GIS in Transportation—Research Road Map
GIS-T 2029: Roadmap Challenge
Val Noronha
Remember 1989? The Berlin Wall, the Cold War. Superclocked desktop computers ran Lotus 1-2-3 at 16 MHz, 640×480 16-color VGA graphics cards were rocking the PC business, we backed up the choicest files from our 30 MB hard drives on to 720 KB floppies, e-mail ran on 600 bps modems, laser printers cost $2,000 and GPS $10,000. To check facts we thumbed through encyclopedias.
Fast forward from 1989 to the present, and compare our technological environment. Now with that 20-year evolution in mind, extrapolate 20 years into the future. What do we see? It’s hazardous to go on record with a 20-year forecast, only to have someone introduce it in a killer app next week, but here are some provocative dimensions and scenarios to consider:
- 20% of the population is over 65—compared with 13% in 2009.
- Gasoline is passé. Only electric vehicles are permitted on public roads. Driving is semi-autonomous. Accidents have been reduced dramatically by collision-avoidance systems; traffic fatalities are usually due to system malfunctions.
- Global warming has changed the face of the planet, the availability of water and the distribution of agriculture, pests and disease. Old weather models are no longer valid. In Wisconsin they’re more concerned about tornadoes than blizzards. Emergency evacuations/relief operations are more frequent.
- On-line shopping has marginalized in-store retail. Freight and personal travel patterns, and commercial land use, are consequently very different.
- Ubiquitous sensors (“smart dust”) are linked together in mesh networks. The flood of data from those sensors is intelligently sorted and distilled into useful information for those who need it. There’s ubiquitous computing … inexpensive, paper-thin display screens, powered by solar panels, body heat/kinetics and batteries that last forever. There’s ubiquitous ultrabroadband wireless communications. You can get information on anything, delivered anywhere, in multimedia. Everything that moves is tracked, and congestion is managed by user fees. The census has lost out to sensors.
- Today’s desktop functionality and more is encapsulated in a thumb-sized e-concierge: phone, camera, communicator, navigator, weather monitor, stock market advisor, biometric ID/e-wallet, garage door opener and house key, hazmat sniffer, blood pressure/sugar monitor and medical file. The e-co communicates smoothly with transit and airline schedules, receives instructions from law/traffic-enforcement, hails cabs, sends messages if you’re running late, orders health-appropriate pizza, gathers and compares prices on planned purchases, and in collaboration/conspiracy with other e-cos, sets up the most exquisite blind dates.
- Reconstruction in 4+ D of the past 20 minutes of an event by synthesizing multiple camera views, positioning, sound, temperature and other environmental metrics. 4+ D simulation of the next 20 minutes in conjunction with process models—e.g. will the aging bridge be able to withstand the traffic during this emergency evacuation along a secondary route? Results of the simulations are broadcast to potentially affected e-cos, staggering the traffic.
- Advanced optimization, simulation and decision support systems advise planners on the ideal placement of facilities, from swimming pools to rail lines. On their way home from work, Joe and Jane Public participate in a consultation on a controversial power corridor alignment decision, using their e-cos from the comfort of their seats in a maglev transit car. In a real-time exchange with dozens of others, they sketch alternative alignments; the planners’ system evaluates (based on yesterday’s and today’s data, not 10-year-old census figures), reports and communicates results to the remote participants. [In other links, Fred elaborates on elements of the consultation/decision process; Harvey’s Transport 2.0 article also addresses this, and Jack Dangermond’s Where 2.0 address suggests that the public transparency and accountability enabled by these technological scenarios is what democracy is all about].
What is the role of GIS-T in this transportation future? What is the research trajectory that takes us from now to then?
Think about your area of specialization, whether technical (image processing, microsimulation, etc) and/or a business area (operations, emergency management, etc). How is the future taking shape in your field? What are the essential stops along the way? What are the intersections and necessary links to other disciplines? Between the public and private sectors? What are the challenges to be overcome? When do they need to be addressed—in 2 years or 20?
