Decisions in Highly Automated Vehicles for Passing Urban Intersections with Support Vector Machines Automotive Research and Testing Center

Format:

Conference/Event

Author/Creator:

Xu, Xu, author.

Contributor:

Wang, Weijen

Conference Name:

WCX World Congress Experience (2018-04-10 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 2018

Summary:

AbstractIntersections and road junctions are with higher traffic accidents due to the wrong decisions of human drivers. In this paper, we consider an artificial intelligence method to mimic decisions of human drivers for highly automated vehicles at passing an urban intersection. We applied the Principal Component Analysis and uniformly scaling for the Support Vector Machine learning is applied to model time series features. The effect due to misspecification by ignoring time series issue is investigated through the comparison of predicted action accurate rate is investigated by a simulation study on the software PreScan

Notes:

Vendor supplied data

Publisher Number:

2018-01-0037

Access Restriction:

Restricted for use by site license