Safety-Critical Data and Autonomous Vehicles: Barriers to Sharing
Autonomous vehicles (AVs) have the potential to transform transportation by greatly improving road safety. However, to ensure their safety and efficacy, it is crucial to have access to safety-critical data, such as crash and near-crash records. Sharing this data among AV companies, academic researchers, regulators, and the public can contribute to the overall improvement of AV design and development.
Despite the benefits of sharing safety-critical data, AV companies have been reluctant to do so. A recent study conducted interviews with twelve employees from AV companies to explore the reasons behind this reluctance and identify potential barriers to data sharing.
Barriers to Data Sharing
The study revealed two key barriers that were previously unknown. The first barrier is the inherent nature of the datasets themselves. Safety-critical data contains knowledge that is essential for improving AV safety, and the process of collecting, analyzing, and sharing this data is resource-intensive. Even within a single company, sharing such data can be complicated due to the politics involved. Different teams within a company may have competing interests and priorities, leading to reluctance in sharing data internally.
The second barrier identified by the study is the perception of AV safety knowledge as private rather than public. Interviewees believed that the knowledge gained from safety-critical data gives their companies a competitive edge. They view it as proprietary information that should be guarded to maintain their advantage in the market. This perception hinders the sharing of safety-critical data for the greater social good.
Implications and Way Forward
The findings of this study have important implications for promoting safety-critical AV data sharing. To overcome the barriers identified, several strategies can be considered.
- Debating and Stratifying Public and Private Knowledge: It is essential to initiate discussions and debates within the AV industry and regulatory bodies regarding the classification of safety knowledge as public or private. By defining clear boundaries, companies can feel more secure in sharing data without compromising their competitive advantages.
- Innovating Data Tools and Sharing Pipelines: Developing new tools and technologies that streamline the process of sharing safety-critical data can alleviate resource constraints and minimize the politics associated with data sharing. Companies could collaborate to create standardized data formats and sharing pipelines to facilitate easier and more efficient exchange of information.
- Offsetting Costs and Incentivizing Sharing: Given the resource-intensive nature of collecting safety-critical data, it is crucial to find ways to offset the costs associated with data curation. Incentives, such as tax breaks or grants, could be provided to companies that actively participate in data sharing initiatives. This would encourage greater participation and promote a culture of collaboration in the AV industry.
In conclusion, the barriers to sharing safety-critical data in the autonomous vehicle industry are rooted in the complexities of data collection, internal politics, and the perception of knowledge as a competitive advantage. Addressing these barriers requires industry-wide discussions, technological innovations, and the provision of incentives to encourage data sharing. By overcoming these obstacles, the AV industry can collectively work towards improving AV safety and realizing the full potential of autonomous vehicles.