Global positioning system (GPS)

An ongoing research project examines guidance systems, which can take over control of a vehicle if the driver becomes incapacitated. Part of this project includes an evaluation of a Differential Global Positioning System (DGPS) for vehicle-based lane sensing. This report documents the results of tests of the 5 Hz NovAtel RT20 DGPS receiver. A series of 32 static tests found the overall mean and standard deviation for the offset errors within specifications. In a series of dynamic tests, in which the vehicle was driven around the track at speeds of 20-35 miles per hour, after removing the effect of the GPS receiver's latency, the DGPS determined position exhibited a mean offset error of -17.3 cm (-6.82 in) and a mean standard deviation of 25.5 cm (10.1 in) in the direction of vehicle motion. In the direction perpendicular to vehicle motion, the mean offset was 4.57 cm (1.8 in) with a mean standard deviation of 39.6 cm (15.6 in). With no overhead obstructions in these tests, continuous satellite lock was possible. Tests at higher speeds based on a more accurate methodology are planned for the future.

Advanced Traveler Information Systems (ATIS) offer the potential to help a driver find the quickest and safest route to a destination. An effective navigation system requires effective route planning services, which need to provide three facilities: route computation, route evaluation, and route display. This project focuses on route planning algorithms for ATIS. The cost models and performance studies in this report show that single-pair algorithms can outperform traditional algorithms in many situations.

This Technical Summary 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.

This Technical Summary pertains to report 2017-49, Using Mobile Device Samples to Estimate Traffic Volumes, published December 2017.

This Technical Summary pertains to Report 2013-14, “Developing Twin Cities Arterial Mobility Performance Measures Using GPS Speed Data,” published May 2013.

This Technical Summary pertains to Report 2014-14, “Using Truck GPS Data for Freight Performance Analysis in the Twin Cities Metro Area,” published March 2014.

This Technical Summary pertains to report 2021-17, Development and Demonstration of an In-Vehicle Lane Departure Warning System Using Standard GPS Technology.

A lane departure warning system (LDWS) has significant potential to reduce crashes on roads. Most existing commercial LDWSs use some kind of image processing techniques with or without Global Positioning System (GPS) technology and/or high-resolution digital maps to detect unintentional lane departures. However, the performance of such systems is compromised in unfavorable weather or road conditions, e.g., fog, snow, or irregular road markings. Previously, we proposed and developed an LDWS using a standard GPS receiver without any high-resolution digital maps. The previously developed LDWS relies on a road reference heading (RRH) of a given road extracted from an open-source, low-resolution mapping database to detect an unintentional lane departure. This method can detect true lane departures accurately but occasionally gives false alarms, i.e., it can issue lane departure warnings even when a vehicle is within its lane. The false alarms occur due to the inaccuracy of how the RRH originated from an inherent lateral error in open-source, low-resolution maps. To overcome this problem, we proposed and developed a novel algorithm to generate an accurate RRH for a given road using a vehicle's past trajectories on that road. The newly developed algorithm that generates an accurate RRH for any given road has been integrated with the previously developed LDWS and extensively evaluated in the field for detection of unintentional lane departures. The field test results showed that the newly developed RRH Generation algorithm significantly improved the performance of the previously developed LDWS by accurately detecting all true lane departures while practically reducing the frequency of false alarms to zero.

In this study; the Texas A&M Transportation Institute (TTI) conducted an independent; follow-up evaluation of StreetLight Data's 2019 traffic count estimates using MnDOT sources of traffic count data. At 442 permanent benchmark locations; TTI found that average annual daily traffic ( AADT) estimation accuracy by StreetLight Data has improved significantly since the 2017 evaluation; especially in moderate- to high-volume categories (i.e.; more than 10;000 AADT). The mean absolute error ranged from 8% to 10% for locations greater than 10;000 AADT and gradually increased to 42% for sites with less than 1;000 AADT. TTI also found significant overestimation bias for low-volume roadways (i.e.; less than 2;500 to 5;000 AADT). This result was present in the permanent benchmark sites and more pronounced in the 265 short-duration count sites. Based on these findings; TTI recommends that MnDOT consider a phased approach to using probe-based traffic count estimates: 1) Continue to maintain MnDOT permanent counter sites; 2) start using probe-based counts for about 90% of the moderate- to high-volume roadways (20;000 or more AADT); 3) continue to use traditional short-duration counts at the remaining 10% of the moderate- to high-volume roadways as a spot check to ensure that probe-based AADT estimates remain within acceptable tolerances in the next five to ten years; 4) periodically monitor the error of AADT estimates on low- to moderate-volume roadways (less than 20;000 AADT); and 5) once acceptable error tolerances for these lower-volume categories are reached; repeat Step 2 for these lower-volume categories.

A Lane-Departure Warning System (LDWS) and Advance Curve-Warning System (ACWS) are critical among several Advanced Driver-Assistance Systems (ADAS) functions; having significant potential to reduce crashes. Generally; LDWS use different image processing or optical scanning techniques to detect a lane departure. Such LDWS have some limitations such as harsh weather or irregular lane markings can influence their performance. Other LDWS use a GPS receiver with access to digital maps with lane-level resolution to improve the system's efficiency but make the overall system more complex and expensive. In this report; a lane-departure detection method is proposed; which uses a standard GPS receiver to determine the lateral shift of a vehicle by comparing a vehicle's trajectory to a reference road direction without the need of any digital maps with lane-level resolution. This method only needs road-level information from a standard digital mapping database. Furthermore; the system estimates the road curvature and provides advisory speed for a given curve simultaneously. The field test results show that the proposed system can detect a true lane departure with an accuracy of almost 100%. Although no true lane departure was left undetected; occasional false lane departures were detected about 10% of the time when the vehicle did not actually depart its lane. Furthermore; system always issues the curve warning with an advisory speed at a safe distance well ahead of time.