Recent working paper:
This research investigates how land use and road network structure influence home-based single-destination choice in the context of trip chains, using the in-vehicle GPS travel data in the Minneapolis-St. Paul Metropolitan area. We propose a new choice set formation approach which combines survival analysis and random selection. Our empirical findings reveal that: (1) Accessibility and diversity of services at the destination influences individuals’ destination choice. (2) Route-specific network measures such as turn index, speed discontinuity, and trip chains’ travel time saving ratio also display statistically significant effects on destination choice. Our approach contributes to methodologies in modeling destination choice. The results improve our understanding on travel behavior and have implications on transportation and land use planning.
This paper is part of Arthur Huang’s Dissertation.
From Gizmodo: Google Killed Map Traffic Estimates Because It Just Didn’t Work
If you’re wondering how road traffic’s gonna slow you today, don’t turn to Google Maps anymore—the site’s killed its estimates. Not because it wasn’t popular. It turns out those road calculations didn’t exactly correlate to, you know, reality.
The Atlantic describes the discovery of perturbed Maps users, who complained to Google when they noticed the change. Its answer?
[W]e have decided that our information systems behind this feature were not as good as they could be. Therefore, we have taken this offline and are currently working to come up with a better, more accurate solution. We are always working to bring you the best Google Maps experience with updates like these!”
Translation: traffic didn’t work. And as the Atlantic’s Nicholas Jackson asks, how could Google be sucking down so much locational data from Android drivers and be botching it to the point that they pulled it down entirely? [The Atlantic]“
A big defeat for the biggest information provider. But using in-vehicle GPS on mobile phones as a probe is coming, and will eventually get it right (approximately, if lagged). The problem of course is that traffic is dynamic, and even a 5 minute lag will be quite off if there is an incident or something non-steady state. However as a signal of whether things are normal, it probably works.
Information provision is probably best for what an individual will not know from routine behavior—random incidents and unfamiliar territory. The qualitative conclusion that incidents and the unexpected are where the greatest gains from traveler information are to be found reinforces the results from our simulations. Those models show that a low level of probes can provide useful information by rapidly detecting incidents, whereas a much greater number is needed to provide any gains from recurring congestion.
The Washington Post reports on NextGen:
New air guidance system threatened with delays : “Now the Obama administration has embarked on the single most ambitious and expensive
national transportation project since completion of the interstate highway system: a program called the Next Generation Air Transportation System (NextGen).
The NextGen concept sounds simple: Replace an air traffic system based on 60-year-old radar with a satellite-based Global Positioning System (GPS) network that would be far more versatile and efficient. In reality, it is an extraordinarily complex undertaking, threatened with delay by airline fears that the government will not deliver the system in time to justify their expenditures.
NextGen demands the largest investment ever made in civil aviation: between $29 billion and $42 billion for equipment, software and training by 2025. The cost would be shared by a federal government struggling with budget constraints and an airline industry that has been drained by years of recession and high fuel prices. Those tensions over funding threaten to slow the launch of NextGen, despite near-universal support for the program, and delays could prove costly.”
TomTom user data sold to Dutch police, used to determine ideal locations for speed traps — Engadget
BY TIM STEVENS
POSTED APR 27TH 2011 01:53PM
TomTom user data sold to Danish police, used to determine location of speed traps
We like it when the accumulated speed data from GPS devices helps us avoid traffic incidents and school zones. As it turns out, though, there are some other uses for the same stats. Dutch news outlet AD is reporting that such data captured by TomTom navigation devices has been purchased by the country’s police force and is being used to determine where speed traps and cameras should be placed. TomTom was reportedly unaware its data was being used in such a way, but if the police would only agree to sell the data on the location of its speed cameras and traps back to TomTom, why, this could be the beginning of a beautiful relationship.
Update: TomTom has issued a statement, which we have embedded after the break. To be totally clear all this data is being collected anonymously and the police have no idea exactly who is speeding, just that speeding has taken place.
Update 2: We have an English-language video from TomTom CEO Harold Goddijn embedded after the break. In it he says that the company will ‘prevent that type of usage’ of the navigation data going forward. So, no need to turn off the ‘ol GPS when you’re late for work tomorrow morning.
1) Customers come first at TomTom;
When you use one of our products we ask for your permission to collect travel time information on an anonymous basis. The vast majority of you do, indeed grant us that permission. When you connect your TomTom to a computer we aggregate this information and use it for a variety of applications, most importantly to create high quality traffic information and to route you around traffic jams.
We also make this information available to local governments and authorities. It helps them to better understand where congestion takes
place, where to build new roads and how to make roads safer.
We are actively promoting the use of this information because we believe we can help make roads safer and less congested.
We are now aware that the police have used traffic information that you have helped to create to place speed cameras at dangerous locations where the average speed is higher than the legally allowed speed limit. We are aware a lot of our customers do not like the idea and we will look at if we should allow this type of usage.
2) This is what we really do with the data;
- We ask for your permission to collect historical data. You can opt in or opt out and can disable the data collection function at any time.
- If you are using a LIVE device, you receive traffic information in real time and you automatically contribute to generating traffic information.
- We make all traffic data anonymous. We can never trace it back to you or your device.
- We turn anonymous data into traffic information to give you the fastest route available and route you through traffic jams in real time.
- We are working with road authorities around the world to use anonymous traffic information to help make roads flow more efficiently and safer.
- Our goal is to create a driver community capable of reducing traffic congestion for everyone.
Waze is a mobile smart-phone application that lets you see real-time traffic information from other Waze users, and share it. Basically, it uses your smart-phone as a probe. It also lets you update the network (of course if the network is still incomplete, real-time traffic data is almost assuredly sparse). This really depends on critical mass, as I described in this paper:
And lagged information may in some instances be worse than no (or historical average) information.
Arterial traffic available on Google Maps for selected cities (including Minneapolis).
It seems they are doing it from Google Maps for Mobile, and getting automatic feedback of location from GPS-enabled online users (and thereby deriving speed). Clearly this is a good thing for traffic data nerds, and critical mass for arterial travel times is a good thing, even if Google winds up being the dominant provider.