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Empirical Analysis of Strategies Employed Within an ICT Curriculum to Increase the Quantity of Graduates Read chapter Read first chapter

2021 | OriginalPaper | Chapter

Smart Low-Speed Self-Driving Transportation System

Authors : Zhenghong Wang, Bowu Zhang

Published in: Advances in Software Engineering, Education, and e-Learning

Publisher: Springer International Publishing

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Abstract

This chapter presents a commercial application of self-driving vehicles and analyzes the strengths, weaknesses, opportunities, and threats (SWOT) related to the application. To illustrate the market potential of the application, we explore two use cases to present detailed application design, highlight prototyping activity, and identify risks and needs for risk management. In addition, we also discuss target customers and marketing strategies for the proposed application.

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Literature
1.
W. Wang, D. Zhao, Extracting traffic primitives directly from naturalistically logged data for self-driving applications. IEEE Rob. Autom. Lett. 3(2), 1223–1229 (2018)CrossRef
2.
L. Liu, H. Li, J. Liu, C. Karatas, Y. Wang, M. Gruteser, Y. Chen, R.P. Martin, BigRoad: Scaling road data acquisition for dependable self-driving, in Proceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services (2017)
3.
E. Ohn-Bar, M.M. Trivedi, Looking at humans in the age of self-driving and highly automated vehicles.IEEE Trans. Intell. Vehic. 1, 90–104 (2016)
4.
Metadata
Title
Smart Low-Speed Self-Driving Transportation System
Authors
Zhenghong Wang
Bowu Zhang
Copyright Year
2021
Book
Advances in Software Engineering, Education, and e-Learning

Print ISBN: 978-3-030-70872-6

Electronic ISBN: 978-3-030-70873-3

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-70873-3_68