Frederick County’s TransIT: Embracing Technology to Maximize Mobility Management
- Author: Andrew Carpenter
- Date: September 5, 2017
With today’s rapid evolution of technology, it can be difficult for transit agencies to choose a path that will help…
In 2017, we saw a flood of new ideas and approaches to mobility management, including new research quantifying walkability and complete streets, Los Angeles Metro’s pursuit of its own in-house microtransit, and even a private company launching a pop-up bus route in London. Despite their diversity, they all shared a common thread: being built on a foundation of data.
Relevant metrics and data provide agencies with a wide range of benefits. Not only does the information collected highlight where their programs or services function well, it also offers insights into weaknesses that may have been previously overlooked. The process of selecting metrics and data points for collection can also help agencies define or scope a problem through decisions of what information would be most critical to gather in order to properly address an issue.
Some communities have already begun to invest heavily in collecting and researching data to inform their myriad public services, including police, parks, and transportation. Pittsburgh, in particular, has developed a model worth exploring, particularly for its focus on the smaller towns surrounding the city, and the fact that it centralizes information for any city department to use. Breaking down the traditional silos of government data would greatly benefit mobility managers who need information from outside their department to understand the challenges their clients face. Another approach has been to establish “policy labs,” which enable teams to develop evidence-backed decisions that can greatly improve public services.
Properly collected data is one tool in a larger kit that drives creative solutions across a vast set of issues, including the nuts and bolts of enhancing fleet management, which can help with resource allocation and service planning for thinly-stretched budgets, or addressing health care crises like opioid addiction, and more abstract exercises such as understanding how people use public space to improve how it serves the community.
Collecting data helps agencies make evidence-based decisions that benefit their communities. The improved efficiencies and resource management then offer space for mobility managers to more effectively address one-on-one issues for residents that just can’t fit into general service due to a variety of potential limitations.
Community engagement for community benefit
NCMM encourages a customer-centered approach to mobility management. Only by integrating input from community members can mobility managers create solutions people will use.
Opening data to the public empowers residents to positively influence their public agencies while informing their community. In Washington, D.C., a Meetup group called Transportation Techies shows the role citizen scientists can play in employing open data. Many “Techies’” projects have directly influenced efforts within the Washington Area Metropolitan Transit Authority (WMATA) and Capital Bikeshare, especially the latter’s methodology for station placement based on maps of how stressful it is to bike on certain streets.
Pairing public information with data from private sources adds to the abilities of communities and agencies to make smart, evidence-based decisions. Various app developers that track bike rides have begun partnering with cities to understand how cyclists use roads, and therefore give planners insight into how they can improve road networks to create safer routes for non-drivers.
Such data practices give public agencies the opportunity to better communicate with their constituents and develop solutions with them. In particular, these circumstances create a space that helps the community define the problems they face, and gives agencies the tools to implement the solution in a customer-centric way.
Smaller communities can do this, too
Data-informed programming can be especially useful for rural transit agencies that find themselves stretching their fleets beyond capacity. Collected information can also help to manage more resource-intensive demand-response services by understanding where areas of high need exist and distributing resources in a more efficient manner.
For example, NCMM has experience working with communities to address gaps in health care access, and has found a lack of basic ridership data a barrier to understanding the problem and therefore potential solutions. This lack of information brought the project to a level in which data collection will be a key tenet in next steps. For the communities involved, data collection is critical measuring any solution’s impact, and to adapting the product to better fit any unexpected needs they uncover.
That said, here at NCMM we are aware that small communities with limited resources often have to put all of their effort into completing rides, without much time or energy left to pursue tech solutions the same way big systems can. By pooling resource with larger regions, such as in Pittsburgh, and engaging local residents, mobility managers can start to address these lacking resources.
In addition, some small communities are already tackling these issues and show signs of developing promising practices in using data to create resident-driven solutions. We at NCMM encourage you to get in touch with us so we can direct you to the resources or communities that can best inform your own data-driven models.
Image Credit: Queridian Solutions, Flickr, CC
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