Tag Archives: GPS technology

Affordable GPS-Based System Warns Drivers About Lane Departures, Approaching Curves

Researchers have developed an affordable camera-free curve and lane departure warning system that relies on consumer-level GPS, rather than sophisticated, expensive digital maps.

The technology uses cumulative driving trajectory data from GPS points detected every 100 milliseconds to predict driving path trajectories and compare these to mapped curves and lanes. With further development, the system can be used as an inexpensive smartphone app or retail device to warn drivers of lane drift and approaching curves.

“The goal of the project is to reduce lane departure crashes. We viewed this as a seed project and demonstrated that the system can be successful,” said Victor Lund, Traffic Engineer, St. Louis County.

What Was Our Goal?

The Minnesota Local Road Research Board sought research to develop a camera-free curve and lane departure warning system that uses consumer-level GPS capability without reliance on sophisticated, expensive digital maps.

What Was the Need?

Lane departures and run-off-road crashes cause more fatalities and serious injuries in Minnesota than any other accident type.

Many current warning technologies rely on cameras that identify lane position based on pavement markings. In inclement weather, stripes and pavement markings can be difficult or impossible to identify; markings also wear off over time, reducing visibility even in clear conditions. Camera-based lane departure warning systems are also expensive and generally restricted to newer luxury vehicles, making them inaccessible to the general driving public.

Though in-vehicle technology for the public usually falls outside the research interests of the Minnesota Department of Transportation and the Minnesota Local Road Research Board, the agencies have been funding development of lane departure warning technologies to improve driver safety. GPS technologies offer an intriguing path to consumer-level lane departure warning systems.

High-level GPS can be accurate to the centimeter level, but access is restricted and use is expensive. These systems also rely on accurate, lane-level roadway mapping, an elusive data set with high access costs.

What Did We Do?

Researchers began with a literature search of the uses of standard GPS receivers in lane departure and navigation. The research team then developed an algorithm for travel direction that uses standard GPS in a straight road lane departure system to determine driving trajectories at accuracy levels suited to safe driving needs.

Investigators adapted a publicly available digital mapping platform to the same algorithm to identify navigational points along curves and develop the curve lane departure warning system. The team enhanced standard safe distance methods to consider driver reaction time in determining when approach warnings should be issued.

Researchers then brought the two developmental stages of the system together with a warning system that identifies vehicle speed, curvature characteristics and safe speed limits, and calculates distance for driver response times to issue an audible warning to drivers on lane drift and a text warning of when and how much to reduce speed as the vehicle approaches a curve.

Two figures, each with a photo of a road segment an a graph that plots roadway curve distances with warning times.
The advanced curve warning system issued audible lane departure warnings when cumulative trajectories showed lateral drift within a curve.

For project testing and demonstration, investigators programmed the algorithm into a device with a built-in GPS receiver, connected it to a laptop for messaging and conducted driving tests on Rice Lake Road and on Interstate 35 near Duluth.

“From a technical point of view, this approach works. We developed a warning system with standard GPS that everyone has in a phone or vehicle. This is a lifesaving technology in a sense,” said Imran Hayee, Professor, University of Minnesota Duluth Department of Electrical Engineering.

What Did We Learn?

Finding no research on development of consumer-grade GPS for lane departure purposes, the research team adapted previous work on the relative accuracy of GPS readings from a MnDOT study on wearable GPS for work zone safety.

Researchers adapted a consumer-level GPS device to acquire data at 10-hertz frequency, which yields a GPS position point of 2.7 meters if a vehicle is driven at 60 mph.

The system calculates lane trajectory from cumulative readings and detects turns or drift. The curve warning system plots trajectories and compares these with open-source digital maps with road-level (rather than lane-level) accuracy to anticipate curves.

Illustrations show how the warning system uses shape points from maps with driving path averages to determine lane departures.

In road testing, the system issued audio warnings for every one of the approximately 200 lane changes, including curves. For curve warnings, the system scanned for curves at least half a mile ahead and calculated the vehicle’s speed and the distance to a curve to issue a timely text warning of the curve ahead and an advisory speed limit. Additional messages were issued when the vehicle was on the curve and when the curve had ended.

False alarms—warnings issued when the vehicle was not departing its lane—occurred in 10 percent of the tests, usually on sharp curves. Further adjustment of the algorithm and additional testing reduced false alarms significantly as the system accumulated data over multiple uses of the same roadway.

What’s Next?

Investigators filed a patent for the technology and will continue to develop the system. Further refinement of reference road direction information will improve accuracy and safety; the research team has developed a new project to employ vehicle-to-vehicle dedicated short-range communication technology to expand road direction reference data. The system will then need to be adapted for a consumer-level device or a smartphone app for use in any vehicle.

This post pertains to the LRRB-produced Report 2018-34, “Development and Demonstration of a Cost-Effective In-Vehicle Lane Departure and Advanced Curve Speed Warning System,” published December 2018.

 

Traffic Tubes Still Provide More Accurate Counts Than GPS Smartphones

Collecting traffic volume information from smartphone data, navigation systems and other GPS-based consumer and mobile technologies is not yet ready for use by MnDOT. However, the emerging technology offers useful information on driving origins and destinations for traffic monitors and planners.

“We’re on the cusp of using GPS technology to get traffic data from more facilities. We’re not there today, but we’ve spurred the industry to look at this opportunity,” said Gene Hicks, Director, MnDOT Traffic Forecasting and Analysis, who helped lead the research study on this topic.

MnDOT conducts traffic counts on its roadway network at regular intervals: every other year on state trunk highways, approximately every four years on city and county roadways, and every 12 years on low-volume roads. To make these traffic assessments, MnDOT currently stretches pneumatic tubes across traveled lanes and counts passing axles for up to 48 hours.

2017-49-p1-image
Using pneumatic road tubes to collect traffic data is an old and reliable practice, but installing them is time-consuming and puts workers in harm’s way.

“Using road tubes to collect traffic volume data is a proven method, but it’s an old practice and puts people in harm’s way. Smartphones may offer a useful alternative,” said Shawn Turner, Division Head, Texas Transportation Institute, who helped evaluate a beta version of traffic volume estimates derived from global positioning system (GPS)-based mobile devices.

What Was Our Goal?

With this project, researchers aimed to explore using smartphones and other GPS-based systems instead of pneumatic tubes to collect traffic volume data. The information collected was compared with actual volume counts from MnDOT traffic monitoring sites.

What Did We Do?

In May 2016 researchers began identifying data collection firms interested in participating in this research effort. These firms were developing products that gather, aggregate and analyze sufficient location data from GPS mobile devices to estimate traffic volumes. Researchers assessed and sorted packages from these firms to identify the best match for MnDOT’s needs.

Two firms that were initially interested withdrew from the project because their products were not ready for rigorous testing. The research team then developed an agreement to work with a third firm, StreetLight, to develop and evaluate traffic volume estimates from GPS-based devices.

Researchers and StreetLight worked together to develop and evaluate traffic volume data. Investigators provided MnDOT traffic count data to the vendor for calibration of its approach, and investigators suggested several ways to enhance StreetLight’s analytics.

2017-49-p2-image
Smartphones, navigation devices and other GPS-based consumer and commercial personal devices collect data that can be used to develop traffic volume estimators.

 

The vendor developed its proprietary approach, combining GPS-based navigation data with location-based service data. The firm normalized these two data sets with U.S. Census population projections, then calibrated and scaled samples with data from 69 MnDOT permanent ATR sites. StreetLight then estimated traffic volumes for MnDOT based on 7,837 short-duration count sites.

What Did We Learn?

On multiple-tube, high-volume roadways, MnDOT expects an accuracy of over 95 percent. The correlation between AADT tube-based data and StreetLight’s data was 79 percent without calibration and scaling, and 85 percent when scaled and calibrated. GPS-linked traffic volume estimations are approaching acceptable accuracy for MnDOT, but are not yet sufficiently accurate to replace tube counting for assessing AADT.

Estimation accuracy varies heavily with traffic volume levels. At high levels of traffic, larger sample sizes of mobile devices seem to drive more accurate assessments. At over 50,000 AADT, StreetLight estimates reached mean absolute percent error levels of 34 percent. At AADT levels below 20,000, the percent error rates ballooned. At all traffic levels, GPS-based data was measured at 61 percent mean absolute percent error.

Low-volume roads and frontage roads where multiple roadways converge had to be removed from count sites for estimating AADT. Overall, some of the GPS-based data fell within 10 to 20 percent absolute percent errors, which is acceptable, but other estimates fell well outside an acceptable range, and the highest errors occurred in low-volume roadway assessments.

What’s Next?

GPS-based data offers granular information that tube counts cannot, like average annual hourly volume estimates, and origin and destination data. With improvements to analytical processes for all data, GPS-based data may provide value outside of AADT estimates.

Currently, MnDOT is evaluating origin-destination data that StreetLight is providing for use in traffic studies and planning analyses. Current research by the University of Maryland and the National Renewable Energy Laboratory is gathering data with better error rates and will be extended in Colorado, Florida and Rhode Island. MnDOT expects volume estimation from GPS-based data will continue to improve and will likely be an acceptable alternative to tube counting in a few years.

This post pertains to Report 2017-49, “Using Mobile Device Samples to Estimate Traffic Volumes,” published December 2017.

AVL Technology Enables Smarter, More Efficient Mowing Operations

A pilot project was begun to study the use of AVL technology in mowing operations. Potential benefits include improved mowing efficiency, improved reporting and ease of supervision, reduced paperwork and reduced spread of noxious weeds.

“Using the data we get from the AVL project, we can estimate how long it will take to mow the entire system,” said Douglas Maki, Asset Management Engineer, MnDOT Metro District. “That way, we can plan far in advance of major holidays, when the most traffic comes through our system.”

“The AVL technology can be used to mark newly disruptive weed locations and anything else a mower operator might see, like potholes, damaged signs or guardrails, and excessive or dangerous debris in the field,” said Adrian Potter, Senior Associate, SRF Consulting Group, Inc.

Potter served as the project’s principal investigator.

What Was the Need?

MnDOT is responsible for mowing roadsides along 14,000 centerline miles of highways for environmental and safety reasons. This is an enormous and critical task, requiring efficient use of employee time and mowing equipment, and efforts to avoid the spreading of noxious weeds, which will lead to increased use of herbicides.

A promising technology that many departments of transportation (DOTs) have installed is automated vehicle location (AVL). AVL systems provide a precise geographic location for DOT-owned vehicles so that real-time data can be obtained on field operations. This technology has been used for snowplowing and other fleet vehicle operations. However, only a few DOTs have used it for mowing operations.

To determine if AVL technology should be used in its
mowing operations, MnDOT undertook a pilot project involving 30 of its mowers. The locations chosen were Metro District roadsides, as MnDOT had previously invested in creating a geographic information system map of noxious weeds on those roadsides.

What Was Our Goal?

The goals of the pilot project were to:

  • Generate protocols for hardware installation and software training.
  • Set up the system for communicating data from the mowers to internal MnDOT servers.
  • Develop accomplishment reports based on data collected by the AVL units.
  • Develop and provide initial training to operators and supervisors.
  • Optimize the mower routes used.

What Did We Do?

For the 2015 and 2016 mowing seasons, researchers fitted 30 Metro District tractors with AVL technology, sensors and communication equipment.

The first stage of the project focused on developing the software interface required for the AVL system. The application had to provide a view of the mower’s exact location so that the mower operator could avoid noxious weeds. Data would be collected through an in-vehicle controller unit and transferred to MnDOT for analysis via a Verizon AirCard system installed on each mower.

Mechanics installed metal racks within each of the 30 mowers to protect the Ameritrak AT-500 AVL hardware unit. A video screen was mounted on the top of the rack. A reporting system was developed for use by operators, supervisors and managers. Training sessions were scheduled at the start of each season and when new operators were hired.

Interior view of mower cab showing location of AVL unit.

What Did We Learn?

The project achieved its initial goals of developing protocols for hardware and software, creating electronic reporting and capturing real-time data.

The research team gained the following insights during the planning and field-testing stages of the project:

  • Substantial time is needed to adequately develop and test the AVL software and hardware.
  • Implementing the system also requires considerable time due to resource limitations, and after implementation, it takes multiple mowing seasons to quantify weed and herbicide reductions.
  • MnDOT mower operators and supervisors recognized the value of the AVL system in improving the efficient use of their time, eliminating the drafting of written reports, and giving MnDOT a more accurate record of acreage mowed.
  • Since the tractors operated at such slow speeds, the initial data captured were too imprecise to analyze. But with software adjustments, this issue was resolved.
  • Installation of the AVL unit could have an impact on the operation of the tractor because the additional electrical burden that the unit places on the tractor battery may require the tractor to be sent to the manufacturer for inspection.

What’s Next?

The initial success of the pilot project provided the basis for continued use of AVL technology in Metro District mowing operations during the 2017 season and possibly beyond. MnDOT is currently evaluating whether this project has provided enough data to expand AVL to other districts in the state. The investigators estimate that after full implementation, MnDOT could save $100,000 per year.

MnDOT may consider installing AVL technology in other agency equipment to optimize and monitor maintenance activities.


This Technical Summary pertains to Report 2017-11, “An Innovative Approach to Smarter Mowing, Utilizing Automated Vehicle Location to Enhance Mowing Operations,” published April 2017.

Additional materials:

Knowing While Mowing: GPS Keeps Maintenance Workers Out Of the Weeds

As temperatures fall and days get shorter, MnDOT Metro District maintenance workers are wrapping up a season of mowing grass along roadsides and in medians that they hope will prove a little more efficient than in the past.

Thanks to a research project that installed GPS devices in tractor cabs, operators have a better sense of exactly which areas they need to mow and which areas should be left alone. Five Metro District tractors were tested in 2015. This year, more than 40 tractors were fitted with the automated vehicle location (AVL) technology, which includes a GPS antenna, an on-board central processing unit (CPU) and an in-cab screen with a user interface.

Trisha Stefanski, Metro District asset management engineer, expects one of the biggest benefits of the project to be a reduction in herbicide use. Maintenance crews use herbicide to control the spread of noxious weeds that sometimes get spread during mowing operations. Mapping exactly where noxious weeds are, and providing that information to operators on a real-time, in-cab screen and user interface helps them mow around those areas.

“We’re really hoping it will reduce the amount of herbicide that we’re putting on our roadways by 50 percent,” Stefanski said. “We’re not certain that will be the number, but that’s what we’re hoping for. We think just not mowing those areas will not spread as many noxious weeds and so we don’t have to apply as much herbicide.”

Metro District operators, such as Jesse Lopez, give the AVL technology rave reviews.

“Basically you can see what you shouldn’t mow and what you should mow. So, it makes it easy for me. It’s just like playing a game,” Lopez said. “This actually helps me to optimize what my job is. I know exactly where I’m at and where I’m going. I think everyone should use it – absolutely everybody who is in a mowing situation or a plowing situation.”

In addition, the AVL technology helps maintenance supervisors keep tabs on exactly where their operators are in real time. It also helps supervisors complete reports by automatically providing the geographic areas where mowing has been completed.

Stefanski says the project has gone really well, and she hopes collecting more data over another mowing season will show real savings on herbicide use. In the meantime, she is thinking of other ways AVL technology could be applied to maintenance operations.

“What I really like about the project is that we are taking something used in a lot snow plows and a lot of other technologies – cars, other things, maybe UPS uses them – and we’re putting it into maintenance operations,” Stefanski said. “Having it for mowing, we can also use it for smooth pavements. We can also use it for other things in mowing operations.”