Archive for March 30th, 2010

You know who you are.

But seriously, this etymological foray into the history of the word chauffeur has me, well, stoked.

Sorry, one of my favorite bits from Henry V. But reader Matt writes in with a confusing (at least to him, and to me upon first glance) yield situation at an intersection in Pennsylvania (Google Map it at: “matsonford road, west conshohocken pa.” Given the mixed messages of the signage, what sayest thou, readers — will you yield?

Matt lays out the scenario below:

When I saw the headline, I thought it was referring to where the Santa Monica freeway intersects with the 405, but alas, it’s a novel interchange configuration, suitable for the Slough-ey, office-park-ey, pedestrian-free places of the world, perhaps some kind of next-century CFI.

(thanks Phil)

Next up for Streetfilms: Ray Kelly?

(Thanks Alan)

As any Traffic reader knows I have a jones for “collective animal mobility.” I recently across an interesting paper, “Traffic and the visual perception of space,” by Petr Šeba, a physicist with the University of Hradec Králové in the Czech Republic.

As he notes:

During the attempt to line up into a dense traffic people have necessarily to share a limited space under turbulent conditions. From the statistical point view it generally leads to a probability distribution of the distances between the traffic objects (cars or pedestrians). But the problem is not restricted on humans. It comes up again when we try to describe the statistics of distances between perching birds or moving sheep herd. Our aim is to demonstrate that the spacing distribution is generic and independent on the nature of the object considered. We show that this fact is based on the unconscious perception of space that people share with the animals.

Here’s how it was done:

In order to verify this hypothesis we organized a simple experiment with pedestrians in a narrow corridor. Using two light gates we measured their velocity and the time interval that elapsed between two subsequent walkers. This enables us to reconstruct the mutual distances and evaluate the distance probability density. The same device and method was used also for a sheep herd moving through an aisle between two near yards. The third source of data are cars moving on a highway in a dense traffic. The velocity and time stamps of the individual cars were obtained by induction loops placed below the roadway.

The probability distribution of distances between objects in all these cases was essentially the same (suggesting, according to the author, a universal mechanism for estimating time-to-collision and its avoidance). Something to consider in those long holiday security lines at the airport.