Category Archives: insights

Choking the choke points

For much of the population, a bicycle route is only as good as its weakest link. An average commuter can bliss out for 90 percent of their ride along an off-street path; but if the remaining 10 percent involve a particularly unsafe intersection or a troubling bridge crossing, it could be a show stopper. I call these choke points; they are often thought of as the weakest link in the chain of bicycle facilities for a city.
They represent an often glossed over, but important tenet of bicycle planning; ironically, they are also one of the most difficult to stay on top of. They come in two varieties. We can refer to them as (1) facility disruptions and (2) naturals.
Facility disruption: It’s simple for a city with no facilities to have no chokepoints; the whole city is a choke point. There are no real facilities that end prematurely. The more facilities a city brings on-line, the more likely choke points result. Every new lane or path needs a starting and ending point[1] and unless they are seamlessly woven into the existing fabric, there is likely some discontinuity that will result.
Naturals: Some cities are naturals for choke points. Seattle, comprised of labyrinth of water barriers which serve to funnel cyclists to select routes, is littered with them. In most communities the ordinary constriction of roadway space owing to bridges over railroads or rivers provides good fodder for where chokepoints fester. And, oftentimes the worst choke points are temporary, resulting from detours owing to construction[2], which is probably best labeled a natural occurance.
The best thing a city can do about choke points is threefold: identify, address, and minimize them.
One of the more systematic efforts to address these comes from Minneapolis, Minnesota. As of 2010, they had 54 gaps in their system[3]–one for each square mile of the entire city[4]. What other cities are taking formal and detailed inventory of the discontinuities and reporting on them?

[1] Starting and ending point: Krizek, K. J. and R. W. Roland (2005). “What is at the end of the road? Understanding discontinuities of on-street bicycle lanes in urban settings.” Transportation Research Part D: Transport and Environment 10(1): 55-68.
[2] Choke points owing to construction: Krizek, K. J. (2002). Even Here, A Failure to Respect Cyclists’ Needs. Minneapolis Star Tribune,. Minneapolis: A2 (commentary).
[3] Gaps in the Minneapolis system: see chapter 7 in Pflaum, D. (2011). Minneapolis Bicycle Master Plan. Minneapolis, Minneapolis Public Works.
[4] One gap per square mile in Minneapolis: The city’s area is 58.4 square miles; once you account for the fact that 6 percent of that area is water, it comes to 54 square miles.

Speed for bicyle travel

Knowing reliable measures of urban cycling speeds is helpful for:
-planning various types of facilities (e.g., turning radii),
-traffic flow estimations,
-better understanding the degree to which various users can comply with harmonious co-mingling,
-modelling exercises (e.g., accessibility metrics),
-general curiousity
It is often thrown out there that speeds for cyclists who travel in urban areas hovers about 10 mph. What do we know of this? Any value, we would expect, would have wide variation. A compilation of a bunch of studies prior to 2000 suggested that free-flow bicycle speeds appears to be somewhere between 6.2 mph and 17.4; the majority of the observations were between 7.5 and 12.4[1]. Of course a lot of the variation is explained by which type of facility the data are from.
Some other or follow up work found values of 9.2 mph during a recreational event that included adults and children[2], 13 mph along greenways in Indianapolis[3] and 15.4 mph along a separated path in Denver[4].
Does this vary by city, time of day, or time of week? Hard to say. Studies using similar methods found average speeds in Toronto to be 9.3 versus 11. 6 in Ottawa[5]. The most interesting revelation is coming from some 11.6 million bicycle trips analyzed as part of the Lyon bikesharing system[6]. The average 2.49 km trip took 14.7 minutes—converting to 6.2 mph—much slower than the above values, probably owing to heavier bikes and more congested conditions. They observed some uptick in speeds during rush hour (people are more pressed for time). But here is the interesting nugget: wednesday morning speeds were systematically higher than other weekdays—a phenomenon the researchers suggest might be because of the higher proportion of (faster) masculine bikers, since a significant fraction of women stay home to care for children on Wednesdays.
It looks like 10 mph is a safe and reliable average.

[1] Compilation of a bunch of studies: Allen, D. P., N. Rouphail, et al. (1998). “Operational analysis of uninterrupted bicycle facilities.” Transportation Research Record: Journal of the Transportation Research Board 1636(1): 29-36.
[2] Speed during a recreational event: Thompson, D. C., V. Rebolledo, et al. (1997). “Bike speed measurements in a recreational population: validity of self reported speed.” Injury Prevention 3(1): 43.
[3] Along greenways in Indianapolis: Lindsey, Greg and Nguyen Luu Bao Doan. 10 Questions about use of urban greenway trails. in Paper presented at Southern Illinois Transportation
Alternatives Conference, 2002.
[4] Bike path in Denver: 8. Khan, Sarosh I. and Winai Raksuntorn. Characteristics of passing and meeting maneuvers on exclusive bicycle paths. Transportation Research Record. 1776,
2001: p. 220-228.
[5] Cyclist speeds – see: Aultman-Hall, Lisa and Michael L. Hill, “Characterizing the Personal Attributes and Travel Behavior of Adult Commuter Cyclists”, Proceedings of the Institute of Transportation Engineers International Annual Meeting, Toronto, ON, August 1998.
[6] Lyon bikeshare system speeds: Jensen, P., J. B. Rouquier, et al. (2010). “Characterizing the speed and paths of shared bicycle use in Lyon.” Transportation Research Part D: Transport and Environment 15(8): 522-524.

Advancing “total health:” shining light on somewhat competing issues of physical activity & air pollution exposure

What if a community had all the successful ingredients leading to higher rates of cycling and walking (e.g., population density, intersection density, diverse mix of land uses, bike paths galore, etc)? Would planners then being doing their job? How would this relate to the total health for residents?
A small but growing number of studies are looking at two criteria of health simultaneously: exercise and air pollution. The results suggest these things might not always move together in the same direction—a “wake up” call for planners who have typically been obsessed with increasing physical activity. This study helps bring to light that the health benefits from increased physical activity in highly walkable neighborhoods may be offset by adverse effects of air pollution exposure. In the words of one of the co-authors, “city planning efforts have been planning to optimize one risk factor [lack of physical activity], when there are multiple risk factors to be taken into account.” <just fyi, another health consideration is bicycle/traffic safety, but that issue might be less controversial>
Should we worry about this? Of course. Is it a growing issue that has the potential to further divide planning initiatives? Hopefully not. Two possibilities:
·         Will cleaner cars, cleaner businesses, and cleaner everything else coming on-line possibly lessen the need to be concerned about pollution.
·         Is the fact that the study is based in Los Angeles—a basin that has perennially been out of compliance with EPA standards and probably has a disproportionate share of polluting car use (both in terms of sheer use and % of fleet that is old)—reason to suggest the issues there are not as bad as other places?
It is hard to say. I don’t think the solution is pollution filter face masks. This work merely suggests an area worth of further investigation to ensure we are not shooting ourselves in the foot.
ABSTRACT:
Background: Physical inactivity and exposure to air pollution are important risk factors for death and disease globally. The built environment may influence exposures to these risk factors in different ways and thus differentially affect the health of urban populations.
Objective: We investigated the built environment’s association with air pollution and physical inactivity, and estimated attributable health risks.
Methods: We used a regional travel survey to estimate within-urban variability in physical inactivity and home-based air pollution exposure [particulate matter with aerodynamic diameter ≤ 2.5 μm (PM2.5), nitrogen oxides (NOx), and ozone (O3)] for 30,007 individuals in southern California. We then estimated the resulting risk for ischemic heart disease (IHD) using literature-derived dose–response values. Using a cross-sectional approach, we compared estimated IHD mortality risks among neighborhoods based on “walkability” scores.
Results: The proportion of physically active individuals was higher in high- versus low-walkability neighborhoods (24.9% vs. 12.5%); however, only a small proportion of the population was physically active, and between-neighborhood variability in estimated IHD mortality attributable to physical inactivity was modest (7 fewer IHD deaths/100,000/year in high- vs. low-walkability neighborhoods). Between-neighborhood differences in estimated IHD mortality from air pollution were comparable in magnitude (9 more IHD deaths/100,000/year for PM2.5 and 3 fewer IHD deaths for O3 in high- vs. low-walkability neighborhoods), suggesting that population health benefits from increased physical activity in high-walkability neighborhoods may be offset by adverse effects of air pollution exposure.
Policy implications: Currently, planning efforts mainly focus on increasing physical activity through neighborhood design. Our results suggest that differences in population health impacts among neighborhoods are similar in magnitude for air pollution and physical activity. Thus, physical activity and exposure to air pollution are critical aspects of planning for cleaner, health-promoting cities.