# Challenges in Partially-Automated Roadway Feature Mapping Using Mobile Laser Scanning and Vehicle Trajectory Data

## TL;DR

This paper discusses the challenges and proposes a new method for converting mobile laser scanning data into digital maps of roadway features, aiding automated map creation for connected vehicle applications.

## Contribution

It introduces a novel processing and feature extraction method for transforming MTLS data into SAE-J2735 map messages, demonstrating its application on multiple intersections.

## Key findings

- Successful generation of SAE-J2735 map messages for eleven intersections
- Identification of remaining challenges in automated EDM development
- Discussion of future research directions in mobile laser scanning data processing

## Abstract

Connected vehicle and driver's assistance applications are greatly facilitated by Enhanced Digital Maps (EDMs) that represent roadway features (e.g., lane edges or centerlines, stop bars). Due to the large number of signalized intersections and miles of roadway, manual development of EDMs on a global basis is not feasible. Mobile Terrestrial Laser Scanning (MTLS) is the preferred data acquisition method to provide data for automated EDM development. Such systems provide an MTLS trajectory and a point cloud for the roadway environment. The challenge is to automatically convert these data into an EDM. This article presents a new processing and feature extraction method, experimental demonstration providing SAE-J2735 map messages for eleven example intersections, and a discussion of the results that points out remaining challenges and suggests directions for future research.