering sharply off the road into a sheer rock face that would very likely critically injure the human “driver” of the automatic car.
Finally there is the potential competition between self-driving cars and real drivers, involving unexpected behavior by the self-driven car that might encourage road rage or at least provoke the inherent feeling of superiority on the part of us real drivers. As one noted online, “I say we are not ready for a fleet of Sunday drivers who actually obey the speed limit.”
A Reasoned Approach
Toyota recently entered the picture with a plan of its own. Its research, to be centered at the artificial intelligence laboratories of MIT and Stanford, will be focused on the goal of intelligent cars that augment but do not replace their drivers. They may adopt a limited number of the features that a totally self-sufficient driverless car might have, such as detecting a ball bouncing into the street and automatically braking. Unlike Google and Tesla, Toyota appears to support the role of keeping the driver in charge, but protected from serious accidents by computer intervention.
The cards appear stacked against the self-driving car because it must navigate an ill-defined, fluid environment that constitutes a far less reliable “guideway” than that of a fixed guideway system.
You may not share my skepticism, but on balance, I can’t believe our streets will ever be filled with self-driving cars. Nor do I think that when you acquire your first Aston Martin or Lamborghini that you’ll even briefly entertain the notion of letting it drive itself.
Your comments are welcome.
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Note: The 2015 International Conference on Connected Vehicles and Expo (ICCVE) in Shenzhen, China, covered technology, policies, economics, and social implications of connected vehicles-including intelligent and autonomous vehicles-and cybersecurity in vehicles and transportation systems. The 2016 ICCVE is scheduled for 24-28 October in Seattle, Wash.
Donald Christiansen is the former editor and publisher of IEEE Spectrum and an independent publishing consultant. He is a Fellow of the IEEE.