By Joseph Averkamp
Start counting: 11 vehicles per minute travelling at highway speeds – that’s one every five seconds. How many people were in it? Are you sure? Here comes another one. The cars just keep on coming, so don’t blink!
That’s the challenge police officers take up when they enforce your High Occupancy Vehicle (HOV) lanes or High Occupancy Toll (HOT) lanes. They can do it, but they’ll be accurate about 36 percent of the time. But what about issuing citations to violators? That will be difficult to do manually when you have approximately 78 violations per hour.
These numbers came from a test of Xerox technology that counts passengers in vehicles as they travelled at regular highway speed. We conducted these tests with Caltrans on a section of Interstate 5’s HOV lane in Orange County, California. This testing showed how transportation agencies can verify that their HOV and High Occupancy Toll (HOT) lanes are used as intended.
In addition to testing the Vehicle Passenger Detection System’s accuracy, our efforts also paved the way to the Best of ITS Award. This award was presented as part of Infrastructure of Things category, and we were selected over ten other finalists.
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This press release tells you about the award, and this blog article tells you why transportation agencies like Caltrans need an automated tool that counts passengers in vehicles. Here is what we learned from our test on a section of Interstate 5 in Orange County, California:
Counting passengers on Orange County’s I-5 at 70 MPH: What we learned. http://ctt.ec/Y32sR+ #oc #Automation
- 671 vehicles per hour in the HOV lane. That’s 11 vehicles per minute, or one vehicle every five seconds. Being able to look into the vehicle and make a snap judgment as to whether or not the vehicle is HOV-qualified is challenging. The vehicles just never stop coming.
- Approximately 78 violators per hour. Even accounting for Low Emission Vehicles, which are allowed in the HOV lane, the violation rate was 11.65 percent. An enforcement officer can manage three to four enforcement actions an hour if a roadside stop is required. An agency could not place enough officers on the roadside to cite 78 vehicles in an hour. The impacts to safety and congestion would be intolerable, and the cost would be astronomical. Roadside enforcement for numbers at this level is not possible.
- Roadside observers were 36 percent accurate; the Xerox Vehicle Passenger Detection System was 95 percent accurate in determining whether a vehicle was a Single Occupant Vehicle (SOV) or an HOV. Moreover, our system captures high quality images which can be used in two ways.
- Allows manual reviewers to examine the images in the safety of their office, and reject those where the system has mistakenly declared the SOV/HOV status. This allows the accuracy results to be improved beyond 95-96 percent range.
- The images can become an evidence package that captures the results for future use.
Unfortunately, for humans using their eyeballs on the roadside, there is no opportunity for a second review or to capture an evidence package.
The trial was conducted over three days in January, 2015. The periods of assessment were the morning and afternoon rush hours, 6 a.m. to 9 a.m. and 3 p.m. to 6 p.m. each day. The intent was to compare accuracy of human observers and our Vehicle Passenger Detection System.
At the conclusion of the study, Joe Rouse, managed lane director for Caltrans, said he was “stunned” by the numbers, and believes that the Xerox system would be an effective tool in policing HOV lanes. “For us, it all comes down to keep traffic moving by making best use of the infrastructure we have,” he said.
Here’s a look at our test results:
|Total Vehicles Reviewed||12,073|
|Violation Rate||11.65%||17.4% adjusted down for low emission vehicles.|
|Total Violations||1,406||11.65% * 12,073|
|Number of Hours During Analysis Period||18||3 days for 6 hours each day|
|Number of Vehicles Seen Per Hour||671||11 vehicles per minute or one vehicle every 5.4 seconds|
|Violators Per Hour||78|
|Single Occupant Vehicle (SOV) Detection Accuracy||Xerox VPDS: 95.3%
Human Roadside Observers: 35.6%
This presents a new way forward for HOV/HOT management. In my previous blog post, we discussed the key challenges of equity, safety, congestion and reliability. This study demonstrates that these issues can be managed, and while the study isn’t the end of the story, it illustrates a path forward to a safer, less congested roadway where traffic flows smoothly. Xerox is proud to be contribute to advancing the state of the art for transportation systems and we’re delighted to accept the Best of ITS Award 2016The results are compelling and the study shows the challenges to enforcing the rules on HOV/HOT lanes, and demonstrates a solution to the problem.