Her – Movie Star and the Future of Mobility
“Her,” nominated for the Best Picture Oscar, demonstrates the power of artificial intelligence. In the film, “Her” is an operating system enhanced with expert systems, similar to the way that Android is enhanced with applications such as Google Maps. “Her” is also a learning system with access to terabytes of information in the cloud. Using the voice of Scarlett Johansson, voice recognition and response has never been more appealing.
While we may be years, or decades, from all the capabilities demonstrated in the movie, our 2014 mobility apps demonstrate how learning systems are already improving our daily travel. With more than a dozen mobility apps on my smart phone, and living near thousands of software companies in Silicon Valley and San Francisco, I witness capabilities of “Her” that are now in use and will increasingly be integrated into a single application for better transportation.
I frequently use Google Maps to compare the travel time of driving versus using transit. When driving, the map application guides me with detailed driving directions. When traveling from one end of the SF Bay to another, Google Maps provides me with the optimal route of walking, taking a bus, taking BART commuter rail, then the bus of another transit system and a walk to a destination. New apps, like RideScout, do the comparison for me, with realtime access to hundreds of transit systems, car share, ride share, and bike share programs. Although RideScout is an imperfect beta from a start-up looking for funding, it is an important step towards making my smartphone a mobility assistant.
When driving, if my Nissan LEAF is low in electric range, there are over a dozen apps to guide me to nearby charging stations, tell me in advance if the charge station is available, reserve the charge space and manage any payment. At other times, a parking app can take me to the least expensive parking garage.
Cars are rapidly advancing beyond my three-year-old electric vehicle. I have driven Toyota cars that keep me from drifting to the next lane and slow if I am to quickly approaching the car ahead. I have driven Fords that park themselves. 2014 cars are networks of processors on wheels with millions of lines of software code communicating with other cars and cloud information.
Google’s latest demonstration of an autonomous electric vehicle is scaring automakers more than Tesla’s success. Google has self-driving cars on the road, which is already legal in California providing that a human sits behind the steering wheel, just in case. The past years have shown these vehicles safer than those driven by humans. The future of cars is a future of autonomous vehicles. The future of how we travel is more than cars.
Were I living in King of Prussia and regularly commuting to Philadelphia, I might use my employer’s internal website to arrange ridesharing. Were I traveling by myself to a meeting in Bethesda, Maryland, I might use a few apps to guide me there. For ridesharing, I could use a rideshare app such as eRideShare, or Ridester, or craigslist, then Amtrak’s app, then Metro’s. In the future, a single system such as “Her” could manage all the travel, payments, and rescheduling for delays. Such a learning system would also know when I would prefer to teleconference rather than travel, even preparing for the meeting with document downloads and presentation preparation.
In major cities, for tens of millions, a car is not something to own, rather it is a service to use. Apps from Hertz, Enterprise, and Budget are used to reserve cars for rental or car sharing. When I was in San Diego, I used car2go, a carsharing innovator, to find the nearest electric Smart Car. I walked a block, used a membership card to unlock the unattended EV, drove it 3 miles to my final destination, logged off and walked away. Point-to-point car sharing is a reality, with a growing percentage of the fleet being electric.
Currently, a significant problem with point-to-point car and bike sharing is that vehicles get clustered in the wrong places. At the start of the day there may be an adequate number at a transit center, by midday there’s none. Self-driving cars may solve that problem. When I took a test ride of the General Motors EN-V, the demonstration 2-seat electric vehicle had the ability to arrange itself in a convoy with other vehicles and reroute to a point where the vehicles are needed. Early applications of self-driving vehicles could include college campuses, carsharing and taxi service.
Where I live, rail, cars and even buses are increasingly electric powered, not diesel and gasoline powered. Much of their electricity comes from renewable sources such as hydropower, solar, wind, and geothermal. Electric drive systems are far more efficient than gasoline engine drive systems. Even as population and workforce increase, we are seeing a decrease in the use of petroleum fuels and of emissions.
Not everyone is ready to embrace a future of a smart apps, artificial intelligence, and electric vehicles. We have all had to reboot our computer. More than once I’ve screamed “operator” into the telephone desperately wanting to talk to a live person rather than continue with mind-numbing voice menus. At a recent urban planning meeting, the conversation turned to the dangers of self-driving electric cars making it too easy for planners to avoid investing in transit-oriented development.
Mobility apps continue to improve, especially for urban transportation. For many of us, our weekly travel is multimodal, as we shuttle between suburbs and urban environments. At times a car is faster, at other times rail and bus. A single and integrated application, like “Her,” could learn our preferences and seamlessly navigate us through bus, rail, shared vehicles, new modes of travel, and telepresence.
In the future, when you want the fastest travel with least emissions, you’ll just ask “Her.”
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Advanced Urban Visioning doesn’t conflict with government-required planning processes; it precedes them. For example, the AUV process may identify the need for specialized infrastructure in a corridor, while the Alternatives Analysis process can now be used to determine the time-frame where such infrastructure becomes necessary given its role in a network.
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