Transportation Research Board (TRB) Annual Meeting
Last month, representatives from Gorove Slade had the privilege of attending the Transportation Research Board (TRB) Annual Meeting in our hometown of Washington, DC! Adam Nodjomian-Escajeda (Alexandria Office), Andy Sandweiss (DC Office), Erin Lin (DC Office), Maribel Wong (DC Office), and Pankaj Singla (Fairfax Office) joined thousands of transportation professionals at the Walter E. Washington Convention Center for five days of workshops, lectures, committee sessions, and poster presentations covering a range of topics related to the transportation planning and engineering field. Check out a few of the highlights we learned below!
Latest Developments in Traffic Engineering and Planning Software, Simulation, and Regulations
One session was focused on the 7th Edition of the Highway Capacity Manual (HCM), where we learned about updates to the network analysis method, uninterrupted and interrupted flow, and active traffic demand management. One update is that active traffic demand management can now be conducted on arterial roadways, in addition to freeways. This new edition of the manual has a focus on quality of service for multimodal transportation! Following this theme, we were able to learn about the Transportation System Simulation Manual, 1st Edition, which is anticipated to be released this year pending the Transportation Research Record’s (TRB’s journal) review. Additional topics in traffic simulation covered were Microsimulation Lane Change Modeling Validation and Hybrid Vehicle Dynamics in Microscopic Simulation.
In a different session on defining and measuring walkability, we learned how students at Purdue University employed a deep-learning based detection model to automatically detect the presence and type of crosswalks using satellite imagery—particularly useful for our pedestrian infrastructure mapping in DC.
Multimodal & Active Transportation Updates
Our planners and engineers are strong proponents of multimodal accessibility, so they attended many sessions concerning multimodal and active transportation. This included a session on walking and biking equity that presented the impact of road diets and bicycle facilities on home prices. The conclusion being that road diet implementation resulted in a net decrease in crashes without increasing traffic on parallel routes, all the while also increasing property values.
At a session dedicated to Equity in Past and Present Practice, we learned how metrics for equity could be developed to reduce disparities in transportation systems, looking at examples from six state DOTs that have done this. Researchers found the need to adopt a common definition of equity, adopt equity criteria in project prioritization, to work with peers to find creative equity-based planning methods, under the general goal of institutionalizing equity within the transportation field.
Transportation Demand Management (TDM)
The TDM committee meeting offered several practical takeaways on TDM implementation and strategies. There was a discussion on how nuanced TDM strategies could be used to help disadvantaged neighborhoods. The new TDM guidebook published by Nelson\Nygaard was introduced with helpful instructions on how to best apply the guidebook in practice. The moderators also shared findings on the impact of monetary incentives to promote active modes of transportation – spoiler alert, the incentives did work!
At another session on TDM, the focus was on measuring the results of TDM programs. We learned how TDM impacts could be measured with specific metrics and where such programs had proven, quantifiable success—showing that there is research that TDM measures work.
WDCSITE-SimCap Meeting
Our TRB attendees, along with Sasha Redmon (Alexandria Office) attended the WDCSite-SimCap meeting held adjacent to the main TRB conference, where we received updates from VASITE, WDCSITE, the National ITE, and FHWA. The biggest update was the WDCSITE board voting to change its name to the “Chesapeake and Potomac Section of the ITE.”
Presenters at the meeting explained how Level of Service could be applied to pedestrian infrastructure. VDOT presented on their new variable speed limit system on I-95
Closing Ceremonies
Closing out the conference, was TRB’s fireside chat with U.S. Transportation Secretary Pete Buttigieg and U.S. Energy Secretary Jenifer M. Granholm. Their discussion covered many topics including the electrification of America’s cars, with a focus on how to distribute EV charging station equitably.
Overall, the Gorove Slade team had a wonderful time at the conference. TRB is often a highlight of the year where we can network with colleagues and peers from around the country. We left TRB this year with knowledge and new practical skills that we will implement to help improve our practice!
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.
