I am blogging this week at Symposium Magazine.
Yesterday’s post introduced our Value of Reliability study on the HOT lanes of I-394. Today’s Post reports on the findings.
These extend the post Understanding the Irrational Commuter from earlier this month.
Monday’s post was Understanding trade-offs and public trust.
I get interviewed about the reliability measures of the new Urban Mobility Report by Ariel Hart of the Atlanta Journal-Constitution: Atlanta traffic bad but predictable :
“‘People care about this,’ said David Levinson, a professor of civil engineering at the University of Minnesota who researches traffic psychology surrounding reliability. People will even accept more congestion to get more reliability, he said, and he has a mathematical formula to calculate how much.
‘It’s the surprises, the inconsistency of the delay that makes it difficult,’ costing people social capital with colleagues, clients and friends when they are unexpectedly late, he said.”
The reliability ratio, the ratio of the value of reliability to the value of time us about 1, depending on how it is measured. See
Carrion, Carlos and David Levinson (in press) Valuation of travel time reliability from a GPS-based experimental design Transportation Research part C [doi]:
“In the Minneapolis–St. Paul region (Twin Cities), the Minnesota Department of Transportation (MnDOT) converted the Interstate 394 High Occupancy Vehicle (HOV) lanes to High Occupancy Toll (HOT) lanes (or MnPASS Express Lanes). These lanes allow single occupancy vehicles (SOVs) to access the HOV lanes by paying a fee. This fee is adjusted according to a dynamic pricing system that varies with the current demand. This paper estimates the value placed by the travelers on the HOT lanes because of improvements in travel time reliability. This value depends on how the travelers regard a route with predictable travel times (or small travel time variability) in comparison to another with unpredictable travel times (or high travel time variability). For this purpose, commuters are recruited and equipped with Global Positioning System (GPS) devices and instructed to commute for two weeks on each of three plausible alternatives between their home in the western suburbs of Minneapolis eastbound to work in downtown or the University of Minnesota: I-394 HOT lanes, I-394 General Purpose lanes (untolled), and signalized arterials close to the I-394 corridor. They are then given the opportunity to travel on their preferred route after experiencing each alternative. This revealed preference data is then analyzed using discrete choice models of route. Three measures of reliability are explored and incorporated in the estimation of the models: standard deviation (a classical measure in the research literature); shortened right range (typically found in departure time choice models); and interquartile range (75th–25th percentile). Each of these measures represents distinct ways about how travelers deal with different sections of reliability. In all the models, it was found that reliability was valued highly (and statistically significantly), but differently according to how it was defined. The estimated value of reliability in each of the models indicates that commuters are willing to pay a fee for a reliable route depending on how they value their reliability savings.”
Recently Published: Carrion, Carlos and David Levinson (2012) Value of travel time reliability: A review of current evidence. Transportation Research Part A: Policy and Practice 46(4) 720–741.[doi]
Travel time reliability is a fundamental factor in travel behavior. It represents the temporal uncertainty experienced by travelers in their movement between any two nodes in a network. The importance of the time reliability depends on the penalties incurred by the travelers. In road networks, travelers consider the existence of a trip travel time uncertainty in different choice situations (departure time, route, mode, and others). In this paper, a systematic review of the current state of research in travel time reliability, and more explicitly in the value of travel time reliability is presented. Moreover, a meta-analysis is performed in order to determine the reasons behind the discrepancy among the reliability estimates.
Keywords: Variability; Reliability; Travel time; Scheduling; Meta-analysis
Recently published: Carrion-Madera, Carlos, David Levinson, and
Kathleen Harder (2011) Value of Travel-Time Reliability: Commuters’ Route-Choice Behavior in the Twin Cities
“Travel-time variability is a noteworthy factor in network performance. It measures the temporal uncertainty experienced by users in their movement between any two nodes in a network. The importance of the time variance depends on the penalties incurred by the users. In road networks, travelers consider the existence of this journey uncertainty in their selection of routes. This choice process takes into account travel-time variability and other characteristics of the travelers and the road network. In this complex behavioral response, a feasible decision is spawned based on not only the amalgamation of attributes, but also on the experience travelers incurred from previous situations. Over the past several years, the analysis of these behavioral responses (travelers’ route choices) to fluctuations in travel-time variability has become a central topic in transportation research. These have generally been based on theoretical approaches built upon Wardropian equilibrium, or empirical formulations using Random Utility Theory. This report focuses on the travel behavior of commuters using Interstate 394 (I-394) and the swapping (bridge) choice behavior of commuters crossing the Mississippi River in Minneapolis. The inferences of this report are based on collected Global Positioning System (GPS) tracking data and accompanying surveys. Furthermore, it also employs two distinct approaches (estimation of Value of Reliability [VOR] and econometric modeling with travelers’ intrapersonal data) in order to analyze the behavioral responses of two distinct sets of subjects in the Minneapolis-Saint Paul (Twin Cities) area.”
Network Reliability on the Electric Grid (from Miller-McCune Debunking Theories of a Terrorist Power Grab
Hines and Blumsack’s study … shows that the most vulnerable points are the ones that have the most energy flowing through them — like huge power stations or highly connected transformers.
Article Do topological models provide good information about electricity
I think there is something to learn about generalizing network reliability and vulnerability across fields (electricity, transportation, etc.). Network structure, and the underlying technology, matter.