This paper considers school access by both active (walk, bike), quasi-active (walk to transit) and non-active modes (car) in a two-level cross-nested logit framework. A sample of 3,272 middle and high school students was collected in Tehran. The results of the cross-nested logit model suggest that for people who choose walking, increasing a 1 percent in home-to-school distance reduces the probability of walking by 3.51 percent. While, this reduction is equal to 2.82 and 2.27 percent as per the multinomial and nested logit models, respectively. This is a direct consequence of the model specification that results in underestimating the effect of distance by 1.24 percent. It is also worth mentioning that, a one percent increase in home-to-school distance diminishes the probability of taking public transit by 1.04 among public transit users, while increases the probability of shifting to public transit from walking by 1.39 percent. Further, a one percent increase of the distance to public transport, decreases the probability of students’ physical activity, approximately, 0.04 percent.
Keywords: Public Transit; Active Mode of Travel; School Trips; Tehran
This paper tests a group decision-making model with altruism to examine the school travel behavior of schoolchildren aged between 6 and 18 years in the Minneapolis-St. Paul metropolitan area. The school trip information of 1,737 two-parent families with a schoolchild is extracted from Travel Behavior Inventory data collected by the Metropolitan Council between the Fall 2010 and Spring 2012. The proposed model has four distinctive characteristics compared with traditional developed models in the field of school travel behavior including: (1) considering the schoolchild explicitly in the model, (2) allowing for bargaining or negotiation within households, (3) quantifying the intra-household interaction among family members, and (4) determining the decision weight function for household members. This framework also covers a household with three members, namely, a father, a mother, and a schoolchild, while unlike other studies is not limited to dual-worker families. To test the hypotheses, we developed two models with and without the group-decision approach. Further, the models are separately developed for different age groups, namely schoolchildren aged between 6-12 and 12-18 years. This study considered at a wide range of variables such as work status of parents, age and gender of students, mode of travel, and distance to school. The findings of this study demonstrate that the elasticities of two modeling approaches are different not only in the value, but in the sign in some cases. In more than 90 percent of the cases, further, the unitary household model overestimates the results. More precisely, the elasticities of unitary household model are as large as 2 times more than that of the group-decision model in 25 percent of cases. This is a direct consequence of model misspecification that misleads both long-term and short-term policies where the intra-household bargaining and interaction is overlooked in travel behavior models.
The current research provides a test framework to understand whether and to what extent increasing public transit use and accessibility by transit affect health. To this end, the effect of transit mode share and accessibility by transit on general health, body mass index, and height are investigated, while controlling for socioeconomic, demographic, and physical activity factors. The coefficient-p-value-sample-size chart is created and effect size analysis are conducted to explore whether the transit use is practically significant. Building on the results of the analysis, we found that the transit mode share and accessibility by transit are not practically significant, and the power of large-sample misrepresents the effect of transit on public health. The results, also, highlight the importance of data and variable selection by portraying a significant correlation between transit use and height in a multivariate regression analysis. What becomes clear from this study is that in spite of the mushrooming interdisciplinary studies in the nexus of transportation and health arena, researchers often propose short- and long-term policies blindly, while failing to report the inherent explanatory power of variables. We show that there is a thin line between false positive and true negative results. From the weakness of p-values perspective, further, we strove to alert both researchers and practitioners to the dangerous pitfall deriving from the power of large- samples. Building the results on just significance and sign of the parameter of interest is worthless, unless the magnitude of effect size is carefully quantified post analysis.
Keywords: Public transit; BRFSS data; ACS data; Accessibility to jobs; p-hacking
Okay, Thunder Bay (map) is not quite in Minnesota, but it is the largest city northeast of Minneapolis, larger even than Duluth with over 100,000 people (though of course, when you get talking about metropolitan areas, the numbers change). “Thunder Bay” didn’t even exist as a named place until 1969, it was formed by the consolidation of the adjacent Lake Superior municipalities of Fort William and Port Arthur, Ontario. Wikipedia writes:
On 1 January 1970, the City of Thunder Bay was formed through the merger of the cities of Fort William, Port Arthur, and the geographic townships of Neebing and McIntyre. Its name was the result of a referendum held previously on 23 June 1969, to determine the new name of the amalgamated Fort William and Port Arthur. Officials debated over the names to be put on the ballot, taking suggestions from residents including “Lakehead” and “The Lakehead”. Predictably, the vote split between the two, and “Thunder Bay” was the victor. The final tally was “Thunder Bay” with 15,870, “Lakehead” with 15,302, and “The Lakehead” with 8,377.
There was more controversy over the selection of a name for the amalgamated city than over whether to amalgamate. A vocal majority of the population preferred the “Lakehead”. There was much discussion over whether there was any other city in the world that uses the word “The” in its name, which there is, as The Pas, Manitoba has “The” in its name, for example. The area was often referred to as the “Lakehead” before and after amalgamation based on its geographic location. It was seen as the “head” of shipping on the Great Lakes and the “rail head”.
Crossing into Ontario, and the Eastern Time Zone, from Minnesota, it becomes immediately apparent that the roads are in better condition. This is not due to the gas tax, which is higher, but not dedicated to transportation, but instead better management and different priorities.
Fort William was established by the Northwest Company (1803-1821) as a fur trading outpost. Today it is a living history museum (well worth seeing if you happen to be in the neighborhood, the Great White North’s equivalent of Williamsburg) replicating its final glory days in 1816 as the Hudson’s Bay Company took over the Northwest Company, but before this outpost was disbanded.
Since Thunder Bay is an amalgam, there is more than one Main Street. In fact the official Main Street is a desolate industrial serving street. There is also a High Street in the Port Arthur section, but that is mostly residential in that area. There are also lots of strip shopping centers and big box stores in newer sections of town. Instead the traditional main street in the Fort William part of town I took to be Victoria Avenue, which is bisected by an unfortunate 1980s urban mall: Victoriaville Center. This was locked shut on Sunday morning, presumably to keep out the locals, who were not among society’s victors.
Even on a Sunday morning, transit was operating, with Bus shelters ubiquitous. Parking meters abut the buildings instead of the curbs. Accessibility, particularly to growing rather than declining economic sectors, was lacking. Even the pawn shops and check cashing are going out of business. Transportation seems the least of Thunder Bay’s problems.
The buildings on the other hand, are mixed at best. Thunder Bay is literally a hollowed out shell of its former self, as illustrated by the Canadian Bank of Commerce facade. They shamefully let their building fall into such a stage of disrepair that only the facade remains. If the bank were out of business, that would be bad enough. But in fact it is still an operating entity (Canadian Imperial Bank of Commerce). Is this how they want their brand reflected? Now I guess it is better to preserve the facade than it be a completely empty lot. But the strongest bank in Canada should want to do something with this site, if only to fund a public facility if they don’t wish a branch.
In the US we are quick to praise Canadian urbanism, looking at Toronto, Montreal, Vancouver and even Edmonton and Calgary. We do not somehow look to Thunder Bay.
Five stages of repurposing. Places across the globe are at different points on the spectrum about repurposing roadspace, away from storage of cars, and toward movement of people. We (undoubtedly mis-)apply the Kübler-Ross model of grief felt by the motorist at the forthcoming loss of automobile roadspace for cycling facilities. A similar argument would apply to bus lanes or pedestrian spaces; we leave those as an exercise for the reader.
Stage 1: Denial applies to most communities across the US as there is little acknowledgement that street space will be or needs to be changing. In fact, there might be efforts to find additional space for auto capacity (e.g., more roads, more lanes, wider lanes, more parking). To the degree that non-auto-based infrastructure is discussed or desired, it centers on finding empty space within existing rights of way (e.g., excessively wide shoulders). Examples: Anytown, USA.
Stage 2: Anger is exemplified by the so-called “War on Bikes” and “War on Cars” that are riveting cities trying to make modest changes like replacing parking with bikelanes. Examples: New York, Washington DC, Toronto.
Stage 3: Bargaining might be exemplified by a willingness to re-design select sections to reduce vehicular presence. Such areas, historically, have been recipients of traffic calming techniques. This might be an explicit commitment to not build more roads, expand lanes, or increase the level of service of intersections. Given that potholes are often thought of as the original form of traffic calming, select stretches of roads might be left to wither, while other stretches might be better maintained to support increased variety of use. But the reach of these areas is increasing. Examples: St. Paul.
Stage 4: Depression builds on Bargaining as the perceived losers in the War on Cars (drivers) just stop fighting the extension of non-auto infrastructure into full corridors. Efforts might be centered on longer stretches of road where there is a willingness to reduce lane capacity. Since the first section of bike lanes already created a bottleneck for cars or eliminated parking, extensions matter a lot less. Examples: Minneapolis, Boulder.
Stage 5: Acceptance would be represented by community-wide consensus to reduce vehicular space, associated with higher non-auto mode shares. This might be in the form of removing on-street parking overall, installing parking in former vehicular lanes, or any of a series of other treatments (e.g., buffered bicycle lanes, bulb-outs). In this stage, precedents and protocol are more established, thereby easing the path by which the public, engineering or public works offices (in snow country) might more willingly accept such projects (e.g., in countless communities across the Netherlands or Denmark—though fully recognizing that there remain intense battles for initiatives that aim to reduce vehicular space, even in these so called progressive settings). Examples: Davis, Portland.
Once urban environments are created, people sort themselves, selecting the environment that best enables them to lead the lifestyle the want. People who want to bike will move to places where biking is easier. People who want to park will do likewise.
Most recent route choice models, following either the random utility maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of the consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. This study evaluates the widely applied shortest path assumption by evaluating routes followed by residents of the Minneapolis—St. Paul metropolitan area. Accurate Global Positioning System (GPS) and Geographic Information System (GIS) data were employed to reveal routes people used over an eight to thirteen week period. Most people did not choose the shortest path. Using three weeks of that data, we find that current route choice set generation algorithms do not reveal the majority of paths that individuals took. Findings from this study may guide future efforts in building better route choice models.
Social equity is increasingly incorporated as a long-term objective into urban transportation plans. Researchers used accessibility measures to assess equity issues, such as determining the amount of jobs reachable by marginalized groups within a defined travel time threshold and compare these measures across socioeconomic categories. However, allocating public transit resources in an equitable manner is not only related to travel time, but also related to the out-of- pocket cost of transit fares, which can represent a major barrier to accessibility for many disadvantaged groups. Therefore, this research proposes a set of new accessibility measures that incorporates both travel time and transit fares. It then applies those measures to determine whether people residing in socially disadvantaged neighborhoods in Montreal, Canada experience the same levels of transit accessibility as those living in other neighborhoods. Results are presented in terms of regional accessibility and trends by social indicator decile. Travel time accessibility measures estimate a higher number of jobs that can be reached compared to combined travel time and cost measures. However, the degree and impact of these measures varies across the social deciles. Compared to other groups in the region, residents of socially disadvantaged areas have more equitable accessibility to jobs using transit; this is reflected in smaller decreases in accessibility when fare costs are included. Generating new measures of accessibility combining travel time and transit fares provides more accurate measures that can be easily communicated by transportation planners and engineers to policy makers and the public since it translates accessibility measures to a dollar value.
Reducing the burden of waiting in transit travel is critical to increase the attractiveness of public transportation and encourage people’s shift from automobile mode. Research shows that wait time perception is highly subjective and varies according to various factors such as mode, availability of schedule information or stops amenities. In addition, high-quality environments are known to reduce stress and to encourage walking and biking. Nevertheless, little research exists on the influence of the stops and stations surrounding environment on transit users’ wait time perception. This study aims to respond to this knowledge gap in order to optimize stop localization and micro urban design around stops. The study compares transit users’ actual and estimated wait time at 36 stops and stations offering a mix of environmental situations in the Twin Cities region. A regression analysis is used to explain the variation in riders’ waiting time estimates as a function of their objectively observed waiting times, as well as stop and station surrounding environment characteristics. The results show that, for waits longer than five minutes, the more the environment is polluted and exposed to traffic, the more transit users tend to overestimate their wait time and that, on the contrary, the more mature trees are present the shorter the wait time is perceived. The combination of the three variables indicates that after 5 minutes wait, the presence of trees achieves to compensate the effects of both air pollution and traffic awareness. Policy implications and further research needs are discussed.
Keywords: Public transportation, transit, rail, bus, stop, station, waiting time, time perception, environment, air pollution, traffic, tree, planning, urban design.
Follow up on my Buses and Railroad Crossings post from August 11, 2014. At some point recently an “Exempt” sign was added, so buses need no longer stop here (the railroad crossing on Franklin Avenue adjacent to I-94). The line has been essentially unused since Bemis closed stopped getting shipments. The site is now being reconfigured as Brickhouse Lofts.
In short, streets.mn gets results.
Now let’s make it a useful trail.
Aaron Isaacs writes:
The Exempt sign was posted after the last shipper up near Delaware Street stopped receiving rail cars. Metro Transit requested the sign. The sign means there are no longer regular train movements. However, the railroad is still in service and still uses the crossing occasionally to switch the yard south of Franklin. Those freight cars may be stored out of service, but they generate rental revenue for the railroad. Rail car storage comes and goes with the traffic demands of the rail system, and the railroad receives income for storing them. Unless someone wants to buy the land from the railroad, I don’t see that changing anytime soon.
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