The “3 Rs” of School Transportation
Insight Highlights:
- Safe and efficient operations of school transportation should be an essential component of their planning, design, and operations.
- In this Insight, we’ll be covering several reasons why K-12 schools often are the most complex land uses we work with, and provide general recommendations on how to approach these complexities.
- This includes insights for transportation planners, school administrators, and K-12 school architects and engineers.
Of all the types of buildings and projects we work on at Gorove Slade, K-12 school projects are consistently the most complex and unique. The work performed for a school is often greater than a large office building or shopping center, which seems counterintuitive but there are good reasons for that. Knowing and understanding those reasons is essential for Gorove Slade’s continued success working on schools. Let’s explore the three largest issues, the “3 Rs” of school transportation.
School buses can take up a lot of space
1. Schools Have Recognizable Travel Demands
First, the majority of the time you walk or pass by a school, there’s minimal to no transportation activity taking place. But this serene environment is disrupted twice a day by a deluge of activity during morning arrival and afternoon dismissal, which have very concentrated transportation demands in a short period of time.
Long line of cars waiting to pick-up students
Secondly, schools must also accommodate school buses that can take up a significant amount of space and have their own special transportation needs. How buses are accommodated, routed, and stored are important considerations on a school site. Ideally, school bus routing and boarding/alighting areas should not conflict with other transportation needs.
Finally, while students are generally easy to control and will follow directions, the same can’t be said for their parents. Well-designed plans can quickly fail when parents ignore rules. When planning schools, operational and infrastructure solutions must account for what happens when parents don’t behave.
In addition, transportation demand varies by school type.
Parents not following rules, blocking drive aisles and bus routes
Grade Level Matters
In general, the lower the grade, the higher vehicular demand is generated. This is due to several factors such as younger students are less likely to walk or bike on their own, and as grade levels increase, so does participation in after-school activities. Additionally, families with young students are often restricted from carpooling simply because of car seat requirements. The difference in high school is even larger, with many schools allowing for different morning arrival times for students, and a much greater participation rate in after school activities. Combining those factors with older high school students driving on their own, high schools can have much less overall demand.
The following chart demonstrates the differences between elementary students and older high school students. The significant drop in the number of students being picked-up and dropped-off leads to much fewer traffic impacts per student between the two (pick-up/drop-off has a much higher impact to the transportation network than driving and parking).
High school students have much lower rates of being picked-up/dropped-off by their parents
Private Schools Generate More Traffic
Secondly, private schools can generate much more traffic than public schools. There are two main reasons for this: (1) they draw from a much larger area than public schools (even choice public schools), and they do not always have a robust school bus network – often not having any at all.
The following chart shows that private elementary schools can have 2 to 3 times the traffic impacts on a per-student basis compared to their public counterparts. Gorove Slade has worked with private schools on many occasions to lessen their traffic impacts, including strategies such as enhancing and increasing bus service, and establishing a robust carpooling program. The specific strategies we recommend private schools use vary from school to school and are based on a data driven approach.
Private schools generate significantly more traffic than public schools
Public Choice Schools Have More Bus Demand
Finally, a common misconception is that choice schools (i.e., schools that don’t draw from surrounding neighborhoods) have more traffic demand than neighborhood schools. The data we’ve seen tells us that there’s a different transportation demand between the two, but it’s not a higher number of vehicles, but rather an increase in the number of students riding the bus.
2. Pick-up/Drop-off Carries Some Risk
When we say that schools can create a lot of traffic demand in a short period of time, we weren’t exaggerating. Imagine a shopping center with a grocery store and a number of smaller shops and restaurants. Now imagine a public elementary school in a building of the exact same size. During morning arrival, the school will generate more than double the traffic of the shopping center. Private schools without any strategies for reducing demand can generate an even higher rate of traffic.
As we wrote above, this traffic occurs for just 15 to 20 minutes twice a day. Over the course of a day, the amount of traffic generated by office buildings and shopping centers dwarfs that of a school, regardless of type. Thus, the ways to decrease traffic impact are different, and focus on encouraging students to arrive to school on other modes, and operational solutions at the school to keep impacts off neighborhood streets.
In the morning elementary schools can generate much more traffic than other land uses
3. Schools are Often Located in Residential Neighborhoods
Finally, most K-12 schools are in residential neighborhoods, which means:
Traffic solutions can conflict with the built environment. Widening roads with more lanes to compensate for arrival/dismissal traffic, even if there is room to accommodate it, could be a conflict in a residential neighborhood. Creating overbuilt roadways for when it’s not arrival/dismissal times would lead to speeding, longer crosswalks, and a poorer pedestrian experience. Thus, many solutions for school traffic include operational or management ones, including spreading out school arrivals (e.g., having different grades arrive at offsetting times), the use of police officers or school crossing guards to direct traffic, and even the use of school-specific timings on nearby traffic signals (e.g., extra green time for the school for 15 to 30 minutes).
Although a good plan can minimize impacts to a neighborhood, it can be difficult to remove them completely, especially on tight, urban school sites. This is usually in the form of traffic impacts during arrival and dismissal, notably queues from parents trying to drop-off/ pick-up their student. Other impacts can be from teachers and staff parking on local streets.
Parents waiting to pick-up students blocking a local street
Gorove Slade’s experience has given us insights on how to handle the potentially tricky transportation aspects associated with K-12 schools. This insight makes us the perfect partner to help tackle the school traffic condundrum.
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.
