High definition maps in urban context

Author:

Zang Andi1,Chen Xin2,Trajcevski Goce3

Affiliation:

1. Northwestern University

2. HERE North America

3. Iowa State University

Abstract

Part of the challenges in the quest for smart cities is to enable effective navigation for different types of mobile users: from pedestrians, through drivers, to autonomous vehicles. While the data sources to facilitate such tasks abound, one of the pressing problems is how to enable efficient management and download of the data needed to populate the screens of devices with the appropriate visualization. In this paper, we present an overview of the different issues and the main features of the existing technologies that, in one way or another, could be used as foundations for effective solution for generating quality maps. We also discuss the possible approaches for addressing such issues in the context of accurate self-localization of vehicles.

Publisher

Association for Computing Machinery (ACM)

Reference28 articles.

1. Accurate vehicle self-localization in high definition map dataset

2. Federal Highway Administration. Highway statistics 2013 2013. Federal Highway Administration. Highway statistics 2013 2013.

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