Got an Iphone recently so sometime I wonder through the tons of applications made for the iPhone and often they are very unexpected and crazy.
By the way, today my mind got the “Wow, the iphone is the perfect tool for dynamic carpooling, being GPS-enabled!” (dynamic carpooling being an old interest of mine)
Of course there are already some applications for iPhone for carpooling: Avego and Carticipate seem the most advanced. What is amazing of iphone for carpooling is that you don’t have to enter your common routes by hand but have your iphone do all the work for you.
The app works by tracking a user’s driving habits and then matching them up with people looking for rides. It’s kinda like Match.com for potential serial killers and would be victims. Using the GPS-enabled iPhone, the app will track common routes the user takes. The app then notifies the user of potential victims..er, riders. From there the app will suggest a place they can meet. It will also show a picture of the person so you use a little hot-or-not in your decision making. (from cleantechnica.com)
By the way, we are eventually starting with Jungo in Trento. Jungo is a way to encourage hitchhiking by giving members a card which gives additional security. At the moment it is not empowered by ICT devices such as Iphones but this might change in future. First membership cards are arriving and Friday we were interviewed by the RAI television, and we did some holloywoodesque let’s-mimic-how-jungo-works camera shots. Lots of fun being an actor!
Interestingly for 2 months, 6 volunteers (called Kerouac) have been testing dynamic ridesharing readiness here in Trentino, along the Trento center – Mesiano – Povo route. For the first 4 weeks they have been doing normal hitchhiking twice a day while for the second 4 weeks, after some advertisement about Jungo, they have been doing hitchhiking using the Jungo cards. Overall they collected 750 rides!
Interestingly their average waiting time (AWT) decreased. And interestingly as well, females have smaller AWT. Males moved from a AWT of 22 minutes during the first 4 weeks to 11.4 minutes while females moved from 6 minutes to 2.7 minutes! Well, 2.7 minutes is definitely much less time than waiting for the bus!!!
This difference of performances based on gender reminded me of some research about this I read time ago.
In Sharing Nicely: On shareable goods and the emergence of sharing as a modality of economic production (best paper I ever read by the way, and released under Creative Commons!), Yochai Benkler reports some research from the paper “Mating Habits of Slugs: Dynamic Carpool Formation in the I-95/I-395 Corridor of Northern Virginia” by Frank Spielberg & Phillip Shapiro (a paper I was not able to download because it’s behind a gated journal, can you help me?):
In a deviation from gender-neutral pickup practices, solo women will not usually enter a car with two men already in it. “Unrelated” slugs on a line, however, will match up, whether male or female, irrespective of the gender of the driver.
This underscores the fact that personal security fears may be a serious obstacle to carpooling with strangers.
The matching practices suggest that security is improved by combining more than one rider with each solo driver, where the riders themselves are not preorganized in groups. Each pair—driver plus each rider, and both riders vis-à-vis the driver—provides each individual with some security against an aggressive stranger. The importance of strength in numbers and lack of personal relationship is indicated by the fact that solo women will join two men in a car if the woman and man were both in line and no relationship between the two men is indicated.
Carpoolers on this model seem to assume a prevalence and distribution of aggressive proclivities in the population that places a low probability on two randomly associated individuals cooperating aggressively. Given such a model of the prevalence and distribution of aggressive tendencies, fully impersonal cooperation can then be seen as safer than partially impersonal cooperation, where some subset of participants have a preexisting relationship.
And on a similar line, I read this table from “Car pooling clubs: solution for the affiliation problem in traditional/dynamic ridesharing systems” by Gonçalo Correia, José Manuel Viegas which reports evidence from “Levin, et al. Measurement of ‘Psychological’ Factors and their role in Transportation behaviour” (another paper behind gated journal I need help with):
Research by Levin, et al  at the University of Iowa reached the conclusion that gender of the potential poolers was of little consequence when the other part was an acquaintance, but became of great consequence when the other part was a stranger, see Table 1.
As can be seen in the table, the desirability of ride sharing decreases with the increase of strangers in the pool, especially for females. These results suggest that gender and prior knowledge of the potential pooler combine to determine the desirability of the other person for ridesharing. Moreover, different combination of these factors can lead to very different results: when the driver is a Female there’s a great difference between transporting two acquaintances-one nonaquaintance (10.84 points) and three nonaquaintances (3.49 points).
Number of Riders
Two nonacquaintances – one nonacquaintance
One nonacquaintance – two nonacquaintances
Table 1. Carpool Desirability (15 point scale) as a function of gender and Acquaintance-ship of Potential Ridesharers (Source: Levin, et al., 1976)
Finally, while browsing for these links I found a two-days workshop titled Real-Time Rides: A Smart Roadmap to Energy and Infrastructure Efficiency held very recently at MIT which contains most of the pointers to researchers and companies currently working on dynamic carpooling and the opportunities opened about it by new GPS-ready devices.