Montgomery County Planning Board Approves Updated LATR Guidelines
Katie Wagner and Will Zeid from our DC office have been working for the last couple of months as development advocates helping lead a stakeholder group with Montgomery County Transportation Staff to update the Local Area Transportation Review (LATR) guidelines to address significant issues with the proportionality of improvements brought about with the most recent updates to the traffic study guidelines. The original guidelines had the potential to trigger requirements for excessively expensive improvements/mitigation/payments for offsite improvements that were disproportional to the impact of the proposed development.
Through coordination meetings, work sessions, and three Planning Board Hearings, our stakeholder group of area transportation engineers, civil engineers, and land use attorneys worked with County Staff to develop updates to the LATR guidelines. The proposed changes were approved on March 3, 2022 by the Montgomery County Planning Board. The updated guidelines went into effect immediately and are in place for all currently submitted and future applications within Montgomery County.
The guidelines adopted a new cap for called the “LATR Proportionality Guide.” It sets an upper limit for the combined value of off-site multimodal improvements to be constructed and/or paid for via fee-in-lieu for the multi-modal adequacy tests. The Planning Board also adopted new processes to approve waivers for master planned pedestrian and bicycle improvements for de minimis residential and commercial projects via a reduced fee-in-lieu payment. These updates were developed through a compromise between public and private sector considerations and concerns. Gorove Slade will be continue to engage with the stakeholder group and Montgomery County going forward.
Key Takeaways
Predictability. The most difficult to predict cost for developers has typically been the scope and costs of off-site improvement. This revision helps give land sellers and developers transparency of future costs for the non-auto related improvement requirements brought on by the Growth and Infrastructure Policy.
Proportionality. Each new development contributes proportionally to the collective cost of maintaining and improving the non-auto infrastructure that benefits the community.
By sharing the financial responsibility costs are applied equitably and avoids the first developer in an area that has not had recent development bearing the cost alone. A single landowner or group of homebuyers will not be overburdened with non-auto infrastructure costs brought on by the requirements of the Montgomery County master plans.
These updates provide a meaningful and, in some cases, critical step forward to helping Applicants identify potential exposure early on in the process and find a path forward when significant improvements are required to meet the new Montgomery County LATR improvement requirements.
We applaud the Montgomery County Transportation Staff for championing these updates and working with the development community to identify improvements to the guidelines that factor in both public and private considerations. We look forward to our continued stakeholder meetings with the team as we all strive to improve the development review process in the County.
Detailed Summary
Off-Site Improvement Cap (LATR Proportionality Guide)
A new cap has been created for off-site improvements, named the “LATR Proportionality Guide”, that sets an upper limit for the combined value of offsite improvements to be constructed and/or paid for via fee-in-lieu for the multi-modal adequacy tests listed below:
- Pedestrian Adequacy Test (PLOC, ADA & Streetlights)
- Bicycle Adequacy Test (Master Planned Bike Facilities)
- Bus Transit Adequacy Test (Bus Shelters and Enhanced Amenities)
- Vision Zero (Improvements accounted for in above tests, County has said they do not have current plans to incorporate additional improvement requirements for this test)
This cap is exclusive of the value for any improvements along the site frontage. While we suggested and worked towards a cap for frontage improvements, Staff felt that would involve a policy change and it was deferred for future discussion.
The cap does not place a limit on improvements required as a result of vehicular analyses, such as intersection improvements; however, if such improvements reduce pedestrian, bicycle and/or bus transit deficiencies, then they can be counted towards the LATR Proportionality Guide (the cap).
The Board still reserves the right to address unique cases where the new updates still do not achieve a “proportional” result for a project, but the goal of the updates is to have that be a less common occurrence. Further, the cap is only an upper limit, and if the sum of improvements identified is below that number, then only the identified improvements would be required.
The formula for calculating the cap is shown below:
LATR Proportionality Guide = Extents of Development x Rate Per SF or DU x Adjustment Factor for Policy Area
- Extents of Development refers to the total proposed SF for commercial uses and number of dwelling units for residential. Note it is total units, not net new, and credit for existing is accounted for when scoping the initial LATR study and extents of the study.
- The rate per SF/DU is the same for all policy areas and varies by type of commercial and type of residential
- There are separate adjustment factors for each policy area and for commercial vs. residential
A quick review of several cases shows significant reductions in offsite improvements for some cases. For examples, a small change in use application had up to $400k+ in identified required bike lanes before the updates but is now capped at below $10k with the updates. Without the new cap, this project likely would not have been able to move forward.
Frontage Improvement Fee-In-Lieu and De Minimis Criteria
A new process has been implemented to approve waivers for master planned pedestrian and bicycle improvements for de minimis residential and commercial projects via a reduced fee-in-lieu payment. This helps address the sometimes disproportional requirements brought on by the master and sector plans for small developments. The updates also include a new formalized process for identifying when a payment for fee-in-lieu for frontage improvements for all projects, small or large, will be permitted.
Tollbooth-style PUDO
Scramble-style PUDO
A scramble-style PUDO refers to when some (or all) students are being dropped off or picked up on the street, not an adjacent sidewalk, and walking between cars. For scrambles, some cars drive into a designated area, and then they all stop and don’t move again until all students arrive safely at the school or in their car at dismissal. Scrambles are often used during dismissal for schools with limited sidewalks since a scramble allows for more cars to load simultaneously.
Scramble-style PUDO
When helping plan a school, what does Gorove Slade recommend? In short, all of them. Our recommendation is to design a PUDO facility that can be flexible and work for several operational styles. Once up and running, the staff and teachers can try several and see what works best. The goal is to give them the tools they need to find the best solution.
An example is the new Cardinal Elementary School in Arlington, VA. We recommended a flexible system with ample sidewalks and a bypass lane, and once it was up and running, the facility operated a bit differently than planned. At dismissal, teachers split the facility in two, with two pick-up waiting spots – one for younger grades closer to the school and one for older ones further away. This allowed for quicker matching at dismissal times.
Afternoon pick-up at Cardinal Elementary School
PUDO Analysis
Gorove Slade handles the analysis of PUDO facilities in several ways. They are inherently tricky to analyze because some operational details are challenging to model, and the significant demand is very sensitive to variables leading to large ranges of results.
Here are three ways we approach analyzing PUDO:
Queuing Analysis/Equations
One method is to use classic queuing equations, which transportation engineers have used for decades for toll booths. They are based on three factors: the arrival rate of cars, the number of booths, and the processing speed of the toll. All three of these factors correspond to PUDO facilities.
Even so, queuing equations often fail to get accurate results for PUDO facilities. For example, we were working for a private school with a notorious PUDO problem at dismissal, so we went to the field and measured the arrival rate of cars, the number of vehicles that could load simultaneously, and the average time for each pick-up. We then entered that information into our queuing models, which then told us the queue should be negative, or in other words, there shouldn’t be a queue at all, as the car arrival rate was less than the overall number of cars that could be processed.
Subsequently, we returned to our observation notes and video. We realized the longest queue in the field was when dismissal began and that our model was correct in that the queue was being processed faster than additional cars arrived. Parents and guardians arrived so early that they stacked up well beyond the school property, but once dismissal started, the queue only got shorter as more cars showed up.
The lesson we learned here is that there are more factors in the queuing analysis than just the traditional three and that arrival rates are not random.
Comparable Analysis
A common transportation engineering practice is to study comparable locations, and sometimes, that works well for PUDO facilities, especially when queuing equations don’t work as described above. We’ve taken max queue data at several private and public schools. We can try to match the car length per student ratio from a site comparable to the one we’re working on, given the design and operational elements of their PUDO.
There are two issues with using comparable data. The first one is that there’s an extensive range of data, so using our observed data leads to a max queue range of 0.10 to 0.20 cars per student being picked up. The wide range is due to how well the PUDO processes traffic and the starting queue length. To use these ratios, you need to estimate how well the PUDO will operate within this range.
But more importantly, our observations found some schools with a max queue under the 0.10 cars per student range during dismissal. This wasn’t because they had fewer cars picking up students; it was because the cars weren’t all in the same place. For example, the school we observed once had around 25 to 30 cars picking up simultaneously, but only six were at the official pick-up spot at the front door. The others were in the parking lot or curbside in several locations. So, when planning PUDO facilities, the ability of parents to use informal locations near the school can be a huge factor in the max queues and overall PUDO operations.
VISSIM Modeling
When something other than engineering judgment combined with the two analyses stiles above is desired, we turn to detailed traffic models using the VISSIM software platform. VISSIM models are highly detailed and can account for things like starting queues and varying arrival rates. The main drawback is that they require more time and resources to assemble, and in the end, they still can’t arrive at a perfect representation of a PUDO since human behavior is always a factor.
Thoughtful design and operations can dramatically improve the pick-up and drop-off process. Whether planning a brand new PUDO experience or improving existing operations, the principles and methods discussed here provide a framework for tackling one of the most persistent logistical challenges for administrators and parents alike. By considering key factors like demand patterns, operational strategies, and facility types, schools can create systems that minimize queuing, reduce neighborhood impacts, and make the beginning and end of the school day better for all.
