An anonymous street in Tokyo. As usual in this huge and confusing metropolis, I have absolutely no idea where I am. So my companion casually punches a button on the dashboard of his car, and the latest Japanese consumer electronics wonder beeps into action. It instantly grabs our coordinates from the global positioning satellite system, displays a detailed street map on a dashboard screen, and indicates our position and direction with an arrow. 33 As we navigate the intricate route from Shinjuku to Asakusa, the system continuously updates the display to reflect our current location-automatically rotating and recentering the map to keep the arrow just below the middle of the map and pointing straight ahead. The real city that surrounds us and the video city that guides us are held in perfect coincidence.
But this is just the beginning. A vehicle that knows where it is, and can pull information relevant to its location out of a database of geographically coded information, can do a lot more than display maps. 34 For example, it might look up interesting facts in online guidebooks and read you a commentary on the passing scene. With slightly more sophisticated programming, it could learn what you particularly cared about-the highlights of local history, perhaps, or census information, or the agricultural products of the area-and, like a knowledgeable and attentive companion, it could offer only observations likely to interest you. If you were driving a delivery truck, looking at real estate, canvassing for a political cause, or performing some other specialized task requiring information about passing buildings and their occupants, the system could supply it. For travelers it could deal with some immediately practical concerns -directing you to the nearest gas station or to the closest inexpensive Chinese restaurant, or finding you a bed for the night. And it could tell you what's on and what's open in your immediate neighborhood.
Silicon-smart vehicles can also calculate efficient routes from their current locations to specified destinations. Finding the shortest path through a street network is a straightforward software task (though doing so efficiently can get a bit tricky when the network is large), and whatever information is available about current traffic conditions can be factored in. The chosen route might simply be displayed on a dashboard screen, but it can almost as easily be output as a sequence of instructions from a robotic back-seat driver -"Next left," "You just made a wrong turn," and so on. Integration of some simple speech-recognition capabilities can even allow the driver to ask "What now?"
Not only may vehicles sense where they are in the road system, but the road system may also be equipped with electronic sensors enabling it to detect where the vehicles are. So the old ideas of the tollbooth and the on-ramp meter can be updated; charges for the use of a road can, in principle, be adjusted instantaneously according to the level of road congestion. 35 The task of the smart vehicle then becomes not just one of calculating the shortest or quickest path to a specified destination, but of computing the cheapest path or of finding a reasonably quick route that does not cost too much.In the future, travel through cities will involve continuous information exchange between smart vehicles and smart roadway systems. 36
As I contemplate all this, I recall Roy Rogers and Trigger-an all-terrain vehicle with abundant onboard intelligence. Trigger always knew where he was, could find his way home if necessary, and understood moment-by-moment what his master needed; horse and cowboy functioned as one. But when the horse vanished from everyday life, leaving behind the horseless carriage, the onboard intelligence went too; there was a technological gap to be filled. (Roy obviously didn't have quite the same relationship to his jeep.) Increasingly, now, electronics are doing the job. Soon, our automobiles will be at least as smart as Trigger, and the car-and-driver relationship will return to the cowpoke-and-horseflesh mode. And when they get smarter still, the horseless carriage may evolve into the driverless automobile.
As a result, we are beginning to know and use cities in new ways. Long ago the urban theorist Kevin Lynch pointed out the fundamental relationship between human cognition and urban form-the importance of the learned mental maps that knowledgeable locals carry about inside their skulls. These mental maps, together with the landmarks and edges that provide orientation within the urban fabric, are what make a city seem familiar and comprehensible. But for us artificially intelligent cyborgs, the ability to navigate through the streets and gain access to a city's resources isn't all in our heads. Increasingly, we rely on our electronic extensions-smart vehicles and hand-held devices, together with the invisible landmarks provided by electronic positioning systems-to orient us in the urban fabric, to capture and process knowledge of our surroundings, and to get us to where we want to go.