Name
Title | ||
|---|---|---|
Risk Assessment of Highly Automated Vehicles with Naturalistic Driving Data: A Surrogate-based optimization Method |
Abstract | ||
|---|---|---|
One essential goal for Highly Automated Vehicles (HAVs) safety test is to assess their risk rate in naturalistic driving environment, and to compare their performance with human drivers. The probability of exposure to risk events is generally low, making the test process extremely time-consuming. To address this, we proposed a surrogate-based method in scenario-based simulation test to expediate the assessment of the risk rate of HAVs. HighD data were used to fit the naturalistic distribution and to estimate the probability of each concrete scenario. Machine learning model-based surrogates were proposed to quickly approximate the test result of each concrete scenario. Considering the different capabilities and domains of various surrogate models, we applied six surrogate models to search for two types of targeted scenarios with different risk levels and rarity levels. We proved that the performances of different surrogate models greatly distinguish from each other when the target scenarios are extremely rare. Inverse Distance Weighted (IDW) was the most efficient surrogate model, which could achieve risk rate assessment with only 2.5% test resources. The required CPU runtime of IDW was 2% of that required by Kriging. The proposed method has great potential in accelerating the risk assessment of HAVs. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/IV51971.2022.9827015 | 2022 IEEE Intelligent Vehicles Symposium (IV) |
Keywords | DocType | ISSN |
highly automated vehicles,naturalistic driving data,safety test,naturalistic driving environment,scenario-based simulation test,HAVs,HighD data,concrete scenario,machine learning model-based surrogates,risk rate assessment,test resources,surrogate-based optimization method,inverse distance weighted,IDW | Conference | 1931-0587 |
ISBN | Citations | PageRank |
978-1-6654-8822-8 | 0 | 0.34 |
References | Authors | |
7 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| He Zhang | 1 | 0 | 0.68 |
| Huajun Zhou | 2 | 0 | 0.34 |
| Jian Sun | 3 | 60 | 14.76 |
| Ye Tian | 4 | 6 | 2.88 |