The Wait for the Bus Feels Longer If Your Stop Is Near Heavy Traffic | Streetsblog

Angie Schmitt at Streetblog writes: The Wait for the Bus Feels Longer If Your Stop Is Near Heavy Traffic

If you’ve ever waited for a bus on a narrow sidewalk next to a dangerous high-speed road, this research is for you: A new study published by the Transportation Research Board finds transit riders perceive waiting times to be longer if they’re at a stop with heavy traffic and high levels of pollution.

Blogger Tim Kovach has been looking at the research in light of Cleveland Mayor Frank Jackson’s recent decision to kick buses off the city’s newly redesigned Public Square. The square is now an attractive, car-free public space, but bus riders don’t get to wait there anymore.

Not only has Jackson added to the local transit agency’s serious financial crisis by rerouting buses, he’s also squandering an opportunity to improve perceptions of transit, Kovach writes:

In their introduction, authors Marina Lagune-Reutler, Andrew Guthrie, Yingling Fan, and David Levinson (herein Lagune-Reutler et al) point out that the amount of time transit users spend waiting to ride is vital for shaping people’s perceptions of public transit. Research even suggests that time and service quality are more important for influencing people’s transportation mode choice than financial costs. Accordingly, if a transit agency makes efforts to cut waiting times, or even the perception of waiting times, they can enhance their public standing and potentially increase ridership without undertaking major capital investment.

The authors conducted surveys from 822 transit users to capture the amount of time they felt they spent waiting for the bus or train during July-August 2013 and February-April 2014. They then compared these self-reported times to video footage, which provided actual waiting time for these same participants.

Their results showed that, on average, transit users tended to overestimate their waiting times by roughly 18%, stating they felt they waited for a mean of 6.45 minutes, when the actual value was 5.48 minutes. Air pollution and heavy traffic combined to cause riders to significantly overestimate their waiting times. A 2.5-minute wait was seen as 3.88 minutes, while a 10-minute wait grew to 12.13.

Tree cover, in turn, can alleviate this effect, particularly for longer waits. Riders perceived their 10-minute waits as lasting just 7 minutes when surrounded by mature trees…

This finding provides an important point that has largely been ignored in the Public Square debate to this point. It’s not simply a matter of whether closing the Square to buses will cost more or whether a unified square is more aesthetically appealing. What matters is that transit riders have every right to take advantage of this outstanding public green space, which their tax dollars helped finance, and that doing so will make them more inclined to enjoy their transit experiences.

What a Logistic Curve of the S&P 500 Tells Us

The S&P 500 is a broad-based stock market index. Because markets are noisy, sometimes it goes up, and sometimes it goes down. (See Mr. Market.) The long-term trend is up, as over the last century or so the US economy is generally growing.

Often people treat this growth as an exponential process. Instead I fit a logistic growth curve (S-Curve) to the data. While at some scales, and particularly in the early period, exponential and logistic curves look similar, eventually a logistic curve implies slowing growth. There is active debate about whether growth is in fact slowing, and whether this is temporary or more permanent.

If you buy this curve, it provides some insights, most notably that sometimes the value of the S&P 500 is below the long-term trend and other times it is above. When it is below, historically it has been a good time to buy stocks. When it is above it is a good time to sell stocks. Obviously the best time to sell is at the peak, and the best time to buy is at the trough. (By “at”, I mean moments before, while it is assume buyers are price-takers, there is always some aspect of “price-maker” as well).

Finding the peaks/troughs is tricky, but finding whether or not the market is high or low is straight-forward. We can speculate that dollar cost averaging into and out of the market may be a good way to avoid the traps of timing imperfections. When it is above the line, dollar cost average selling, when it is below, dollar cost average buying. History waits to prove whether this is better than the simpler dollar cost average into the market that so many personal investment advisors advise.

Currently we are above the trendline. Not as much above as in 2000, but pretty close to where we were in 2008. In my mind this is a “sell signal”: it is a time to own cash, not stocks.•

Since I tend to think this is a reliable indicator, I am mostly in cash right now. It’s not clear where the top or bottom will be, and anyone who tells you otherwise is either very rich or lying (or both).

sandp500trends

A logistic curve has to have a maximum value (which is asymptotically but never actually reached), which we call “K“. The estimation follows the procedure outlined here, which I am my classes have used to understand technology deployment, particularly in transport. The data come from Quandl.

In this case, K=3035 gives the best fit (highest R-square), the model implies the S&P 500 will approach but never exceed 3035. This model is estimated for data from 1980 forward, and then applied for data from 1900 forward. Since tnought is 2010, the indication is that growth has slowed (we are in late growth).

Arguably there was a phase shift in the stock market around 1980, with the gold standard and oil embargo in 1973 through deregulation in the late 1970s and early 1980s changing how the economy operated compared with the post-World War II era.

It is certainly possible technology will great improve the economy and future profits, or policy will make or break the economy. But the economy is a big thing, it is hard to move much. When we worry about doubling of unemployment from 5% to 10% that is a personal tragedy for many people, but the economy as a whole sees employment drop from 95% to 90%, which is a 5% difference, not a 100% difference.

Some individual stocks may be buys at this point, even as the market as a whole is not. On the other hand, a falling market sinks all boats, to mix a metaphor.

 

 

The model is given below:

1980 start INTERCEPT -208.9
b 0.1039
RSQ 0.9129
tnought=intercept/-b tnought 2010
K 3035

 

 

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The content of this website is provided for general information purposes only and is not intended to solicit the purchase of securities or to be used as immigration, investment, legal or tax advice. Etc.

Don’t sue me if you lose money.

These U.S. Cities Offer the Best Job Access to Transit Riders | Streetsblog

Angie Schmitt at Streetsblog writes: These U.S. Cities Offer the Best Job Access to Transit Riders

How well does your city’s transit system connect people to jobs? A new report from the University of Minnesota lays out how many jobs are accessible via transit in major American cities.screen-shot-2017-01-06-at-12-46-27-pm



New York, San Francisco, Chicago, and D.C. offer the best transit access to jobs, the authors concluded. In addition, Seattle and Denver are two regions that punch above their weight, according to co-author David Levinson, a University of Minnesota civil engineering professor.

The research team analyzed transit schedules and walking distances to transit stops for every Census tract in the United States. Then they measured how many jobs were accessible via transit to the typical person in the region within 10-minute intervals. So for each region, they calculated how many jobs the average resident could reach on transit in 10 minutes, 20 minutes, and so on, up to an hour. The rankings are based on an average of those numbers, with more weight given to jobs accessible via shorter transit commutes than longer ones.

Both Seattle and Denver have devoted significant resources to transit expansions recently (with Seattle making especially strong progress enhancing transit in the central city). But transit accessibility is influenced by other factors in addition to the extent and frequency of the rail or bus network. Land use — or how close jobs are to workers — is another big component.

Portland, for example, probably performs well more because of its urban growth boundary than its relatively recent streetcar additions, the authors say. And San Jose may owe its high ranking to “a lot of jobs in the San Francisco metropolitan area accessible from the San Jose metropolitan area,” Levinson said.

The boundaries of regions as defined by the Census do add an element of randomness to the rankings, Levinson notes. But while small regions have fewer jobs than big regions, and thus fewer transit accessible jobs, rankings tend to hold up when you adjust for size. In the lowest-ranking region, Birmingham, Alabama, just 3.4 percent of nearly 500,000 total jobs are accessible within a 60-minute transit commute for the average resident, while in New York City, about 14 percent of the region’s 8.5 million jobs are transit accessible.

Levinson and his colleagues have been using this type of analysis to rank cities on job accessibility via walking and driving as well. In every U.S. metro region, the average resident can access more jobs by driving than by transit. “But the advantage is smaller in large cities (like New York) than smaller cities,” said Levinson.

Accessibility, Levinson says, is a more useful metric to analyze transportation systems than measures like congestion, or annual hours of delay in traffic, which transportation planners have relied on for decades. “We build cities to maximize access, so that people can easily reach other people, goods, and ideas they care about,” he said. “Without the benefits of access, there would be no reason for cities at all. So accessibility is how we should assess how well infrastructure is serving our cities.”

Travel from Pittsburgh to Columbus, Ohio, in 15 minutes? | Pittsburgh Post-Gazette

Ed Blazina at the Pittsburgh Post-Gazette writes: “Travel from Pittsburgh to Columbus, Ohio, in 15 minutes?” Yes dear reader, the Hyperloop publicity machine is out in full force.

The technology is based on a simple concept of sharply reducing drag on a moving vehicle, said Kaveh Hosseini, lead aerodynamicist at Hyperloop One.

Pods that could hold 20 to 40 people or carry freight are placed in a tube with air pressure 1/1000th of the normal rate. Using a quick jolt of magnetic energy to begin moving, the pods travel on a cushion of air at speeds Mr. Hosseini estimated could be 15 percent to 30 percent faster than jet travel.

Pods could be designed with individual seats or stations for businessmen or families traveling together. The speed of the pods mean they could leave every few minutes, almost creating an on-demand travel system that would make it possible to live in Columbus and commute to work daily in Pittsburgh, 185 miles away.

David Levinson, a professor of civil engineering at the Intelligent Transportation Systems Institute at the University of Minnesota, called the idea “just silly” and potentially dangerous if it moves ahead too quickly. He said the technology is less developed than the ill-fated maglev system proposed here in the 1990s.

“People don’t want to be hurled at 700 mph… People aren’t made to move at that rate,” he said. “It might be OK for freight, but I’m doubtful.” By comparison, he noted, it took the aviation industry several decades to develop after the Wright brothers made their demonstration flight near Kitty Hawk, N.C., in 1903.

Mr. Hosseini disagreed, saying access to computers, simulation and optimization software and advanced manufacturing techniques sharply reduce extended field tests. “Something that used to take weeks of trials and field tests can be optimized with the push of a button,” he said.

Obviously I know people have traveled faster than 700 mph. The point was more about the proposed acceleration and deceleration of 5 m/s. I can’t imagine freight needs to move that fast. In any case, no one believes that simulation substitutes for field tests.

[Also the Intelligent Transportation Systems Institute hasn’t existed for a few years, but I guess the website is still up.]

But let them get a test track going and test actual people inside their vehicle, before they start proposing actual services, much less networks. They are definitely putting the cart before the horse, and only agencies with money to burn should be talking about this.

For better critiques see Alon Levy at Pedestrian Observations.

Accessibility and the Evaluation of Investments on the Beijing Subway

Recently Published

Fig_6_The_different_subway_lines_efficiency_in_Beijing
Efficiency of Beijing Subway Lines: Change in Person Weighted Accessibility per km.

This study measures the job and population accessibility via transit for Beijing using the cumulative opportunity metric. It is shown that transit accessibility varies widely across Beijing, but is highly focused on subway stations. Early lines added far more accessibility than more recently planned lines.

Transit Riders’ Perception of Waiting Time and Stops’ Surrounding Environments

Recently published

Reported vs. Observed Waiting Times
Reported vs. Observed Waiting Times

Reducing the burden of waiting in transit travel is critical to increasing the attractiveness of public transportation. Waiting time perceptions are highly subjective and vary according to mode, availability of schedule information, and stop amenities. The research on pedestrian design finds that high-quality and natural environments reduce stress and encourage walking and bicycling. It seems reasonable that similar effects would apply for transit users on the basis of the environments around transit stops, but little research directly explores the issue. This paper responds to this knowledge gap by examining how perceptions of waiting time vary in relation to stop environments. The research compared transit users’ actual and estimated wait time at 36 stops and stations in a mix of environmental situations in the region of the Twin Cities, Minnesota. Regression analysis explained the variation in riders’ self-reported wait- ing time as a function of their externally observed waiting times as well as characteristics of the environment surrounding the stop and station. For waits longer than 5 min, perceptible pollution and exposure to traffic led to significant overestimates of waiting time. Riders waiting at stops with dense, mature tree cover, however, significantly underestimated their waiting times. The effect of dense, mature tree cover is strong enough to compensate for the effects of both air pollution and traffic awareness. Policy implications and further research needs are discussed.

Access Across America: UMN ranks accessibility to jobs by transit

New research from the Accessibility Observatory at the University of Minnesota ranks 49 of the 50 largest (by population) metropolitan areas in the United States for connecting workers with jobs via transit.

The new rankings, part of the Access Across America study that began in 2013, focus on accessibility, a measure that examines both land use and transportation systems. Accessibility measures how many destinations, such as jobs, can be reached in a given time.

“This project updates our detailed evaluation of access to jobs by transit,” said Andrew Owen, director of the Observatory. “Transit is an essential transportation service for many Americans, and we directly compare the accessibility performance of America’s largest metropolitan areas.”

The findings have a range of uses and implications. State departments of transportation, metropolitan planning organizations, and transit agencies can apply the evaluations to performance goals related to congestion, reliability, and sustainability. In addition, detailed accessibility evaluation can help in selecting between project alternatives and prioritizing investments.

Top 10 metro areas: job accessibility by transit (January 2015)

  1. New York
  2. San Francisco
  3. Chicago
  4. Washington
  5. Los Angeles
  6. Boston
  7. Philadelphia
  8. Seattle
  9. San Jose
  10. Denver

The report—Access Across America: Transit 2015—presents detailed accessibility values for each of the 49 metropolitan areas, as well as detailed block-level color maps that illustrate the spatial patterns of accessibility within each area. New analysis of the data from the accessibility to jobs by transit rankings will continue to be published periodically.

The accessibility metrics presented in this report are designed to be comparable to those presented in the Accessibility Observatory’s earlier Access Across America: Auto 2015 report. “Taken together, these reports provide a comprehensive view of the relative accessibility impact of auto and transit systems across different cities,” Owen said.

For example, the Phoenix and Minneapolis–St. Paul metropolitan areas have effectively the same total number of jobs (1.7 million; ranked 13th and 14th respectively), and their auto accessibility rankings are also very close—13th and 12th. “However, they differ significantly in their transit accessibility rankings: Minneapolis–St. Paul ranks 12th in transit access to jobs, while Phoenix ranks 22nd,” Owen said.

In the study, rankings are determined by a weighted average of accessibility, giving a higher weight to closer, easier-to-access jobs. Jobs reachable within 10 minutes are weighted most heavily; jobs were given decreasing weight as travel time increases up to 60 minutes. Travel times were calculated using detailed pedestrian networks and full transit schedules for the 7:00 to 9:00 a.m. period. The calculations include all components of a transit journey, including “last mile” access and egress walking segments and transfers, and account for minute-by-minute variations in service frequency.

Future comparison reports will track the way that accessibility in these metropolitan areas evolves in response to transportation investments and land-use decisions, Owen explained.

The research was sponsored by the National Accessibility Evaluation Pooled-Fund Study, a multi-year effort led by the Minnesota Department of Transportation and supported by partners including the Federal Highway Administration and 10 state DOTs.

The Accessibility Observatory at the University of Minnesota is the nation’s leading resource for the research and application of accessibility-based transportation system evaluation. The Observatory is a program of the Center for Transportation Studies and the Department of Civil, Environmental, and Geo- Engineering. CTS is nationally renown for developing, fostering, and spreading innovation in transportation.

Accessibility Observatory reports, including the new analysis of job accessibility by transit (Access Across America: Transit 2015), are available at: access.umn.edu

Journal of Transport and Land Use, Volume 10

With the New Year, the Journal of Transport and Land Use is moving to a continuous publication model, out with the old periodic batch mode, in with the ‘it’s done, it goes online’ model. So we cleared the backlog and hereby post Volume 10, with 25 papers.

 

Vol 10, No 1 (2017)

Table of Contents

Petrus van der waerden, Harry Timmermans, Marloes de Bruin-Verhoeven
Sarah Louise Brooke, Stephen Ison, Mohammed Quddus
Michael Manville
Wei-Shiuen Ng
Jean-François Doulet, Aurélien Delpirou, Teddy Delaunay
Carey Curtis, Jan Scheurer
Chi-Hong (Patrick) Tsai, Corinne Mulley, Matthew Burke, Barbara Yen
Ren Thomas, Luca Bertolini
James Robert McIntosh, Peter Newman, Roman Trubka, Jeff Kenworthy
Erik Elldér
Rolf Moeckel
Jinhyun Hong
Yuntao Guo, Srinivas Peeta, Sekhar Somenahalli
Sara Ishaq Mohammad, Daniel J. Graham, Patricia C. Melo
Liang Ma, Jennifer Dill
Louis A Merlin
Lei Zhang, David M Levinson
Reza Banai
Michael Manville
Haibing Jiang, David M Levinson
Niels Heeres, Terry Van Dijk, Jos Arts, Taede Tillema
Carole Turley Voulgaris, Brian D. Taylor, Evelyn Blumenberg, Anne Brown, Kelcie Ralph
Lewis Lehe
Na Chen, Gulsah Akar
Robin Lovelace, Anna Goodman, Rachel Aldred, Nikolai Berkoff, Ali Abbas, James Woodcock

On transit subsidies, first and second best

A reader writes:

Hi David, you postulate that transit that can’t be profitable or break even will shut down, which is certainly plausible and could even be welcome, but unless roads (serving human or automated drivers) and other transportation infrastrucutre are also subject to the same market discipline – if annual revenue doesn’t cover annualized full life cycle costs, including externalities, they are shutdown and the land is put to other uses – I would suggest we have a double standard about which is being disguised as a concern over subsidy.

Futhermore, this sidesteps questions of how non market forces such as zoning force the landscape into something for which transit is unsuitable and only vehicles will do.  Again, pointing to concerns about transit’s viability in suburbs or low density areas as a market concern ignores the very large non-market forces which mandate the low density in which transit does poorly.
I’m not trying to argue for transit subidies, I’d be happy to see a “pay what you use” model for all transport, even walking, provided we subject land used for transportation to the same market forces as we do the land for coffee shops and laundromats and provided people can make real market choices about how to use the land they own.  We are very far from such a free market and automated cars aren’t going to suddenly level the playing field.
In the absence of serious reform of these non-market forces, subsidizing transit should be seen as a way of managing the harm inflicted by those non-market forces.  Getting rid of non-market forces is often justified, but I’m always puzzled why proposals to jettison non-market forces always start with transit rather than free parking, free roads, free traffic control, free collision response, etc etc.
Yeah, life is unfair. Transit started out private and serves a far small share of the population in the US and so has a different political hurdle to overcome. I think I have written enough about road pricing that readers understand the position I hold, and not every sentence can say “but, but but.”
In the first best world, everything is priced properly. In our second best world, nothing is. The question is, should we accept the second best or do something to move to the first best? How distortionary is moving from second best to first best in steps (since it will never be done all at once)?