In order to solve the problem of safety caused by multi-party data sharing in autonomous driving simulation testing， a blockchain-based model for data notarization of autonomous driving simulation testing was proposed to ensure secure storage and traceability of the data， thereby providing reliable support for auditing work. Firstly， the semi-public characteristics of consortium blockchain were utilized to ensure that on-chain data were only visible to authorized organizations， while a permission verification mechanism based on RBAC （Role-Based Access Control） model was employed to implement access control for these organizations. Secondly， a smart contract template was defined to standardize the data access process， and process extension points were open to support customized functions， for example， allowing extension of associated smart contracts to ensure automatic execution of simulation resource trading activities. Finally， optimization strategies， including on-chain and off-chain hybrid storage of InterPlanetary File System （IPFS）， data batch processing， and resource data caching， were proposed to address limitations of blockchain storage resources and processing capabilities. Tests were conducted to evaluate the efficiency of data notarization for 500 data simulation scenarios generated by large language models. Experimental results show that compared to the direct access method， the notarization process applying batch processing strategy reduces the total transaction number by 72.00%， decreasing the performance consumption caused by smart contract calls significantly， and has the average time for writing and reading all data reduced by 85.36% and 52.67%， respectively. It can be seen that the proposed model provides reliable technical support for the data security of multi-party data sharing in autonomous driving simulation testing， while the proposed optimization strategies improve the data memory access efficiency significantly.