Visualizing Next Generation Routing

The New England Roundtable of CSCMP recently organized a tour of Walgreens’ Northeast Distribution Center (DC). What an amazing facility! Because I live in a Boston suburb and the DC is in Connecticut, I used MapQuest to get turn-by-turn directions and it told me that the trip would take just under 2 hours.

I made it to the tour on time, but it involved significant speeding and stress. The problem was that MapQuest does not factor in rush hour traffic or stretches of road where the speed limit is reduced because of repairs.

Over the years, I have occasionally been absolutely amazed by software applications, such as the first time I saw and used MapQuest. But it is now possible to imagine a next generation routing solution.

In a previous posting, I wrote about Google Maps Navigation and how a driver can use an Android-powered smartphone like a GPS device, docking it into their car or truck to obtain turn-by-turn navigation. Google’s vision is that the smartphone will provide not just verbal directions and a map, but also overlay street maps with satellite pictures and even street-level views. The maps will also show historic traffic congestion. The other nice thing about using an Internet-enabled smartphone is that you don’t have to periodically download current map data into your navigation device.

Additionally, Google is developing a live traffic congestion application. The more consumers that use this service, the better Google’s live traffic congestion detection will work. When a consumer enables Google Maps with My Location, their phone sends anonymous bits of data back to Google describing how fast they’re travelling. Google then combines that person’s speed with the speed of other users on the road, across (eventually) thousands or tens of thousands of phones moving around a city at any given time. The application ends up with a good picture of live traffic conditions. 

So, here is my vision of a routing application for the future. A driver punches in the location they want to go to and turn-by-turn directions are generated along with an accurate estimate of travel time based on current congestion patterns. Applications that plan and route truck fleets would optimize all routes simultaneously based on current congestion patterns, not just historical road speeds as shown on the GPS maps. 

Further, if the application detects a few days of slow travel on a particular stretch of road, it would generate a query: “Why is this stretch of road slow? Is there road construction taking place?” If the answer is yes, the routing application would change estimated travel times until speeds on that stretch of road return to historical normal.

Finally, if unexpected congestion does develop, combining GPS with next generation routing will allow for dynamic routing, for either an individual truck or a fleet of trucks.

What I have described here is not fully possible yet, but it will be in a few years. Descartes, an ARC client, is starting to talk about “MRM 2.0,” which basically combines routing, the power of a network, and GPS data in new and interesting ways. Although what I have described is not exactly MRM 2.0 as outlined by Descartes, it is clear that solution providers also see that new and greatly improved routing applications will become possible in the not too distant future.

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