There is a new meme going about mis-using the term “white privilege” (and its cousin “male privilege”) to describe why white males ‘have it better’ than non-whites and non-males. (To be clear, I am not disputing that in the US in 2014, the average white has it better than the average black for a variety of historical reasons. I am also not disputing sexism exists. Lots of other types of discrimination exist as well.)
In general application, the “privilege meme” frames it wrong. The things that whites do that blacks get arrested and tasered for (such as sitting in public spaces in skyways) are not white privilege. They are civil rights violations. Everyone has the right to not be arrested in such circumstances. It is not a privilege not to be arrested for not breaking any laws.
It is a privilege to drive your car on a public roadway. You earn this privilege by passing exams, and being able to buy a car, and not violating any motor vehicle laws subsequently.
It is a right to walk. I don’t need a license to do so.
It is a right to board a bus and sit wherever you want.
It is a privilege to serve your country in public office. You earn this in an election.
It is a right to vote in an election.
It is a privilege to afford an expensive high-powered lawyer. You “earned” this by either earning or inheriting money.
It is a right not to be harassed, assaulted, or raped, or murdered.
It is a right to have an attorney provided for you, if you commit a crime such as harassment, assault, rape, or murder.
It is not a privilege to commit a crime such as harassment, assault, rape, or murder.
It is a privilege to be immune from punishment for a crime such as harassment, assault, rape, or murder. You probably didn’t earn this.
The researchers turned up three especially interesting findings. The first is that in single-bicyclist homes, men are roughly twice as likely as women to ride. But when you’ve got two or more cyclists living together, that gap disappears. That could be because living with a cyclist encourages people of any gender to starting biking, or because people who enjoy cycling end up in the same home through marriage or friendship. “I don’t know what direction causality goes,” Schoner says.
The second finding is that among people who rode at least once on the day they kept their travel diary, there is no gender gap when it comes to the number of trips taken that day. In other words, women who ride do so just as frequently as men. “This suggests,” Schoner and Lindsey write, “that much of the remaining gender gap can be attributed to a participation gap, not an intensity gap.”
Finally, the 2010 data shows that having kids doesn’t lead to people biking less. That’s a change: In 2000, a parent was only half as likely to be a cyclist as a non-parent. There’s no gender difference here, but because women bear the greater burden when it comes to childcare, it’s encouraging news for those working to shrink the gender gap. “The relationship between having children and bicycling is complex and unclear,” Schoner says, but “having children may be becoming less of a barrier to bicycling over time.”
In the constant exhortations to pedestrians around cars and trains, we hear “Safety is a shared responsibility“. This of course is true. Many crashes are the product of a chain of failures. The driver was too fast for conditions. The driver did not pay attention. The pedestrian did not pay attention. Someone else did not pay attention and braked sharply, and someone behind them swerved because they were following too close and hit a third person. And so on. Yet authorities are often quick to blame the victim, rather than the system design.
The more you hear the exhortation, the less effective it becomes (diminishing returns set in), much like the security threat warnings of the Bush Administration, telling us at the airport we were at threat level orange, constantly.
People are imperfect. They feel they have better things to be doing then looking out for lurking dangers around every corner. They did not evolve to operate in a city with multi-ton machines operating at speeds faster than the fastest land animals. They see meaningless signs and signals and learn to ignore them. Breaking traffic and pedestrian laws may be illegal, but it is hardly immoral – we don’t feel guilty when we conscientiously don’t allow ourselves to be governed by degrading light bulbs implemented by unthinking bureaucracies.
Designs for systems that involve people should consider human imperfection. Ideally systems are forgiving of human error. Light rail trains, e.g, are much more dangerous than buses. (Cars are too). They are far less tolerant of imperfection, as they can neither brake quickly (due to mass) nor swerve (due to tracks), and are more deadly on impact (again due to mass).
There are two good strategies for multi-modal travel within a finite space:
keep them separated and
mix them slowly
(The third strategy: mix them quickly will lead to tragedy as long as people are making decisions, rather than machines.)
The “keep them separated” strategy is why safety on interstate highways is much better than other streets. High speed vehicles are interacting with other high speed vehicles, but low speed vehicles are prohibited. It is far from perfect, but better than the previous alternative. So much so that when speed limits were raised in the 1980s, overall safety went up as drivers were attracted off much more dangerous roads onto the interstate, which was only marginally more dangerous with the higher speed limit, and now less likely to result in a speeding ticket. Security theater that deters people from flying and encourages them to drive is more dangerous than the original threat.
Newer subway systems (such as the shuttle at MSP airport between the terminal and the LRT station/parking ramps), have glass barriers preventing people from accidentally falling on the track. Despite running one train every 90 seconds or so for over 10 years, I have not heard of any incidents with this system.
The Minneapolis-St. Paul region has chosen, for the most part, not to build grade separated transit systems. They are certainly more expensive, even if more beneficial (safer and faster). That leaves the strategy of “mix them slowly.”
Proponent of shared spaces, the late Hans Monderman has a famous quote “When you treat people like idiots, they’ll behave like idiots.”
As the song goes “Signs, signs, everywhere signs”. Each sign and signal degrades the effectiveness of all the others. Monderman went for a sign and signal-free approach, using design to guide people and vehicles through town centers. In this scheme pavements give people the guidance they need.
While peer-reviewed evaluations of shared spaces have been limited, Kaparias et al. from Imperial College, evaluating Exhibition Road, say: “The results suggest that pedestrians feel most comfortable in shared space under conditions which ensure their presence is clear to other road users – these conditions include low vehicular traffic, high pedestrian traffic, good lighting and pedestrian-only facilities. Conversely, the presence of many pedestrians and, in particular, children and elderly, makes drivers feel uneasy and, therefore, enhances their alertness.” Subsequent research by the team finds “The results of the comparative analysis indicated a general decrease in traffic conflict rates as a result of the redesign but also highlighted specific issues that may require additional analysis”
Karndacharuk et al. write: “A comparative analysis of the data after implementation highlights the importance of the active frontage in enabling a lower (vehicular) speed environment in relation to the number of pedestrians within the shared space.”
In short, design matters. Over-engineering can be as great or even greater sin than under-engineering. The best design is not necessarily more gadgets, instructions, rat runs, prohibitions on actions, closing of desire lines, or other devices constraining people from their intuitions.
Rather it is running with and shaping travelers natural instincts, so the environment is not chafing but accommodating. Safety is a shared responsibility, and those who diminish the effectiveness of safety tools such as signs and signals by their misuse and excessive exhortations which loosely spend people’s scarce attention are culpable as well.
Much earlier this year The Transit Camera posted operating cost comparisons among Minnesota transit operators (reproduced below). The UMN Transitway (owned by the University, operated by a contractor, with no payment required (i.e. free to ride), subsidized by the University and student fees) had the lowest cost per ride.
LRT came in at $2.66 / ride, Metro Transit bus came in at $3.55. Of course part of this is that the LRT was operating one good (high demand) route, while buses include a mix of high demand and low demand routes.
For the sake of argument, assume the operating cost difference is in fact $0.90 per ride. Assume the capital costs differences for a service are $713,162,915. (This understates the capital costs of bus, but we undoubtedly overstated their operating costs for comparable routes, since there are always economies of density, in both operating and capital costs). There are always arguments about which capital costs should be attributed to what (e.g. parking ramps, road improvements, etc., so this may overstate the actual capital costs of a minimalist train system. These are however the official LRT numbers for Hiawatha LRT (the Blue Line).
The difference in operating costs would not make up the difference in capital costs until there were 792 million rides, ignoring interest rates. At 10.498 million rides per year, this would take 75 years. The life of the facility is probably less than 75 years.
I call the assumption that lower operating costs outweigh higher capital costs the “free capital fallacy”.
If capital were free, and the lifespan infinite, i.e. interest rates were zero and the capital never deteriorated, and demand patterns never changed, only today’s operating costs would matter. The option with the lower operating costs, all else equal, would be the best. Eventually the difference in operating costs would recover the difference in capital costs.
In fact, capital is not free. (Though some bloggers might think so.) Interest rates, while low, and near zero sometimes for the public sector, are not actually zero, or negative.
Thus, we need to trade-off capital and operating costs, and look at Net Present Value. Depending on the interest rate, sometimes the lower capital/higher operating cost option is better, and sometimes the higher capital/lower operating cost option is better. (Obviously, the lower capita/lower operating cost option would dominate).
It is time once again for my annual Minnesota Dept. of Transportation Transit Report system cost comparison. As before the overall focus of this bit of information is on comparing fixed-route operations from the various agencies across the state. A comparison of 2011 costs can be seen here. This is only a small part of the information contained in the report. If you have an interest in learning more about these and other transit providers in Minnesota I recommend reading the report in its entirety.
2012 Cost Per Ride Comparison for Minnesota Fixed-Route Transit Providers
UNIVERSITY OF MINNESOTA TRANSIT
WINONA TRANSIT SERVICE*
METRO TRANSIT: LRT
ST. CLOUD METRO BUS
GREATER MANKATO TRANSIT SYSTEM
ROCHESTER PUBLIC TRANSIT
MOORHEAD METROPOLITAN AREA TRANSIT
METRO TRANSIT: BUS
DULUTH TRANSIT AUTHORITY
METROPOLITAN TRANSPORTATION SERVICES
MAPLE GROVE TRANSIT
MINNESOTA VALLEY TRANSIT AUTHORITY
EAST GRAND FORKS TRANSIT***
METRO VAN POOL**
LA CRESCENT APPLE EXPRESS****
RAMSEY STAR EXPRESS*****
METRO TRANSIT: NORTHSTAR
Notes: *Winona operates service under contract for WSU and St. Marys **Not fixed-route service, included due to being part of overall Twin Cities Metro area system structure ***EGFT service operated under contract by Cities Area Transit ****Apple Express operated under contract by La Crosse MTU ***** Ramsey service discontinued with opening of Ramsey Northstar station
Source: 2013 Transit Report – A Guide to Minnesota’s Public Transit Systems (MnDot)
With frequent press attention on traffic congestion and “gridlock,” it may be surprising that work trip travel times in US cities are better than those of high income competitors in other nations …. Indeed, the University of Minnesota’s David Levinson, found that the typical employee can reach two-thirds of jobs in major US metropolitan areas within 30 minutes.
Census Bureau data indicates that the average work trip travel time in US cities of more than 5 million population was approximately 29 minutes each way. Western European cities of more than 5 million population have an average travel time of 32 minutes. Toronto, Canada’s only city of this size, has a travel time of 33 minutes. East Asian cities with more than 5 million residents (Tokyo, Osaka-Kobe-Kyoto, Nagoya, Seoul, Hong Kong and Singapore) have far longer average travel times — at 42 minutes. Australia’s two largest cities (Sydney and Melbourne), which are yet to reach 5 million, have an average travel times of 35 minutes.
Time is important, of course. What you can do with that time (the quality of the experience) also matters. If you can work while traveling, the value of saving time is less than if you must focus on the driving task. This is one reason why autonomous vehicles may be such a game-changer. It may also explain in part the premium people are willing to pay for high quality transit and intercity rail service.
Bicycling has grown in popularity over the past decade, but the gap in rates of bicycling between men and women in the United States (US) persists. This paper uses regional travel behavior study data from the Minneapolis-St. Paul Metropolitan Region in 2000 and 2010 to measure and model the gender gap in bicycling over time.
Findings from a series of statistical tests show that in aggregate, women bike less than men, and that growth in bicycling has been slower for women than for men over the past decade. However, stratifying the sample shows that women who live with at least one other adult bicyclist participate in bicycling at an equal rate as men. Similarly, frequency of bicycle trips among people who participate in bicycling differed by gender only slightly in 2000, and not at all in 2010. Binary logistic modeling results show that several factors, such as age and trip purpose, are associated with different bicycling outcomes for men and women, but some commonly hypothesized explanations, such as having children, were declining in effect or altogether insignificant.
These findings and conclusions are important for practice and research because understanding the nuances of the gender gap, such as the apparent gap in participation but not in frequency or the contagion effect of living with a cyclist, is essential for targeting programs effectively. This paper also identifies several travel behavior data collection limitations that complicate studying the gender gap, and offers recommendations for further study.
While equity has been an important consideration for transportation planning agencies in the U.S. following the passage of Civil Rights Act of 1964 (Title VI specifically) and the subsequent Department of Transportation directives, there is little guidance on how to assess the distribution of benefits generated by transport investment programs. As a result, the distribution of these benefits has received relatively little attention in transportation planning, compared to transport-related burdens. Drawing on philosophies of social justice, we present an equity assessment of the distribution of accessibility in order to define the rate of “access poverty” among the population. We then apply this analysis to regional transportation plan scenarios from the San Francisco Bay Area, focusing on measures of differences between public transit and automobile access. The analysis shows that virtually all neighborhoods suffer from substantial gaps between car and public transport-based accessibility, but that the two proposed transportation investment programs reduce access poverty compared to the “no project” scenario. We also investigate how access and access poverty rates vary by demographic groups and map low-income communities within access impoverished areas, which could be the subject of further focused investments.
Now only if we could do that for the whole country, hmm?