Travel Time Perception Errors: Causes and Consequences

Congratulations to soon to be Dr. Carlos Carrion (shown in the center of the picture, between alums Nebiyou Tilahun and Pavithra Parthasarthi), who recently defended his Ph.D. Thesis “Travel Time Perception Errors: Causes and Consequences” (a draft of which is linked). He is working as a post-doctoral researcher at MIT/SMART in Singapore.

Travel Time Perception Errors: Causes and Consequences
This research investigates the causes, and consequences behind travel time perception. Travel times are experienced. Thus, travelers estimate the travel time through their own perception. This is the underlying reason behind the mismatch between travel times as reported by a traveler (subjective travel time distribution) and travel times as measured from a device (e.g. loop detector or GPS navigation device; objective travel time distribution) in collected data. It is reasonable that the relationship between subjective travel times and objective travel times may be expressed mathematically as: Ts = To + ξ. Ts is a random variable associated with the probability density given by the subjective travel time distribution. To is a random variable associated with the probability density given by the objective travel time distribution. The variable ξ is the random perception error also associated with its own probability density. Thus, it is clear that travelers may overestimate or underestimate the measured travel times, and this is likely to influence their decisions unless E(ξ) = 0, and Var(ξ) ≈ 0. In other words, travelers are “optimizing” (i.e. executing decisions) according to their own divergent views of the objective travel time distribution.
This dissertation contributes novel results to the following areas of transportation research: travel time perception; valuation of travel time; and route choice modeling. This study presents a systematic identification of factors that lead to perception errors of travel time. In addition, the factors are related to similar factors on time perception research in psychology. These factors are included in econometric models to study their influence on travel time perception, and also identify which of these factors lead to overestimation or underestimation of travel times. These econometric models are estimated on data collected from commuters recruited from a previous research study in the Minneapolis-St. Paul region (Carrion and Levinson, 2012a, Zhu, 2010). The data (surveys, and Global Positioning System [GPS] points) consists of work trips (from home to work, and from work to home) of subjects. For these work trips, the subjects’ self-reported travel times, and the subjects’ travel times measured by GPS devices were collected. Furthermore, this dissertation provides the first empirical results that highlight the influence of perception errors in the valuation of travel time, and in the dynamic behavior of travelers’ route choices. Last but not least important, this dissertation presents the most comprehensive literature review of the value of travel time reliability written to date.

Traffic Congestion and Job Accessibility

KFAI Community Radio in Minneapolis

I was interviewed a few weeks ago by Dale Connelly for KFAI Community Radio. The edited interview (aired April 22, 2013) is below as an MP3 (5:51)

Every so often we get a discouraging report on traffic congestion in metropolitan areas.
The latest rating from Texas A & M’s Transportation Institute gave Washington DC the worst rating for congestion, followed by Los Angeles, San Francisco, New York and Boston. No big surprise there.
But one University of Minnesota professor says counting stationary cars is only part of the story. David Levinson is a professor of civil engineering and author of the Access Across America Study. He told KFAI’s Dale Connelly there’s more to consider when looking at the problem of traffic congestion.
David Levinson holds the Richard P. Braun/Center for Transportation Studies Chair in Transportation at the University of Minnesota. His study, Access Across America, says some of the cities regularly identified as most congested actually have transportation networks that provide good access to jobs. You can see the study online at


Street Improvement Fees

The League of Minnesota Cities writes:

Briefing paper—2013
Minnesota cities and street improvement districts
League position
The League supports HF 745 (Erhardt, DFL-Edina) and SF 607 (Carlson, DFL-Eagan), legislation that would allow cities to create street improvement districts. This authority would allow cities to collect fees from property owners within a district to fund municipal street maintenance, construction, reconstruction, and facility upgrades. If enacted, this legislation would provide cities with an additional tool to build and maintain city streets.

Sounds like a good idea to me. To be fair, there are opponents. The stated opposition seems odd. They oppose this tool because it is not voter approved, yet I don’t ever recall voting on property tax hikes, or sales taxes for stadia which are imposed on me. The real opposition is because it shifts the burden from one class of taxpayers to another, hopefully so that it is more closely aligned with benefits.
At any rate, our research on the similar Transportation Utility Fees is:

Drew Kerr has a pay-walled article at Finance & Commerce here.

Evaluation of the Minnesota Road Fee Test

MnDOT has posted the evaluation of the recent Mileage Based User Fee test: Connected Vehicles for Safety, Mobility, and User Fees: Evaluation of the Minnesota Road Fee Test:

“In 2007 Minnesota legislature approved a $5,000,000 project in order to demonstrate technologies which will allow for the future replacement of the gas tax with a fuel-neutral mileage charge. The Minnesota Department of Transportation (MnDOT) organized a study to examine the implementation and operation of a mileage based user fee program (MBUF), which might allow for the supplementation or replacement of traditional gas taxes. The primary objectives of the study were to: assess the feasibility of using consumer devices for implementing Connected Vehicle and MBUF applications. These applications included localized in-vehicle signing for improving safety, especially for rural areas, and the demonstration of the proposed Connected Vehicle approach for providing location-specific traveler information and collecting vehicle probe data. The study consisted of 500 voluntary participants, equipped with an in-vehicle system comprised of entirely commercially available components, primarily a smartphone using an application capable of tracking participant vehicle trips. Successfully meeting its primary objectives, the system was capable of assigning variable mileage fees determined by user location or time of day, as well as presenting in-vehicle safety notifications which had measureable effect on the participants driving habits. MnDOT contracted Science Applications International Corporation (SAIC) to perform research for the project and an evaluation of its findings. This document is the final report from SAIC, providing a summary of the study, its findings and an evaluation of the project as a whole.”

The rates tested were:
1. Outside Minnesota miles – $0.00 per mile;
2. Inside Minnesota miles – $0.01 per mile;
3. Twin Cities (“Metro Zone”) – Peak miles – $0.03 per mile; and
4. “Non-Technology” miles – $0.03 per mile.
It looks like there were some technology problems in the experiment (having worked with GPS and in-vehicle devices for research, I believe this is still emerging technology with imperfect reliability, insufficient for mainstream application):

As mentioned previously, trip data was only available for 57 percent of trips generated by the system. Of the 43 percent of trips where trip data was not available, 69 percent of the trip data loss was due to a vehicle detection failure. Trip data was only recorded if the system could both detect the device was in the correct vehicle and a valid GPS signal was found. Therefore, the remaining 31 percent of the trip data loss can likely be attributed to poor GPS signal during trips. Although the log messages associated with GPS availability cannot be extrapolated to measure the number of trips or miles impacted, the loss of trip data resulting from vehicle detection failures or lack of GPS signal during trips clearly identifies GPS availability as a significant system issue. The deployment team’s report provides additional insight into the accuracy of the system as it relates to GPS connectivity and accuracy. Intermittent GPS signal was reported as a contributing factor to lower device miles compared to odometer miles collected.

Just as a random statistic, which probably doesn’t mean a lot, the report includes the word “success*” 27 times and “fail*” 33 times.
I believe MBUF or an equivalent will come eventually, but here and now the gas tax (or wholesale fuel tax, if we want to hide it), properly indexed to inflation and fuel economy, is where we need to be focusing for the revenue required to operate road systems in the US.

Property Tax on Privatized Roads

Recently published:

  • Junge, Jason and David Levinson (2013)
    Property Tax on Privatized Roads.
    Research in Transportation Business and Management. [doi]
    Roads cover a significant fraction of the land area in many municipalities. The public provision of roads means this land is exempt from the local property tax. Transferring roads from public to private ownership would not only remove maintenance costs from city budgets, but increase potential property tax revenue as well. This paper calculates the value of the land occupied by roads in sample cities and determines the potential revenue increase if they were subject to property tax. Further calculation computes the extent to which the property tax rate could be reduced if the land value of roads were added to the tax base.

    JEL code: R40, R11, R14

    Keywords: tax, land value, locational analysis, transportation finance

The case for (and against) public subsidy for public transport

David King and I argue The case for (and against) public subsidy for public transport at Streets.MN:

“In most of the United States and much of the world, public transport is publicly subsidized. Everyone in an area pays for transit whether or not they use it. This was not always the case, and need not everywhere be the case. Once mass transportation was provided to the public for profit (in Minneapolis and St. Paul as well as most other US cities) from the late 1800s through the first half of the 1900s. While rights-of-way were often publicly provided, the companies operating transit paid for the maintenance of those rights-of-way above and beyond what was required for transit.”

A Portfolio Theory of Route Choice


Recently published:

Although many individual route choice models have been proposed to incorporate travel time variability as a decision factor, they are typically still deterministic in the sense that the optimal strategy requires choosing one particular route that maximizes utility. In contrast, this study introduces an individual route choice model where choosing a portfolio of routes instead of a single route is the best strategy for a rational traveler who cares about both journey time and lateness when facing stochastic network conditions. The proposed model is compared with UE and SUE models and the difference in both behavioral foundation and model characteristics is highlighted. A numerical example is introduced to demonstrate how such model can be used in traffic assignment problem. The model is then tested with GPS data collected in metropolitan Minneapolis–St. Paul, Minnesota. Our data suggest there is no single dominant route (defined here as a route with the shortest travel time for a 15 day period) in 18% of cases when links travel times are correlated. This paper demonstrates that choosing a portfolio of routes could be the rational choice of a traveler who wants to optimize route decisions under variability.

JEL-Code: R41, R48, D63
Keywords: Transportation planning, route choice, travel behavior, link performance

Moving beyond mobility: measuring accessibility in U.S. cities

CTS Catalyst summarizes our Access Across America report:

Moving beyond mobility: measuring accessibility in U.S. cities

Every year, Americans face a steady stream of discouraging news. We’re spending more time stuck in traffic. Congestion in our metro areas is on the rise. Yet these reports focus almost exclusively on traffic mobility—how quickly travelers can move between any two points via automobile or transit. But according to a new University of Minnesota study, there’s much more to the story.

“Focusing solely on mobility and traffic delay doesn’t provide a complete picture of how the traffic system is functioning,” says Professor David Levinson, the R.P. Braun/CTS Chair in Transportation Engineering. “Travelers in many of these cities have the ability to reach their desired destinations, such as shopping, jobs, and recreation, in a reasonable amount of time despite congestion and slower travel because these cities have greater density of activities. In short, these travelers enjoy better access to destinations.”


A new study, Access Across America, goes beyond congestion rankings to focus on accessibility: a measure that examines both land use and the transportation system. The study is the first systematic comparison of trends in accessibility to jobs by car within the U.S. By comparing accessibility to jobs by automobile during the morning peak period for 51 metropolitan areas, the study shows which cities are performing well in terms of accessibility and which have seen the greatest change.

To generate the rankings for this study, Levinson created a weighted average of accessibility, giving a higher weight to closer jobs. Jobs reachable within 10 minutes are weighted most heavily, and jobs are given decreasing weight as travel time increases up to 60 minutes. Based on this measure, the 10 metro areas that provide the greatest average accessibility to jobs are Los Angeles, San Francisco, New York, Chicago, Minneapolis, San Jose, Washington, Dallas, Boston, and Houston.

“It can be surprising to see that some of the cities often ranked as the most congested also have the highest levels of job accessibility,” Levinson says. “This is due to the density of jobs those urban areas offer.”

Levinson also found that job accessibility has changed over time. In the past two decades, Las Vegas, Jacksonville, Austin, Orlando, and Phoenix have seen the largest percentage gains in job accessibility while Cleveland, Detroit, Honolulu, and Los Angeles have seen the largest percentage drops.

According to Levinson, this research offers an important takeaway for metro areas interested in increasing accessibility. “There are two ways for cities to improve accessibility—by making transportation faster and more direct or by increasing the density of activities, such as locating jobs closer together and closer to workers. While neither of these things can easily be shifted overnight, they can make a significant impact over the long term.”

This report extends the Access to Destinations study, an interdisciplinary research and outreach effort coordinated by CTS with support from multiple sponsors.

Adventures in Forecasting Intercity Rail: NLX edition

Projections around the proposed intercity railway “Northern Lights Express (NLX)” line from Duluth to Twin Cities are presented below. The first two columns of data are from the Statewide Rail plan, funded by MnDOT, prepared by Cambridge Systematics (lead). The last column is from the recent draft Environmental Assessment by USDOT, MnDOT and WisDOT

State Railway Plan Environmental Assessment
Base Best
Scenario Evaluated: High speed, 8 RT High speed, 8 RT
Phase I I Route 9
Capital Cost $878,500,000 $676,600,000 $820,000,000
Operating and Maintenance Cost (Annual) $45,700,000 $35,900,000
Revenue $9,600,000 $12,000,000 $27,660,000
Farebox Recovery 21% 34%
Capital Cost per Mile $5,800,000 $4,500,000
Capital Cost per Rider (2030) $2,042 $1,049 $732.14
Operating Subsidy per Rider $83.82 $36.96
Ridership 2020 938,000
Ridership 2030 430,000 645,000 1,120,000
Ridership 2040 1,302,000
Feb-10 Minnesota Comprehensive Statewide Freight and Passenger Rail Plan
Apr-13 Northern Lights Express High Speed Passenger Rail Project from Minneapolis to Duluth, Minnesota

Who will pay if NLX fails?


I was asked to write an opinion piece for The Pine City Pioneer: Who will pay if NLX fails? in response to one put forward by project consultant Alexander Metcalf of TEMS:

“TEMS, the consultant hired to advocate for the project, asserts that revenue will exceed operating costs at higher speeds. I agree that both revenue and costs will increase with speed, whether one increases faster than the other is an empirical question on which forecasts are highly questionable for a variety of reasons, not the least of which is lack of existing service on which to base such assumptions. Many have suggested the Downeaster is the most comparable market.
The Downeaster already carried 300,000 riders in 2005 and was in fact forecast to carry 625,000 passengers between Boston and Portland in 2015, so, [the fact] that it exceeds 525,000 riders in 2012 after a major investment is hardly testament to it beating targets.
More important is to compare the structure of the markets. Boston and Portland are less than 100 miles apart. Duluth is 137 miles from Minneapolis, so you would expect more trips between Boston and Portland if the sizes of the city pairs were equal. They are not.
The population of metropolitan Portland, Maine (516,000) exceeds that of Duluth (280,000); while the metropolitan Boston combined statistical area (7.6 million) remains larger than the Twin Cities (3.6 million). The number of trips between two places is a product of their sizes and inversely proportional to the travel time. On a population basis alone we expect the Boston to Portland market to have almost four times as many trips as Minneapolis to Duluth.
Of course metropolitan Boston has much greater transit use (12.2 percent) than Minneapolis (4.7 percent), and much better connections so that will also tend to increase ridership for the Downeaster above what the NLX should expect.
Unfortunately, U.S. experience with passenger rail for the past 50 years suggests the forecasts are optimistically biased in favor of the project in order to increase the likelihood they will be funded. The question at hand is will the project in fact recover its operating and capital costs?
We have no evidence it will. TEMS admits that Amtrak considers state revenue as income. A subsidy is a subsidy whether it comes from the federal, state, or local government. So even if the Northeast Corridor were operationally profitable (conveniently forgetting capital costs, which need to be paid somehow), that is not evidence any other particular route would be. Just because it pays its utilities (operating costs) doesn’t mean it pays its mortgage (capital costs). Who will pay if the NLX fails to meet revenue hopes?”