This is the fourth installment of a series of posts describing my thesis for the SFU Master of Urban Studies program. My first three thesis articles here and here examined some of the underlying reasons for my research and the results here.
Since it is well known that separated cycling lanes help support cycling growth among those 60% of the population that are “interested but concerned” in cycling more. It is also well known that transit agency suffer from the weak link known as the “first and last mile.” Essentially the requirement to walk far distances to get to transit from home is a significant impediment for increasing transit ridership.
This study takes actual Washington D.C. bikeshare trip data (1.5 Million of them to be exact, that were made between April 1, 2013 and September 31, 2013) and attempts to determine if there is a relationship between where people were making trips and the built environment, nearby separated cycling lanes and nearby high frequency transit services. This installment will focus on the multimodal (cycling and transit) “first and last mile” aspect of bikeshare trips.
It is the hope that this research will provide empirically based evidence showing how people are using bikeshare systems and provide strong support for the investment of separated cycling infrastructure lanes and the resulting safe cycling environments. Developing the understanding of how people are cycling within cities and the relationship with other modes, will also help guide policy, implementation and design decisions for these bikeshare systems.
Right from the beginning it was very apparent that the Capital Bikeshare system usage was heavily dominated by a subscriber commuting patterns (subscribers are users with annual or monthly subscriptions, casual users have 24-hour or 3 day passes). Subscriber users also accounted for 75% of trips for the study.
How do these trips related to the Frequent Transit Network (defined as the network of bus and rail based transit services operating at 15 minutes or better all day frequencies)?
The bikeshare system is well used within walking distance (400m) of the Frequent Transit Network. Approximately 93% of all trips were made at bikeshare stations within walking distance from the Metrobus based Frequent Transit Network. On the other hand approximately 50% of all trips were made within walking distance of the Metrorail based Frequent Transit Network.
Since it was hard to discern any visible pattern from the visualization for Metrobus based transit, the following section will focus on trips related to Metrorail stations. The following table shows that during the peak time more trips are ending at Metrorail stations in the morning and starting from Metrorail stations in the evening.
Since the above table showed strong commuting patterns the following four maps visualize the average number of trips per days in operation per bike share station. These maps also attempt to visualize the typical commuting pattern from 6am to 11am and 3pm to 9pm by filtering the stations (show in color) based on their walking distance to Metrorail stations. These maps clearly show for the AM Peak a large portion of trips starting in the residential neighbourhoods surrounding the downtown and ending within walking distance of Metrorail stations. The evening peak shows the reverse pattern.
What did the statistical analysis find? Any rows that have been highlighted in green indicate a positive statistically significant relationship, while red shows a negative relationship. No colour indicates no statistically significant relationship was found. The results find that there was only a positive relationship between more bikeshare trips and only with Metrorail station frequent transit services during the peak times.
Metrobus based frequent transit services were found to have weak or negative relationships with more trips at bikeshare stations. Why would this be?
Some answers may be revealed if we refer to a 2012 Capital Bikeshare Member Survey conducted on its subscriber members. First it is important to note that I understand that my study and these surveys are measuring completely different things. This survey measures members responses, where as my study measures bikeshare station trips relationships to the surrounding walkable area. That being said there are some similarities between the results that can be compared.
So what did this survey find?
“respondents reduced use of all other transportation modes; 50% drove a car less often, 60% use a taxi less often,61% ride Metrorail less often, 52% ride a bus less often, and 52% decreased their use of walking.”
Basically 52% of all bikeshare members were using Metrobus services before they had a Capital Bikeshare membership.
To explain the negative relationships with Metrobus based frequent transit services you also have to take into account that Metrobus fares are not transferable to Metrorail service or vice versa. Another key distinction is that Metrobus services do not have their own separated right of way and have to mix with traffic making them succeptible to traffic jams. The Metrorail service meanwhile has high capacity, high frequency, wide stop spacing and its own dedicated right of way as it zips along under the downtown uninterrupted by traffic. There is potential that the bikeshare system is competing with the Metrobus services to complete the “first and last mile” getting to and from Metrorail services. When you look at someone that has to make a choice between the Metrobus, Metrorail, and Capital Bikeshare with different fare systems it is easy to see someone opting for the spontaneity and flexibility of the bikeshare and the reliability, speed and reach of the Metrorail service.
Potentially an integrated fare system that combines all modes under one pricing structure may be able to mitigate these issues. Metrobus and Capital Bikeshare can compliment each other rather than compete for the same resources. Alternatively separating Metrobus services from traffic on key corridors may also help.
So what do these results mean for planning bikeshare systems and cycling infrastructure. You can anticipate higher bikeshare trips at Metrorail format of transit with high capacity, high frequency, separation from automobile traffic and wider stop spacing services. These results provide strong support for placing bikeshare stations as close as possible to Metrorail stations. Since higher trip activity can be anticipated at Metrorail stations in the peak times, planning agencies can focus system rebalancing, marketing and incentive efforts here.
Additional capacity should be added at Metrorail stations by placing larger bikeshare stations there. This will help mitigate having not enough bikes, or having too few places to return the bikes.
It was also found that there was a relationship with separated cycling lanes, therefore the network of separated cycling lanes should be extended to connect major employment and higher density residential destinations with the Metrorail stations.
Real time information on bikeshare station availability and connecting bus arrival times (such as TransitScreen) can be provided at Metrorail stations, key government offices and businesses. This can empower prospective members with the information to make decisions of which mode will work best at any given time.
Finally incentives such as providing additional time for commutes that naturally redistribute the bikes, can be provided to encourage people to make trips and potentially save bikeshare operating costs.