Abstract
Abstract. Automated driving has received a high degree of public attention in recent years as it will lead to profound changes in mobility, society and urban development. Despite several product announcements from automobile manufacturers and mobility providers, many questions have not yet been answered completely. The need of lane-level HD maps was widely discussed and has been the reason for company acquisitions. HD maps are tailored towards supporting the operation of an automated vehicle. However, the development of this technology also requires road space models, but with a completely different focus and level of detail. Therefore, this article investigates the system development and testing challenges of automated driving. Based on this, requirements of road space models for developing automated driving are derived and gaps to current standards are indicated.
Highlights
Automating the tasks of a driver has several potentials
The objective of this paper is to analyze the requirements for road space models in the context of automated driving
This article discussed the approaches of how an automated driving system functions and its testing challenges
Summary
Full automation will pave the way towards mobility-on-demand services, where a circulating fleet offers rides and overall costs are reduced due to high utilization rates. A main reason for this involves the exceptionally high number of different traffic scenarios that can occur on public roads. Since the simulation is conceived as a central element for testing the correct functioning of the system, the modeling of the vehicle’s environment becomes inevitable. The objective of this paper is to analyze the requirements for road space models in the context of automated driving. The functioning and testing of automated driving systems is discussed and the main requirements for road space models are derived. Current standards and formats capable of modeling road spaces are examined and evaluated against those requirements
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