Lesson

RSU triangulation techniques and inertial GPS solutions can improve geolocation accuracy for connected vehicles operating in dense urban environments.

New York City CV Pilot considered location correction solutions to address GPS positioning challenges associated with the cities "urban canyons"


New York City; New York; United States


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Lesson Learned

New York City is known for its "urban canyons" which provide a challenging environment for GNSS (Global Navigation Satellite System - a broader term including GPS and other similar systems) technology; as a result, additional techniques were required in the onboard units’ (OBUs) positioning algorithms to provide the accuracy needed for many of the V2V and V2I safety applications. Such augmentation of vehicle positioning would thus help provide continuous access to GPS positioning data so that the safety applications could continue operating while the connected vehicles passed under bridges, elevated roadways, through tunnels etc. while navigating the typical Manhattan streetscapes and traffic environment.

It was originally proposed that NYC use positioning augmentation approaches that used Radio Technical Committee for Maritime Service (RTCM) messages. The NYCDOT team considered several options and required potential vendors to consider a variety of techniques (e.g., RSU triangulation, Inertial navigation system (INS), Map Matching) to improve the overall location accuracy. These techniques were each likely to result in the need for standardization, connection to vehicle data buses, and establishment of accuracy performance requirements that consider when multiple inputs or methods are combined and address potential loss of one or more inputs.

When considering positioning correction techniques, it should be noted that the local receiver needs to be able to handle the type of corrections needed for a given method. Not all GNSS receivers are capable of using all corrections, and not all GNSS receiver and antenna combinations perform equally well under different conditions (e.g., rejection of multi-path signals). Different GNSS receivers also have varying capability to receive GNSS signals at different frequencies and from other non-GPS sources (e.g., GPS-like systems such as the Russian GLONASS or EU Galileo satellite systems). Receiving additional signals from other satellites can help to mitigate urban canyon issues since there are more potential satellites that are not blocked by buildings.

NYC eventually came to the conclusion that the urban canyon environment posed challenges to position accuracy that were of a magnitude larger than correctable by RTCM. As a result, RTCM was removed from project scope. NYC’s Onboard Unit vendors eventually decided on using a combination of RSU triangulation and inertial GPS.

As the state of positioning technology evolves over time, the capabilities, costs, and availability of solutions will change. Research is ongoing for improving positioning performance in urban environments. Currently, there are significant tradeoffs in cost versus performance, as the size of the surveying receiver market is orders of magnitude lower than the size of the automotive market. However, this has potential to change as the market changes due to automation, satellite constellation enhancements, etc.


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Source

Connected Vehicle Pilot Positioning and Timing Report: Summary of Positioning and Timing Approaches in CV Pilot Sites

Author: Chang, James and Ed Fok

Published By: USDOT Federal Highway Administration

Other Reference Number: Report No. FHWA-JPO-18-638

URL: https://rosap.ntl.bts.gov/view/dot/35427

Lesson Contacts

Lesson Analyst:

Kathy Thompson


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States

New York

Countries

United States

Goal Areas

Safety

Keywords

coordinated signals, signal coordination, centralized signal control, signal synchronization, traffic signals, advanced signal control, signal timing optimization, coordinated signal control, advanced signal controller, traffic signal retiming, retiming, photo enforcement, red light cameras, red light running, automated enforcement, run red lights, RLR, red light runners, photo-red, speed cameras, automated speed enforcement, photo radar

Lesson ID: 2018-00819