U researcher rates MN’s travel accessibility

Brian Edwards at the MnDaily writes: “U researcher rates MN’s travel accessibility
 A University of Minnesota researcher is using travel data to rank the best areas in the state to live based on access to vital destinations.
The University’s Accessibility Observatory is evaluating transportation destinations, such as jobs, schools and hospitals in the state in order to measure accessibility.
The data could shape how entities like the Minnesota Department of Transportation plan future transit projects.
Andrew Owen, lead researcher and director of the observatory in the University’s Department of Civil, Environmental and Geo-Engineering, said the research identifies where jobs are concentrated.
“Focusing on accessibility gives a way to look at how well we are achieving the goals of transportation systems,” he said.
The program uses bus, rail, car and pedestrian travel times combined with census data to measure the number of jobs that can be reached within 30 minutes of a person’s home, Owen said. The data can be adjusted to give information about any type of destination from anywhere in the state.
David Levinson, a professor in the Department of Civil, Environmental and Geo-Engineering, said this information can also explain why people choose a certain mode of transportation.
“In places with higher transit accessibility, people are more likely to use [public] transit,” he said.
Levinson said the research also focuses on how frequently public transportation is available at a certain location.
“Transit accessibility varies by time of day,” Levinson said. “If the bus just left and won’t be back for another 30 minutes, you can’t reach very many places.”

ITSO TransTalk Seminar: April 24: What happens downstream of a bottleneck does not always stay downstream.

Benjamin Coifman will be giving an ITSO TransTalk seminar on Friday April 24 in the Civil Engineering Building (500 Pillsbury Drive) Room 205 at 12:15. Food will be provided.


What happens downstream of a bottleneck does not always stay downstream.


In modern cities freeway traffic congestion degrades the movement of most persons and goods. The congestion is due to a small number of bottlenecks and just as a chain is only as strong as the weakest link, freeway flow along a corridor is restricted by the tightest bottleneck. Conventionally bottlenecks are modeled as a point along the roadway with queuing upstream and free flow downstream. Downstream of the bottleneck all signals are presumed to flow downstream with the traffic while within the queue many signals propagate upstream (e.g., stop and go traffic). This talk presents two detailed examples where this conventional wisdom fails to capture the microscopic details of the actual traffic dynamics where disturbances actually propagate upstream through the bottleneck from the supposedly free flow conditions downstream. Unfortunately the small misunderstandings have lead to large errors in the conclusions reached by many researchers. The first example presents empirical evidence of subtle flow limiting and speed reducing phenomena more than a mile downstream of a lane drop bottleneck. These phenomena reduce the maximum throughput measured at the lane drop bottleneck below actual capacity, so in this case conventional measures underestimate capacity.

The second example presents a simulation-based study of an on-ramp bottleneck. In this case the modeling incorporates driver relaxation whereby drivers will tolerate a truncated headway for a little while after an entrance but slowly relax back to their preferred speed-spacing relationship. The results show that flow downstream of the on-ramp bottleneck is supersaturated, so in this case conventional measures overestimate capacity. Thus, an empirical study or traffic responsive ramp meter could easily mistake the supersaturated flows to be the bottleneck’s capacity flow, when in fact these supersaturated flows are unsustainable and simply represent system loading during the earliest portion of bottleneck activation. Instead of flow dropping “from capacity”, we see flow drop “to capacity” from supersaturation.


Benjamin Coifman grew up in Minneapolis, graduated Suma Cum Laude from the University of Minnesota, earned a MS and PhD in Civil Engineering and a MEng in Electrical Engineering and Computer Science at the University of California, Berkeley. Currently holds a joint appointment in Civil Engineering and Electrical and Computer Engineering at the Ohio State University. Research emphasis on: Traffic Flow Theory, Traffic Monitoring, and Intelligent Transportation Systems.

Elements of Access: Our travel is constrained

by Kay Axhausen

Two views of an example time-space prism:  Source: lenntorp (1976)  (Figure 4.10)
Two views of an example time-space prism:
Source: lenntorp (1976) (Figure 4.10)

You might think of your schedule as what shows up on your calendar or daily planner. But there are lot of activities you probably don’t typically record: Driving to work, going out to lunch, sleeping, and so on. To engineers and mathematicians, the daily schedule is a complex optimization problem: there are periods of time (windows) when you have to be at certain places in order to be available to others, you have to be able to get to these points with the (mobility) tools you can bring along, you want to spend certain amounts of time at each point to be able to achieve your goals; all of this within the 24 hours of the day and within your commitments and monetary budgets.[1]

So how do people solve this problem everyday? Often, we start with what happened yesterday as a model, We also have many previous occasions of when we wanted to combine certain combinations of activities and location. We have building blocks, which reduces the complexity of the problem enormously. In addition, there are constraints that make many combinations of places infeasible within the allotted time.
Social scientists have thought about this problem for a long time. These are illustrated in the Figure.

Torsten Hägarstrand, a famous Swedish geographer, identified and visualized one set of these constraints in the 1970s. His insight was to see, that some activities in time and space are much more firmly committed to than others. Think of the work schedule of a nurse or teacher, or the need to drop a child off at school. These firm commitments form anchors within the daily schedule, constraining the time available for remaining activities, and where they might take place. We are all caught in time and space.

[1] Lenntorp, B. and P. Hort (1976). Paths in space-time environments: A time-geographic study of movement possibilities of individuals, Volume 44. Royal University of Lund, Department of Geography Lund.

Help liberate funds from Venture Capitalists

From time to time I (like many others I suppose) get offers from ride share companies like Lyft and Uber. Sign up your friends (who can’t already be members), they get $20, you get $20. This is just to get you hooked. Like a drug dealer, the first hit is free. But IF you have self-control, this is a means of taking funds from Venture Capitalists who are sponsoring these enterprises, getting a free ride with no future obligations. That is a worthy goal, isn’t it?


So here is my current Lyft promo code (through 11:59 pm April 24)



Uber’s current promotion doesn’t benefit me at all, but does get you two free rides. Here is the promo code: SpringMSP. Valid anywhere in the US through 5/31/2015.

I am skeptical of their business model, but hey, no reason you shouldn’t get a free ride.

Good luck.


The Journal of Transport and Land Use (JTLU) is now archived at the University of Minnesota Digital Conservancy in addition to the JTLU homepage. You can conveniently download any article from any issue even in the event the journal website is down.

Persistent link to this collection  http://hdl.handle.net/11299/170162


The missing link: bike network quality boosts bike commuting

CTS Catalyst writes up our Missing Link paper.

Cities promote bicycle networks to support and encourage bicycle commuting, yet until now little has been known about how the overall quality of a city’s bicycle infrastructure network impacts bicycle ridership.

In a study analyzing bike networks in 74 U.S. cities, University of Minnesota researchers have discovered that even after controlling for city size and demographics, both connectivity and directness are important factors in predicting bicycle commuting.

“This new research fills in a big gap in our knowledge about how bike facilities impact ridership,” says Jessica Schoner, research assistant in the Department of Civil, Environmental, and Geo- Engineering (CEGE) and lead author of the study. “Previous studies have found relationships between the quantity of bicycle infrastructure in a city and ridership, but the missing link has been insight into how the quality of a network affects bike ridership.”

To determine how network quality affects ridership, Schoner and co-author RP Braun/CTS Chair David Levinson began by collecting bicycle infrastructure maps from 74 mid- to large-sized U.S. cities and analyzing the maps to evaluate the backbone network of dedicated bicycling infrastructure. Then, they tested the relationship between the network analysis and the number of bicycle commuters in the city while controlling for a number of variables, including city population, land area, median income, household structure, college enrollment, and auto ownership.

“We wanted to determine whether a cyclist could complete their desired trip using the bicycle network without significant detours or gaps that would require riding in unsafe or uncomfortable conditions,” Schoner says.

BikingPhoto: Nicola Harger

Through their analysis, researchers found that a city’s bicycle commuting rate is associated with several measures of bike network quality, such as network density, connectivity, fragmentation, and directness. Interestingly, they discovered that density had the greatest impact on the level of bicycle commuting. According to Schoner, these findings suggest that cities hoping to maximize the impacts of their bike infrastructure investments should first consider increasing the density of a bike network before expanding its breadth. Researchers also concluded that excessive small fragments of bike facilities should be avoided, and they found that college enrollment is a strong predictor for bicycle commuting.

This research comes at a critical time in the development of bicycle networks across the U.S. According to the Federal Highway Administration (FHWA), cities are increasingly promoting biking for its environmental, health, and congestion-relief benefits. Investment in bike facilities has also increased: between 1999 and 2011, total federal and state government funding on bicycling and pedestrian infrastructure exceeded $7 billion. In 2012, the FHWA completed the Nonmotorized Transportation Pilot Program, which allocated $25 million each to four pilot cities over five years to measure the impacts of new infrastructure on mode shift to biking and walking.

“As we continue to invest in our country’s bike networks, it is important for transportation and planning agencies to fully understand how their bicycle infrastructure networks affect bicycle commuting in order to target investments in a way that optimizes the impact on existing riders and potential future cyclists,” says Schoner. “These findings provide a framework for transportation planners and policymakers to evaluate their local bicycle networks and prioritize the projects that best support nonmotorized travel behavior.”

Thredbo 14: 14th International Conference on Competition and Ownership in Land Passenger Transport

Registrations Open

Thredbo 14 Conference

Early bird registration closes 31 May 2015

14th International Conference on Competition and Ownership in Land Passenger Transport

Ritz-Carlton Hotel, Santiago, Chile

Sunday 30 August to
Thursday 3 September 2015

Thredbo 14 Conference
Santiago, Chile

The Thredbo Series serves as a forum for the international community, integrating a mix of executives from public agencies, and operating and consulting companies with researchers and academics in a unique and lively discussion. The conference includes academic developments, case studies, and benchmark experiences, with participants from every continent. Unlike most scientific conferences, Thredbo is structured around workshops with delegates choosing a workshop which they stay with for the duration. In each workshop, there is a deep discussion around a relevant question that later forms the basis of a report which is shared in a plenary presentation and then published in a special journal edition. This structure allows everyone attending Thredbo not only to hear interesting viewpoints but also to be actively involved in the discussion.

This conference has captured the attention of researchers worldwide; we have received 160 papers from 27 countries that have been allocated across eight exciting workshops. It will be a very lively and exciting week that you should not miss.


Main Street – St. Bonifacius, Minnesota

A week after I came to the Twin Cities (June 1999), I picked up a City Pages and saw this great article by Katy Reckdahl: The Cars of St. Bonifacius.

Head west on Highway 7 past Excelsior about 35 miles from Minneapolis, cross the rails put in place a century ago by the Great Northern Railroad, and you’ll be in St. Bonifacius, population 1180. Immediately off to the right across a grassy ditch is the St. Boni Farm Store, which Tom Logelin’s father started in 1932 as a feed and seed store and Logelin has continued as an appliance outlet. Logelin–a dignified man with a shock of wavy gray hair and an “I’d Rather Be Fishing” belt buckle that explains his nut-brown tan–gracefully winds up a dishwasher demonstration before approaching another potential customer.

“Oh, yeah, the taxicab thing,” he says when informed of the visitor’s question. “We register more damn taxis out here than any other place around. We always know it’s that time of the year–October or November–because there are a stream of taxis stopping here, asking for directions.” But this year may see the last time Logelin leaves his sea of white Whirlpools to gesture the way to city hall (up the hill and to the right). If state regulators have their way, St. Boni will have to gear up its bureaucracy, or forsake its unlikely status as the metro’s taxicab capital.

First, some numbers. A decade ago, according to city hall estimates, St. Bonifacius had only about 50 licensed cabs. But in the last few years, cabdrivers around the metro area have found out that Logelin’s directions lead them to one of the best license deals around: $50 per car per year, compared with more than $300 in St. Paul and $400 in Minneapolis. Airport cabdrivers, who have to be licensed with a metropolitan city in order to receive a permit, have been taking notice. In 1998, 390 cars–more than two-thirds of all airport cabs–were licensed in St. Bonifacius. That’s roughly one cab for every three people in St. Bonifacius, for a total number that edges out the 343 registered cabs in the city of Minneapolis, and eclipses the 124 licensed by St. Paul. …

As part of my tour of Main Streets of Minnesota, I accidentally stumbled upon St. Bonifacius on my way to Hutchinson and New Ulm (see coming episodes). I knew intellectually this was a small town. But given its legend as taxi capital of Minnesota, it was smaller than anticipated.

The article continues:

St. Bonifacius wasn’t always a taxi town. The area was settled in the 1850s by German immigrants, among them Tom Logelin’s grandfather, and Logelin serves as the community’s unofficial historian. At one point, he boasts, “we were a hub of commerce for the surrounding area. Much bigger than Mound, Excelsior, Waconia.” The locally headquartered Minnetonka Canning Company “was the biggest cannery west of the Mississippi. Every canned good on the Great Northern came from St. Boni.”

But the advent of the automobile changed all that, Logelin says, allowing people to travel further for their errands and cutting into business on Main Street. Car travel also hurt the rail business, which put the pinch on Minnetonka Canning. The firm shut down its assembly lines during the Depression. “Isn’t it ironic?” Logelin asks, in an oratory style used most recently when he spoke at the local Memorial Day service. “Whereas in the old days the development of the automobile started the demise of St. Boni, today’s great income is from the automobile.”

Twin Fields for Kids 2011 Grant Recipient Lost Dog in St. Boni. Last seen on Kennedy Memorial near the Library. Pixie Work Projects Administration Project 1939. City Park Rules. No Pets Allowed. No Bikes Skateboards or Motorized Vehicles Allowed. Park Closes at Dusk
Mar 29 Legion Aux Ham Bingo 200 7 Ton Road: 5 Tons Per Axle Weight Limit During State Weight Restrictions. In Memory of the Unborn Child
Street Bench Daylight Copper Washtub at the Laundromat. Dressel Agency Insurance Sales.
Grumpy's Pizza Burgers Wings. It's Miller Time St. Boniface Catholic Church "As for Me, I Trust in the Lord" Sculpture by church
Welcome to St. Bonifacius (someone tried flags). DNR Approved Wood. Rocket (US Army Surplus?) at playground. Playground in St. Bonifacius

Main Street (County Highway 92) intersects Highway 7, and the town is a couple of blocks in from the current right-of-way of the highway, centered on the intersection with Kennedy Memorial Drive, a block south of Old Minnesota 7. The town now has over 2200 people.

So if you are ever on Highway 7 and looking for a Meat Raffle, a Ham Bingo, or a playground for the kids, take a right on Main Street.

Cross-posted at streets.mn

Elements of Access: Spontaneous Priority

by Wesley Marshall



SPONTANEOUS ROAD USER PRIORIZATION IN SHARED SPACE INTERSECTIONS (red line = 1:1 ratio of pedestrians to vehicles; hollow circles = pedestrian-dominated intersections; blue circles = vehicle-dominated intersections; circle size = higher level of modal dominance when conflict arose) by Wesley Marshall and Nick Ferenchak

SPONTANEOUS ROAD USER PRIORIZATION IN SHARED SPACE INTERSECTIONS (red line = 1:1 ratio of pedestrians to vehicles; hollow circles = pedestrian-dominated intersections; blue circles = vehicle-dominated intersections; circle size = higher level of modal dominance when conflict arose) by Wesley Marshall and Nick Ferenchak

Like we said last time, shared spaces are streets where all signs, traffic control devices, street markings, and separation of modes have been removed. This way of thinking forces all road users, no matter the mode of transportation, to take responsibility for their own actions and negotiate the space via all the other road users by means of eye contact and other social cues. This is in stark contrast to a conventional street design where modes tend to be separated and movements guided and controlled by traffic signals and the like. In the right context, the result of shared space is not chaos; instead, spontaneous order takes hold, resulting in a space often more efficient and safer than a conventional design.

Shared space is an often misunderstood concept. First things first; the right context is key. Shared spaces would not work everywhere, especially when the focus is mobility and high travel speeds. The surrounding land uses and the way that these buildings and activities interact with the street make a big difference. So does the mix of road users. A street dominated by cars would be hard pressed to function like we might imagine a shared space should.

Many people believe living streets and/or woonerfs to be synonymous with shared spaces. However, these street types specifically grant priority in the street space to pedestrians. A true shared space concept does not. Why? Because it doesn’t have to. In the right context, this prioritization occurs naturally. The above graph is from a recent paper I wrote with my doctoral student Nick Ferenchak. We analyzed data from 37 shared space intersections with high levels of interaction between pedestrians and vehicles and assessed which mode acquiesced to which when a conflict arose. When vehicles outnumbered pedestrians, while controlling for other design factors, the pedestrians tended to back off and cede the road space to the cars. However when pedestrians outnumbered cars, this prioritization spontaneously flipped. Now, the cars were the ones yielding to the pedestrians when a conflict arose. The red line in the graph above represents the 1:1 ratio of pedestrians to vehicles. What we call the modal dominance index is represented by the size and color of the circles. The hollow circles signify pedestrian-dominated intersections while the blue circles represent vehicle-dominated intersections. The size of the circle indicate a higher level of dominance over the shared space.

Many shared space designers are tempted to follow the living street or woonerf model and grant pedestrians priority in the street space, to the point where there is a call for what is known as a Pedestrian Priority Shared Space (PPSS). While such designs can be successful and find a multitude of benefits, putting up signs to grant pedestrians priority misses a key point of the shared space concept.   A true shared space in the right context doesn’t need those signs.