Monitoring and Forecasting of Key Functions and Technologies for Automated Driving

Abstract

Companies facing transformation in the automotive industry will need to adapt to new trends, technologies and functions, in order to remain competitive. The challenge is to anticipate such trends and to forecast their development over time. The aim of this paper is to develop a methodology that allows us to analyze the temporal development of technologies, taking automated driving as an example. The framework consists of a technological and a functional roadmap. The technology roadmap provides information on the temporal development of 59 technologies based on expert elicitation using a multi-stage Delphi survey and patent analyses. The functional roadmap is derived from a meta-analysis of studies including 209 predictions of the maturity of automated driving functions. The technological and functional roadmaps are merged into a consolidated roadmap, linking the temporal development of technologies and functions. Based on the publication analysis, SAE level 5 is predicted to be market-ready by 2030. Contrasted to the results from the Delphi survey in the technological roadmap, 2030 seems to be too optimistic, however, as some key technologies would not have reached market readiness by this time. As with all forecasts, the proposed framework is not able to accurately predict the future. However, the combination of different forecast approaches enables users to have a more holistic view of future developments than with single forecasting methods.

Generation of Topical Educational Content by Estimation of the Number of Patents in the Digital Field

“…Further work may be devoted to the formation of the design of experiments to compare the quality of various approaches [19][20][21][22] to the identification of topical technologies, the selection and assessment of the effect of sources of keywords and patent activity data on the completeness of inclusion of topical technologies, as well as the selection of clustering methods to automate the identification of groups of evaluated technologies. In addition, the process of automating the construction of educational programs based on data from open sources can be considered in future research.…”

“…Patent analysis is used in many high-tech fields, such as automated driving [19], industrial engineering [20], tracking the evolution pathways of some nanogenerator technologies [21], and electric vehicle design [22].…”

Identifying the Technology Opportunities and the Technology Taxonomy for Railway Static Inverters With Patent Data Analytics

“…Kronemeyer et al [22] developed a method using semantic anchor points to represent a company's core competencies and use these semantic anchor points for monitoring competitor's innovation activities. Ulrich et al [23] developed a methodology for forecasting technology trends that can be used by a wide range of users. Machuca-Martinez et al [24] show a patent database for Coronaviruses that provides an overview of the patenting activity and trends in focused antiviral therapy with the use of triazole-based compounds, glycoprotein, and protease-inhibitors as a possible treatment.…”

Implementasi Algoritma Exponential Smoothing Untuk Prediksi Penjualan Pada Platform E-Commerce

“…Agar tetap kompetitif, perusahaan perlu terus menganalisis tidak hanya pasar dan lingkungan kompetitif tetapi juga pengembangan teknologi utama yang membentuk dan memungkinkan keberhasilan implementasi model bisnis dari waktu ke waktu (Ulrich et al, 2022). Model Drop-shipping dikembangkan setelah munculnya e-commerce.…”