Update on Project Activities
This week, we examined data on the Transbasesf.org and Vision Zero websites and discussed specific improvements to the current LTS metric (see existing map). We are also in the process of researching other factors that should matter for a biking metric.
What We Observed and Learned
This week, we found more information on how to improve LTS for San Francisco regarding slope, pavement quality, intersection comfort, car ownership, and income level. Slope, which is not in the current LTS, plays a large part in comfort because hills cause an increase in the exertion of energy required, whether it be a car driving up the hill or a person walking or biking. Low pavement quality can also make biking stressful, which we experienced firsthand at Townsend Street. Intersection safety is another aspect that could improve the comfortability of bikers as well as drivers, because the space between bikers, cars, and pedestrians is essential in order to reduce collisions. The original LTS metric developed by the Mineta Transportation Institute does evaluate intersections based on width, signalization, traffic speed, and right turn conflicts, but the SFMTA did not include those components. The number of people who have a car is another important aspect in regards to LTS because it determines how many cars could possibly be on the road, which feeds directly into the improvement of biker safety. If less cars are on the streets, the more comfortable bikers are when commuting. Moreover, lower car ownership rates could indicate higher demand for better bicycling infrastructure. According to the 2014 American Community Survey (ACS), bicycle commuting rates are higher for households with fewer or no cars, as well as for low income groups. However, income levels could pose complications when used in bikeability metrics, as discussed below. Moreover, trends in San Francisco could differ from the national statistics. In order to help improve the effectiveness of LTS, a new method to address each of these complications will be necessary.
Critical Analysis/Moving Forward
As we continue to work on finalizing our project deliverable, we are concentrating on which changes we want to add to the current Level of Traffic Stress. This will allow us to move forward with the development of our own map that displays the different levels of traffic stress for District 6 and District 11 (chosen because they have relatively poor bicycling conditions).
As of now, we have found that LTS fails to acknowledge the hilliness and condition of streets in San Francisco. We intend to improve the current LTS that the San Francisco Municipal Transportation Agency and Bicycle Coalition currently use by adding slope and pavement quality as major consideration that factor into the different levels. A level of one signifies areas that are safe to bike for general cyclists whereas a level of four depicts streets where only the “fearless” bikers would ride through. For our map and newly improved LTS, however, we plan to add letters to the different levels from A-D, where A (represented by dotted, thin, or unhighlighted lines) signifies areas with minimal slopes or new pavement and D represents areas with extreme slope levels or potholes. This allows us to keep the SFMTA’s existing methodology intact even as we add our own elements. Additionally, we will include a key that shows examples of this metric (for example, Townsend is 2AD because it is LTS 2, flat, and has poor pavement). District 11 is much hillier than District 6, so it will interesting to compare how our metric works in those two vastly different topographies.
We plan to display intersection comfort as color-coded points. However, we recognize that points vastly oversimplify the complex range of possible movements, such as right/left turns and crossings, each of which is unique from a transportation planner’s perspective. Interestingly, the San Francisco Department of Public Health had already shown intersection comfort as points in its BEQI metric.
We decided to display two equity concerns - car ownership and income levels - as Census tracts rather scoring specific segments and intersections. We did not feel comfortable doing the latter because it could require us to make judgement calls about how the City should allocate resources based on demographics. One the other hand, a concern with displaying raw demographic data is that we must make a connect that data to bikeability. One possibility is to display the frequency of various LTS streets in each tract, or to display car ownership rates and income levels near each segment. We also hope to develop pie or bar charts of car ownership and income levels for each District, to establish a better overall picture.
We are still considering how to most effectively communicate this information through our map and literature review, but we are all excited to develop the final product.