Update on Project Activities
This week, we continued working on the final report, presentation, and map. We put together a literature review on Level of Traffic Stress based on the original Mineta study, and we will also created a summary of the other major bikeability metrics. We have also written up the case study on Long Beach and will do so for Copenhagen as well. For the map, we added the intersection analysis from the Mineta study and displayed the results as points. We also tested out ArcGIS Online as an alternative to Carto, and found that it has similar capabilities and is easier to use. What We Observed and Learned The original LTS uses four components to determine intersection comfort. Firstly, signalized intersections are automatically designated as LTS 1. For unsignalized intersections, a score is assigned based on the presence of a median refuge, number of lanes being crossed, and the speed limit of the street being crossed. However, we found that almost all intersections in San Francisco are LTS 1 or 2 based on this approach, because most are signalized or have low speed limits. This scoring is not reflective of the actual stress of many intersections, which lack protection, markings, or bicycle signals. By applying lessons from Long Beach’s intersection treatments (bike boxes, markings, detection signals) and practices we saw in San Francisco (protected intersections), we hope to redo the analysis to better reflect reality. We also tried using ArcGIS online to recreate the map we made using Carto. It turns out that ArcGIS story maps have the ability to create popups, tabs, symbolized lines and intersections, and sidebars. While Carto also has these capabilities, they often require knowledge of Javascript or html. Critical Analysis/Moving Forward Using metrics to gauge a City’s well-being or progress can be tricky business. What works for one study does not always work for another. In the case of the Mineta study, intersection analysis was used for an academic research paper on network connectivity, which requires advanced software and datasets that can be easily analyzed. Meanwhile, the SFMTA uses LTS to help decide on new infrastructure investments, which may require more detailed information about each intersection and what treatments already exist. As we continue improving on our version of LTS, we have to keep in mind that the SFMTA uses LTS for important decisions, and that our LTS should be an accurate reflection of real bicycling conditions. Using Carto also taught us that coding and web design can be powerful planning tools. Interactive online maps can communicate information to the public and other government departments in a clear, engaging format. However, we should keep in mind that maps have also been used to target vulnerable populations. For our project, including metrics like income level and car ownership can help planners understand which neighborhoods might desire more investment in bicycling. At the same time, we must take care to interpret our map in a way that is sensitive to existing residents. For example, some people may view bike lanes as a cause of gentrification, rather than a way to make mobility more affordable. Thus, the socioeconomic aspects of our metric should be viewed with caution. 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. Update on Project Activities
The team did not meet this week outside of class, but we came into this week with a lot of insight and direction as to what information and data we need to acquire in order to move our project forward. Janice suggested that we use specific streets in District 6 and analyze whether the LTS biking metric can help improve these streets and make them safer for bikers as well as pedestrians. As a group, we have been researching the applications of LTS to intersections to get an idea of what would be considered a safe intersection versus an unsafe intersection. We have also been gathering information from other bikeability metrics, such as Long Beach and Copenhagen, in order to get an idea of what actually works and what is actually a reachable improvement for intersections in San Francisco specifically, since San Francisco has many physical features that make applying LTS fairly difficult. Since our meeting with David from the Stanford Geospatial Center on Friday, we have been searching for mapping data that would be useful for the creation of our GIS map. Stanley and Derek have put together a rough dataset with all pertinent street and intersection information critical for completing our map. Hopefully, SFMTA gets back to us with mapping data on intersection activity that would be applicable to evaluating whether an intersection has suitable characteristics for the amount of traffic fluctuating through it. David also shared a few links with us that use Carto and AGO as a guide for web mapping our data that we find. Plus a tutorial on how to get the street intersections from the street line data. What We Learned and Observed I think that the most important thing we learned and observed this week was that making our GIS map is the easy portion of the project. The most challenging component is finding legitimate data that we can actually apply to our project. There are many different sets of data about biking routes and improvement of overall biking comfortability, so it is challenging to find the exact data we need to mold our GIS map. Now that we have some specific direction from Janice regarding what information we need to acquire, gathering information and data have become a lot more feasible for the group. Critical Analysis/Moving Forward At this point, we have successfully divided up the research that each group member will do regarding the pitfalls of LTS and are currently filling out our final PowerPoint and final scope of work. Since we have a draft of a GIS map, we can now try to incorporate other interactive features within our map and make it more user friendly and understandable for audiences. Getting all of the information and data together now will make forming our final draft of the project a lot easier. Considering our pace on completing the project was slow at first because of how broad our topic is, finally narrowing down the things we need to research will allow for faster understanding and direction for finalizing our project deliverables. Update on Project Activities
We met on Sunday after our trip to San Francisco to debrief our experience. we were able to take an hour to kind of hash out next steps based on the information we collected during our SF trip. We realized that we needed to be more specific in our project and that the SFMTA really believes LTS is the primary metric they should use when evaluating bikeability in San Francisco. This team meeting was important because we are now narrowing down our focus for our scope of work. We ended up proposing to investigate how intersections in a supervisor district in SF have different bikeability ratings.We also ended up calling Janice on Friday for our check-in. During the meeting, we were able to figure out specific streets in District 6 that had great intersections and streets with poor intersections. Janice also suggested that we provide the SF Bicycle Coalition with a document describing Level of Traffic Stress (LTS) and the areas that LTS fails to address. She suggested that we could use data and information found in other bike ability metric studies to supplement our report on the weaker areas of LTS. This report would be helpful in holding SFMTA accountable for their use of LTS to evaluate bike safety and prompt them to consider other factors when doing so. We also met with David from the Stanford Geospatial Center on Friday. During this time, David showed us some good sources for GIS data online and suggested that we use Carto for displaying an interactive map that our community partner can use/share with the public. What We Observed and Learned The most important thing we learned and observed was that sometimes, community partners change plans and we have to be flexible and do it quickly to adjust to those changes effectively. We realize that at this point, we really need to start getting going on project components as we have been moving slowly along our project. Now that we have some clear deliverables, we can divide up the work accordingly and get things done quicker. Critical Analysis/Moving Forward The main priority for us is to assign which team members will research which pitfalls of LTS and put the information into our final document. This will be important as we enter the final stages of the quarter. Another thing we need to do is to really pick up our pace and perhaps have more frequent communications as we try to get more robust research and start putting the pieces together. Some of us will start to cobble together a base dataset with all pertinent street and intersection information for our GIS map. Then, we will be able to add other features to our dataset and equip our map with interactive features. Update on Project Activities
Two events dominated this past week - the Scope of Work presentation and our trip to San Francisco on Friday. We now better understand how the San Francisco Bicycle Coalition (SFBC) and the San Francisco Municipal Transportation Agency (SFMTA) operate and what their needs are. At the same time, we have new questions about how to include equity, how to reach out to locals, and what format the map should be in. We will meet this Sunday to discuss additional research and field work needs. Later this week, we will also email Janice with the data we want from the SFMTA, call her with updates, and potentially meet with the Geospatial Center staff to discuss the map. What We Observed and Learned Overall, the consensus on our Scope of Work was to consider San Francisco’s diversity and unique context. For instance, language barriers might prevent Cantonese and Spanish speakers from engaging with bicycle projects and advocacy. Moreover, existing lifestyles are not always conducive to bicycling. Deland’s project on Broadway Street revealed that bicycling is a low priority for Chinatown residents. How can we account for these established preferences? Moreover, San Francisco is diverse socioeconomically. SFBC advocacy member Charles explained the need to tweak messaging when speaking to luxury condo owners versus single-room occupancy residents. This raises a crucial question: are bike, pedestrian, and transit resources being fairly distributed across the City’s cultural and socioeconomic groups? Low stress bicycling… for whom? Beyond equity, we must consider other non-infrastructure concerns, such as the hilly topography and windy weather. Additional suggestions included the using the Census Bureau’s “OnTheMap” service for traffic data, examining the purpose of bikeability metrics, and changing the metric’s name to be more intuitive or striking. Janice echoed the need to consider a range of issues in her email, commenting that we could consider adding land use, demographics, and danger hotspots to the Level of Traffic Stress (LTS) metric. An important element of our trip was experiencing San Francisco bicycling firsthand. A number of highlights stood out during our bike tour with Janice, as well as our trips to and from the Caltrain station. For instance, pavement quality along Townsend Street was a surprisingly important issue. The reason for the poor pavement was that Townsend is an “unaccepted street”, so the City leaves maintenance to nearby property owners. We also passed through San Francisco’s latest protected intersection, which was a joy to ride. However, because many other parts of our journey were exposed to traffic, the overall trip was stressful. This emphasizes the point that a bicycle trip is only as comfortable as its most stressful link, as well as the need for an extensive and well-connected network. During our trip with Janice, we encountered windy conditions and steep hills, both of which are elements of bikeability we should consider. Finally, the way back to the Caltrain station was quite scary. We took a route under the freeway, where there were no bike lanes at all for a long stretch. This highlights the need for wayfinding that can direct people to areas with better infrastructure. In our meetings with the SFBC and the SFMTA, we gained critical knowledge about how the two groups work. One of the SFBC advocacy team’s main functions is to keep track of infrastructure projects across the City. This need could shape how we create our map and our report. The second major function is to engage with members. In fact, most of Charles' activities that day involved meeting over coffee with Coalition members, spreading awareness about projects and asking them to participate in advocacy. Meanwhile, the SFMTA's main role as the handlers of transportation infrastructure money is to prioritize projects based on limited funding and to implement an overall strategy. This means that their decision-making tools are highly advanced, using both quantitative metrics like LTS, the high injury network, and connectivity as well as public input from meetings. We found out that LTS is in fact just one small part of the range of tools they use. In fact, Jamie called it "a blunt tool". Critical Analysis/Moving Forward This week, we gained valuable insights into bicycle advocacy and infrastructure from our trip, readings, and feedback. Firstly, we found there are a variety of barriers to improving bikeability, often because the intentions of policies and laws differ from implementation. For example, CEQA was intended to reduce greenhouse gas emissions, but in San Francisco was used to block all new bicycle infrastructure in the City for four years. This could, however, indicate a need for better preparation and accountability on the part of bike advocates and planners and the need to ensure people informed about the project beforehand. This is an important part of advocacy work. Additionally, we found that San Francisco’s Open Data policy does not actually mean all data is available. Most of the SFMTA’s data is actually not accessible, and making that data available would take time and effort that the Agency does not necessarily have. The lack of open and useable data on bicycling could impact citizens’ and government’s ability to analyze progress. Finally, just because San Francisco has a resolution to reach a 20% bicycle mode share by 2020 does not mean there is enough funding to achieve that. In fact, the 2013-2018 Bicycle Strategy acknowledges a significant funding gap in achieving 20% mode share. Additionally, we learned that city governance is a messy and not always transparent process, and much of it involves mediating the relationship between citizens and government. From the SFMTA meeting, Jamie Parks told us that gathering feedback from citizens is difficult, and that efforts to create public online forums have devolved into bickering. Mr. Parks argued that meeting face-to-face with people at public meetings is usually the best way to obtain feedback. On the flip side, disseminating government information to citizens is not easy. In addition to the barriers to maintaining open data, many of the SFMTA’s decision-making processes were unknown to us before we actually met with them. Though the Agency has an elaborate, computerized process for narrowing down future projects based on LTS, high injury networks, corridor studies, cost, connectivity, and demand, we did not know about this until the meeting. Nonprofit work is also about relationships - and it often means sitting in the complicated zone between citizens and government. The advocacy team’s two main roles - spreading awareness of bike projects and mobilizing the public to push for better projects - are related to the back and forth between these two groups. Being in this zone can lead to tension. Prior to our visit, the SFBC was engaging in a Twitter war with @SF311, a government agency, for blocking a bike path despite the protests of a person trying to bike through. The SFMTA was mistakenly tagged in this heated argument, angering some planners in the Agency. The SFBC is in a unique position for a nonprofit because it on good terms with the City government. The Coalition maneuver deftly in order to balance the demands of members and their relationship with the City. After the Twitter argument calmed down, they issued a quiet tweet apologizing to the SFMTA. Equity considerations were another important theme. How does bikeability fit into broader issues of gentrification, homelessness, equity? Charles and Julia of the SFBC consider their work to be part of much broader and interrelated issues of local governance, equity, and public space. However, there are sometimes conflicts. For example, homeless encampments block bike lanes at the Hairball, leading to a sensitive situation that the SFBC is unwilling to step into. What does this issue reveal about the broader complications with bicycle advocacy? The feedback we obtained will inform our project going forward. In terms of researching bikeability metrics, we now know that we will not necessarily replace LTS. If we decide not to replace it, we should at least suggest additions or tweaks to it, which can include equity and diversity, non-infrastructure concerns, hotspot and intersection analysis, local participation, and the high injury network. Moreover, now we better understand how the SFBC works, so we could potentially mold our work to better fit that. For example, they might use LTS to keep the SFMTA accountable. Right now, they usually use the high injury network to identify priorities. Creating a map that lets them track project progress and summarize past changes could be helpful, especially if it is layered with demographics, injury, land use, and participation tools. We also better understand our position relative to understanding hotspots and intersection safety, as well as researching equity concerns and find better ways for engaging with the public. |
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