Process for Studying “Shortcutting” Through a Neighborhood

By Mike Spack, PE, PTOE

Here’s an interesting email I received from a blog subscriber (feel free to shoot me similar questions) –

I need to scope out a traffic shortcutting study for a client and don’t have too much experience on this. Thought I may have seen a ‘how-to’ reference in one in your blog posts or emails. I don’t seem to find it so wondering if you would be kind enough to share any reference material on the matter.

Basically, I’m thinking on surveying plate numbers at both entry and exit points of the perceived shortcutting issue and matching up the plates from both ends. Essentially if a plate is registered at both entry and exit (within a certain time span) thus it is a shortcutting vehicle. Am I reasonably correct on my approach?          

Here’s my response –

I don’t know of any references on how to do this type of study.

It should be possible to use automatic license plate reading technology for this, but I don’t know of any portable systems on the market (and there doesn’t seem to be a big enough market to make it worth someone’s while to figure out).  You could consider using a Bluetooth matching system, like BlueToad or BlueMac, but I think the sample size is too small in a neighborhood to get accurate results.

You are on the right track.  For neighborhood studies, we manually record the license plates at the entry/exit points in 5 minute time intervals.  That helps you match up someone cutting through vs. someone who parked at their home for a few hours.  Our license plates are six digits long in Minnesota.  If it’s a busier road (more than 1,000 vehicles per day), we’ll tell our field people to record the first four digits of the plate.  You may also need to put two people at each entry/exit point so that a person can focus on a single direction.  Binoculars might be helpful too.

I used to have an old DOS based program that did the matching, but we’ve just sorted using a spreadsheet of late.  You could get into using a database if you have more than two access points.

On busier roads, we’ve used digital recording apps on our phone and done the transcription back in the office (recording license plate, time, and direction) instead of writing things down in the field.  Cell phones with voice recognition might be a good option now, but we haven’t tested that.

I typically put a few road tube counters out along the route too.  That way you can get a percentage of the total traffic that is cutting through.  Most of the studies we’ve done have focused on a two-hour window in the a.m. rush period and a two-hour window in the p.m. rush period.  You can obviously do more time, but be sure to give your field staff reasonable breaks.

For budgeting, you just need to add up all of the hours your field staff will be out and guess on your processing time.  I don’t even have any rules of thumb to help you on that one.

If this all sounds like too much effort, here’s a quick hack to estimate cut through traffic that we’ve used is:

1. Install tube counters along the cut-through route and routes that are known not to have cut-through traffic within the neighborhood.
2. Look at hourly/by direction data during the peak periods on each segment.
3. From the non-cut-through routes, calculate the ratio of normal peak hour volume to daily volume (typically about 10%).
4. Review the ratio of normal peak hour volume to daily volume on the alleged cut-through route. If the non-cut-through route has a 10% ratio and the cut-through route has a 24% ratio, it’s reasonable to estimate the extra 14% of traffic is cut-through traffic.

Do you have suggestions on how to collect cut through traffic data? Leave a message below. I would love to hear how others are addressing this common concern.