Automatic intersection map generation task 10 report.

Zheng, Jianfeng; Liu, Henry X.; Parikh, Jay; Crash Avoidance Metrics Partnership

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Automatic intersection map generation task 10 report.

2016-02-29
By Zheng, Jianfeng ; Liu, Henry X. ; Parikh, Jay

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English

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Alternative Title:

Automatic intersection map generation : V2I safety applications project;task 10 report.;
Creators:

Zheng, Jianfeng ; Liu, Henry X. ; Parikh, Jay

Zheng, Jianfeng ; Liu, Henry X. ; Parikh, Jay Less -
Corporate Creators:

Crash Avoidance Metrics Partnership
Corporate Contributors:

United States. Federal Highway Administration ; United States. Joint Program Office for Intelligent Transportation Systems

United States. Federal Highway Administration ; United States. Joint Program Office for Intelligent Transportation Systems Less -
Subject/TRT Terms:

[+]

Accuracy Automatic Vehicle Detection And Identification Systems Basic Safety Message Center Lines Connected Vehicle Data Collection Feasibility Analysis Intersection Map Intersections Laser Radar Map Generation Mapping Maps Roadside Equipment Traffic Lanes Traffic Signal Phases V2I System Vehicle To Infrastructure Communications
Publication/ Report Number:

FHWA-JPO-16-416
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final report
Corporate Publisher:

United States. Federal Highway Administration ; United States. Joint Program Office for Intelligent Transportation Systems

United States. Federal Highway Administration ; United States. Joint Program Office for Intelligent Transportation Systems Less -
Abstract:

This report describes the work conducted in Task 10 of the V2I Safety Applications Development Project. The work was performed by the University of

Michigan Transportation Research Institute (UMTRI) under contract to the Crash Avoidance Metrics Partners LLC (CAMP) Vehicle to Infrastructure

(V2I) Consortium. Participating companies in the V2I Consortium were FCA US LLC, Ford, General Motors, Hyundai-Kia, Honda, Mazda, Nissan,

Subaru, Volvo Truck, and VW/Audi. This project investigated the feasibility of automatically generating intersection maps in SAE J2735 MAP format

using Basic Safety Messages (BSMs) received by Roadside Units (RSUs). A procedure for classifying vehicle trips through the intersection and

subsequently estimating lane centerlines was developed. In addition, a method for associating vehicle movements to the green signal phase was also

developed using Signal Phase and Timing (SPaT) messages. BSM data from five intersections used in the Safety Pilot Model Deployment Project

were analyzed. The estimated maps were compared to reference maps produced from LIDAR surveys of the intersections. With 48 traffic lanes in

total, 43 lanes and associated vehicle movements were correctly identified using the estimation approach. Five lanes were not successfully identified

due mainly to a lack of BSM data. For the identified lanes, two measurements of accuracy were calculated: the mean distance of the estimated

geometry node points to closest points in the surveyed lane centerline geometry and the maximum distance of estimated points and surveyed lane

geometry. On average, the mean distance was found to be 0.5 meter and maximum distance was found to be 1.2 meters between the estimated maps

and reference maps. Overall, this project demonstrated the significant potential of using BSM data for estimation of an intersection map as well as

association of the vehicle lanes (vehicle movements) to the traffic signal phases.
Format:

PDF
Funding:

DTFH6114H00002
Collection(s):

ITSJPO Digital Library Federal Highway Administration
Main Document Checksum:

[+]

urn:sha256:db0c282677e8a82efbe0cbdf63c058cfb6eea0db08f8ece2e61c7f2c42cd1e1b
Download URL:

https://rosap.ntl.bts.gov/view/dot/3601/dot_3601_DS1.pdf
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Automatic intersection map generation task 10 report.

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