吃晚饭porting artificial intelligence solution to parking problem

Author:Linda Duffy

With a finite number of parking spaces and an increasing number of cars, frustration and inconvenience related to parking is growing. Recognising this as a problem, Manuela Rasthofer, CEO ofTerraLoupe GmbH, launched a project tocombine artificial intelligence and orthorectified aerial imageryto create an accurate inventory of available parking lots and spaces throughout Germany.

Mapping available parking

Parking a car can be a stressful and time-consuming activity, and in the future, autonomously navigated vehicles will be searching for spaces without a driver to help. The need for high-definition digital maps that accurately measure and identify all types of objects, including parking spaces, is quickly becoming a reality.

TerraLoupe GmbH is a technology start-up based in Munich, Germany, that focuses on combining geodata and computer analytics in innovative ways. Starting with high-resolution orthoimagery, TerraLoupe appliesmachine learning algorithms to detect and measure objects in the physical world, such as buildings, roads, and trees, to create data-rich 3D models.

“To address the growing parking problem, we wanted to see if it was feasible to detect and assess parking lots using aerial imagery and artificial intelligence,”says Rasthofer.“By automating the extraction of features and digital content, we thought we could greatly reduce the time it took to create maps, without sacrificing the accuracy.”

Acost-effective method of creating digital mapsis particularly interesting to Tier one automotive suppliers and original equipment manufacturers (OEMs) to support the autonomous navigation industry; however, many other industries can make use of the information as well.

HxGN Content Program delivers

Semantic lane model created out of detected lane markings based on 15 centimetres GSD data in Martinsburg

In 2014, theHxGN Content Programbegan collecting speculative off-the-shelforthorectified imageryof the US, parts of Europe, and populated areas of Canada tocreate a database available to customers. The goal was to acquirecloud-free 30-cm resolution, 4-band imageryover less populated areas, and15-cm resolutionover metro areas with apopulation greater than 50,000.

Through the HxGN Content Program, TerraLoupe obtained15-cm resolution orthoimagery of Berlinto test its internally developed object-identification algorithms. The initial work on Berlin tookeight weeks to train the algorithmsto accurately identify and categorise parking spaces, followed by justthree days to analyse and produce mapsfor all of Germany.

“Access to imagery through the HxGN Content Programallows us todownload the geographic locationswe need, and thentrain our algorithms on the new data,”explained Rasthofer.“There are always slight differences in architecture, infrastructure, and road systems that are unique to each country. We check the confidence interval for each object and recheck low percentages. As we correct errors, the algorithms continue to learn and improve until we achieve a very high accuracy level.”

Theaerial orthoimages available through the HxGN Content Programgo through a rigorous QA/QC process to ensure delivery of survey-grade images.“The HxGN Content Program best suits the needs of our customers in theareas of autonomous driving, parking assistance, and loss reportsfor insurance/reinsurance companies,”says Rasthofer.“We also successfully deliverintelligence related to infrastructure, utilities, railways, and others for a variety of purposes.”

urate mapping

TerraLoupe’s project shows thathigh-resolution aerial orthoimages combined with machine learningcan effectively be used to extract digital content. The parking analysis provides useful information, such as the locations, entrances and exits of parking lots and the number of cars of different categories (compact, medium-sized, large) that can fit in each lot. Urban planners, delivery people, taxi drivers, and patrons in congested retail areas could all benefit from this improved parking intelligence.

“The availability ofhigh-resolution, high-accuracy imagerydetermined where we started the project; however, we intend to perform this analysis on all of Europe as data becomes available through Hexagon, and we’d like to expand our services into the U.S.,”says Rasthofer.“Overall our goal is to efficiently extract all types of objects andcreate a complete digital environment.”

Obtainingaerial imagery is fasterand moreefficientthan terrestrial methods, allowing more frequent updates, which is crucial for many applications. Hexagon’s global operations generate widespread availability of imagery and good business partnerships with data providers to continue to meet thegrowing demand for digital maps.