Fuel Optimization, Geospatial and On-Board Navigation
Since the Large Hadron Collider at CERN could generate Micro Black Holes (MBH), Strangelets and Monopoles, I have been finding it hard to get motivated to blog about geospatial stuff – since there may not be geospatial stuff to blog about – or an audience to read about it. Of course, I think that the most insightful comment about the potential of the Hadron Collider was produced by …Frank Sinatra. Well, actually his song writers Leigh and Springer who authored “How Little We Know”. It goes like this –
“How little we know
How much to discover
What chemical forces flow
From lover to lover
How little we understand what touches off that tingle,
That sudden explosion when two tingles intermingle.”
It’s those tingles at the Hadron Collider that have me worried. Case closed!
However, I found out that the Hadron Collider and its beam will not be active until mid-October at the earliest and perhaps not until the beginning of 2009. Faced with this gift of six months, I decided I’d better start-up again. Of course, there is also the possibility that the LHC startup creates no threat to our continued existence– so I thought I would turn to the next biggest danger – GAS PRICES.
“Smart” fuel utilization through effective tactics for optimizing distance-biased puzzles seems to me to be the area where geospatial problem solving might have a lot to contribute. I keep looking to see which PND or in-dash navigation system manufacturers come out with fuel saving features, but the leading edge services continue to offer only “gas price maps” and “vanilla” traffic information.
What are some of the interesting “services” that could be incorporated in routing and navigation software/systems to help solve fuel economy problems?
Traffic (optimize to non-traffic bearing shortest route or ones that minimize a vehicle fuel consumption footprint through time and distance optimization).
Slope prediction (fuel economy through automated drive train management)
Fuel economy warnings (based on analysis of drive train diagnostics or even simple distance/time calculations based on GPS readings and car class)
Fuel economy optimized routing (traffic, speed, distance, slope optimiztion).
Optimized Local Search (eliminating false targets, creating direct routes to desired product or service – eliminating ineffective shopping solutions).
Or put another way, would you be interested in a device (in-dash or onboard (PDA or smart phone) that could provide one or all of these services to help reduce your fuel costs? Thinking about these types of solutions shows why in-dash units won’t be going away soon and points to the problems of making smart phones and PDAs viable players in optimizing fuel economy. Maybe ADAS really does have a future? Conversely, there may be ways to finesse fuel-economy” applications on PDAs and smart phones.
Finally, some of the solutions mentioned above may require additional data that is not currently provided by map data providers – like accurate elevation data. Hmmmm. Isn’t that what Intermap is doing? Perhaps this is the explosion when “…two tingles intermingle”?