Lane-Level Vehicle Positioning : Integrating Diverse Systems for Precision and Reliability

NHTSA · 2013 · ROSA P / United States. Federal Highway Administration

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Summary

This fact sheet outlines the objectives and methodology of the “Innovative Approaches for Next Generation Vehicle Positioning” project, an Exploratory Advanced Research (EAR) Program study conducted at the University of California, Riverside, and funded by the Federal Highway Administration (FHWA). The research addresses the critical limitation of current vehicle positioning systems, specifically that integrated Global Positioning System/Inertial Navigation System (GPS/INS) technology cannot consistently provide the lane-level precision and reliability required for advanced driver assistance applications. Standard INS systems accrue error without correction, while GPS signals are frequently blocked by obstacles, and feature-based technologies like cameras, LIDAR, and RADAR depend on the presence of detectable structural features. The study aims to develop a low-cost, public-sector solution that integrates data from satellites, terrestrial radio signals, and feature-based sensors to ensure robust positioning in any location, weather, or visibility condition. The project employed a phased approach to evaluate viable positioning architectures. In Phase I, researchers compared candidate technologies based on accuracy, reliability, availability, continuity, and deployment costs. The evaluation included GPS variants (standard, differential, and carrier phase differential), terrestrial radio sources (pseudolites, cell phones, digital TV, AM/FM radio, and packet radio), and feature-based sensors (vision, RADAR, and LIDAR). Based on this assessment, the investigators selected FM and digital TV radio navigation methods, along with vision, LIDAR, and RADAR, for further exploration in Phase II. These selected technologies serve as adjuncts to a primary dual system consisting of inertial navigation aided by Carrier Phase Differential GPS (CPDGPS), which provides the necessary centimeter-level precision. Phase II focuses on developing and evaluating prototype integrated positioning systems using a three-step methodology. First, the system fuses asynchronous data from diverse sensors to reliably estimate vehicle state. Second, high-rate sensor readings are integrated through a moving vehicle model to produce a continuously available state estimate. Third, integrated errors from high-rate sensors are corrected using data from the diversity of aiding sensors. The researchers plan to conduct field tests on sufficiently advanced prototypes and propose a full-scale deployment plan. The significance of this research lies in its potential to accelerate the maturity of the Connected Vehicle Program and advance intelligent transportation systems. By identifying the strengths and limitations of various sensors, components, algorithms, and strategies, the project aims to provide a robust lane-positioning architecture that supports roadway safety, mobility, and reduced energy use. The findings are intended to benefit automotive manufacturers and other federal agencies, offering a major step forward in realizing the safety and mobility benefits of next-generation vehicle positioning technologies.

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• lane positioning