A Test Scenario Automatic Generation Strategy for Intelligent Driving Systems

Joint Authors

Gao, Feng
He, Yingdong
Wang, Zilong
Duan, Jianli

Source

Mathematical Problems in Engineering

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-10, 10 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-01-15

Country of Publication

Egypt

No. of Pages

10

Main Subjects

Civil Engineering

Abstract EN

In this paper, a methodology of automatic generation of test scenarios for intelligent driving systems is proposed, which is based on the combination of the test matrix (TM) and combinatorial testing (CT) methods together.

With a hierarchical model of influence factors, an evaluation index for scenario complexity is designed.

Then an improved CT algorithm is proposed to make a balance between test efficiency, condition coverage, and scenario complexity.

This method can ensure the required combinational coverage and at the same time increase the overall complexity of generated scenarios, which is not considered by CT.

Furthermore, the way to find the best compromise between efficiency and complexity and the bound of scenario number has been analyzed theoretically.

To validate the effectiveness, it has been applied in the hardware-in-the-loop (HIL) test of a lane departure warning system (LDW).

The results show that the proposed method can ensure required coverage with a significantly improved scenario complexity, and the generated test scenario can find system defects more efficiently.

American Psychological Association (APA)

Gao, Feng& Duan, Jianli& He, Yingdong& Wang, Zilong. 2019. A Test Scenario Automatic Generation Strategy for Intelligent Driving Systems. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1195259

Modern Language Association (MLA)

Gao, Feng…[et al.]. A Test Scenario Automatic Generation Strategy for Intelligent Driving Systems. Mathematical Problems in Engineering No. 2019 (2019), pp.1-10.
https://search.emarefa.net/detail/BIM-1195259

American Medical Association (AMA)

Gao, Feng& Duan, Jianli& He, Yingdong& Wang, Zilong. A Test Scenario Automatic Generation Strategy for Intelligent Driving Systems. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-10.
https://search.emarefa.net/detail/BIM-1195259

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1195259