A Study on High Definition Road Map Construction Using Aerial Photography

2020 ◽  
Vol 28 (3) ◽  
pp. 69-76
Author(s):  
Tae Seok Choi ◽  
Ha Su Yoon ◽  
Yun Soo Choi ◽  
Won Jong Lee ◽  
Soo Young Chang
Keyword(s):  
Aerial Photography ◽  
High Definition ◽  
Road Map ◽  
Map Construction

Mining crowdsourced trajectory and geo‐tagged data for spatial‐semantic road map construction

2021 ◽  
Author(s):  
Jincai Huang ◽  
Yunfei Zhang ◽  
Min Deng ◽  
Zhengbing He
Keyword(s):  
Road Map ◽  
Map Construction

Outdoor Map Construction Based on Aerial Photography and Electrical Map Using Multi-Plane Laser Range Scan Data

2013 ◽  
Vol 25 (1) ◽  
pp. 5-15 ◽  
Author(s):  
Taketoshi Mori ◽  
◽  
Takahiro Sato ◽  
Aiko Kuroda ◽  
Masayuki Tanaka ◽  
...  
Keyword(s):  
Aerial Photography ◽  
Sensor Data ◽  
Digital Map ◽  
Personal Mobility ◽  
Laser Range ◽  
Grid Map ◽  
Map Construction ◽  
Scan Data ◽  
Edge Based ◽  
Accumulated Error

This research is on personal mobility that estimates its self position on a sensor data map created from sensor data, acquired from laser range scan sensors and/or other sensors, and annotates various multiple items of information on a digital map. This paper describes a method of creating an edge-based grid map from both aerial photography and an electricalmap for this purpose and a way and its realization to estimate position and to construct outdoor maps from multi-plane laser range scan data on the grid map. Since threedimensional scanning is rather difficult and the scan rate is low, we used two-dimensional scanning that enables movement without slowing it down by scanning multiple horizontal and/or slanted planes. Experimental results show that the system is able to ensure the accuracy of accumulated error within 2 m by integrating aerial photography and electrical maps plus multiplane scanning.

Using high-definition aerial photography to search in 3D for malleefowl mounds is a cost-effective alternative to ground searches

2015 ◽  
Vol 21 (3) ◽  
pp. 208 ◽  
Author(s):  
Scott Thompson ◽  
Graham Thompson ◽  
Jessica Sackmann ◽  
Julia Spark ◽  
Tristan Brown
Keyword(s):  
Aerial Photography ◽  
Cost Effective ◽  
Ground Level ◽  
Relative Cost ◽  
High Definition ◽  
Above Ground Level ◽  
Assessment Technique ◽  
Cost Effective Alternative ◽  
Ground Grid ◽  
The Cost

The threatened malleefowl (Leipoa ocellata) constructs a large (often >3 m) incubator mound (nest) that is considered a useful proxy for surveying its presence and abundance in the context of an environmental impact assessment. Here we report on the effectiveness and relative cost of using high-definition aerial photography to search in 3D for malleefowl mounds by comparing results to those of earlier ground-based searches. High-definition colour aerial photography was taken of an area of ~7014 ha and searched in 3D for malleefowl mounds. All 24 active (i.e. in use) malleefowl mounds known before the examination of aerial photography were detected using the new assessment technique. Of the 108 total mounds (active and inactive) known from earlier on-ground surveys, 94 (87%) were recorded using the new technique. Mounds not detected were all old and weathered, many barely above ground level and some with vegetation growing in the crater. Approximately 6.3% of the identifications considered ‘confident’ and ~35.0% considered ‘potential’ based on the aerial photography proved to be false positives. The cost of detecting malleefowl mounds using the interpretation of high-definition 3D colour aerial photography and then subsequently examining these areas on the ground is appreciably cheaper than on-ground grid searches.

Autonomous Robotic Exploration by Incremental Road Map Construction

2019 ◽  
Vol 16 (4) ◽  
pp. 1720-1731 ◽  
Author(s):  
Chaoqun Wang ◽  
Wenzheng Chi ◽  
Yuxiang Sun ◽  
Max Q.-H. Meng
Keyword(s):  
Road Map ◽  
Robotic Exploration ◽  
Map Construction

Lane-Marker-Based Map Construction and Map Precision Evaluation Methods Using On-Board Cameras for Autonomous Driving

2020 ◽  
Vol 32 (3) ◽  
pp. 613-623
Author(s):  
Kenta Maeda ◽  
Junya Takahashi ◽  
Pongsathorn Raksincharoensak ◽  
◽  
Keyword(s):  
Autonomous Vehicles ◽  
Evaluation Method ◽  
Autonomous Driving ◽  
Sufficient Information ◽  
High Definition ◽  
Special Purpose Vehicle ◽  
Construction Methods ◽  
Map Construction ◽  
Mapping System ◽  
Cost Efficient

This report describes a map construction and evaluation method based on lane-marker information for autonomous driving. Autonomous driving systems typically require digital high-definition (HD) maps to correct the current position of autonomous vehicles by using localization techniques. However, an HD map is usually costly to generate because it requires a special-purpose vehicle and mapping system with precise and expensive sensors. This report presents a map construction method that uses cost-efficient on-board cameras. We implement two types of map construction methods with two different cameras in terms of range and field of view and test their performances to determine the minimum sensor specification required for autonomous driving. This report also presents a constructed map evaluation method to determine the “usability” of the map for autonomous driving. Given that the system cannot obtain “true” positions of landmarks, the method judges whether the constructed map contains sufficient information for localization via the presented indices “lateral-distance error.” The methods are verified based on mapping and localization errors determined via manual driving tests. Furthermore, the smoothness of steering maneuvers is determined by conducting autonomous driving tests on a proving ground. The results reveal the necessary conditions of sensor requirements, i.e., the constant visibility of landmarks is one of the key factors for ego-localization to conduct autonomous driving.

A Study on High Definition Road Map Usability for Application of Autonomous Driving Function

2021 ◽  
Vol 22 (11) ◽  
pp. 1893-1902
Author(s):  
Jong-Min Oh ◽  
Kwang-Jin Han ◽  
Yun-Soo Choi ◽  
Byeong-Heon Min ◽  
Sang-Min Lee
Keyword(s):  
Autonomous Driving ◽  
High Definition ◽  
Driving Function ◽  
Road Map

Wavelet Transform-Based High-Definition Map Construction From a Panoramic Camera

2021 ◽  
Vol 26 (5) ◽  
pp. 569-576
Author(s):  
Hanyang Zhuang ◽  
Xuejun Zhou ◽  
Chunxiang Wang ◽  
Yuhan Qian
Keyword(s):  
Wavelet Transform ◽  
High Definition ◽  
Map Construction
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