High Definition Corridor Mapping From Images Sequences

Abstract

The density, high accuracy, and rapid collection of geographical data for road surface and surrounding objects and the extraction of meaningful information from these data increases its importance in line with technological developments. Artificial intelligence studies and developments in cloud technology have affected the automotive industry as well as every sector and have enabled the development of driverless vehicle technology. In order to safely drive with autonomous vehicles, high definition maps that contain detailed information for road surface and its surrounding objects with high precision at centimeter-level must be used. In this context, in recent years, the development of mobile mapping systems (MMS) consisting of low-cost sensors and the development of algorithms for the evaluation of the data obtained from these systems have become increasingly popular. In this study, it was investigated whether HD maps can be obtained by using low-cost imaging sensors.

Comparison of Unmanned Aerial Vehicle-LiDAR and Image-Based Mobile Mapping System for Assessing Road Geometry Parameters via Digital Terrain Models

“…To determine road geometry parameters, various survey techniques based on accuracy specifications can be used. Surveys can be implemented with traditional techniques, such as total station (TS) ( 4 ), digital levels ( 5 ), and real-time kinematics-global navigation satellite system (RTK-GNSS) ( 6 ). Obtaining the slopes directly with TS is possible by measuring two points on the left and right sides of a road.…”