Autonomous driving tends to be an imperative technology to facilitate smart transportation, where vehicular automation plays a prominent role. To accelerate its development, the Society of Automotive Engineers (SAE) regularized the automation to different SAE levels and successfully promoted the research and products to improve road safety, efficiency, and convenience. Meanwhile, advanced driver assistance systems (ADAS) and automated driving systems (ADS) are widely developed to support vehicular automation and achieve success in automation technology. However, safety risks always concern the developers and users and hinder the deployment of autonomous vehicles. Although the studies on the injury risk from autonomous vehicles are ongoing and extensive, limited current research compares ADAS and ADS, especially from a systematic perspective. We conduct this comparison study comprehensively. Different from existing works, we first incorporate multi-source data to ensure higher reliability of analysis results. Next, we conduct both descriptive statistics and statistical inference with random parameters multinomial logit model to analyze the interaction between investigated factors and observed crash data. Moreover, we compare the crash severity across different automation levels SAE L2-5 to further reveal the interaction between different factors. Given the analysis results, we find that different factors impact the injury severity between ADS and ADAS. The crashes from ADAS are more correlated to driver type, surface,object collided with, and the impact area. The ADS crashes are more associated with road type, pre-crash movement, impact area, and vehicle conditions. Our findings provide the insights into safety outcomes of current ADS and ADAS, which helps stakeholders better explore automated vehicle safety for accelerating the deployment of autonomous vehicles.

翻译：自动驾驶技术正成为推动智能交通发展的关键手段，其中车辆自动化扮演着核心角色。为加速其发展，美国汽车工程师学会（SAE）将自动化水平划分为不同等级，并成功推动了相关研究与产品以提升道路安全、效率与便捷性。与此同时，高级驾驶辅助系统（ADAS）与自动驾驶系统（ADS）被广泛开发以支持车辆自动化，并在自动化技术领域取得了成功。然而，安全风险始终是开发者与用户关注的焦点，并阻碍了自动驾驶汽车的部署。尽管关于自动驾驶车辆碰撞伤害风险的研究广泛且持续，但目前从系统视角比较ADAS与ADS的研究仍十分有限。本研究对此进行了全面的比较分析。与现有研究不同，我们首先整合多源数据以确保分析结果具有更高的可靠性。其次，采用随机参数多项Logit模型进行描述性统计与统计推断，以探究研究因素与观测碰撞数据之间的相互作用。此外，我们比较了SAE L2-5不同自动化等级下的碰撞严重性，以进一步揭示不同因素间的交互作用。基于分析结果发现，ADAS与ADS的伤害严重性受不同因素影响。ADAS相关碰撞更多与驾驶员类型、路面状况、碰撞物体及碰撞区域相关；而ADS相关碰撞则更多与道路类型、碰撞前运动状态、碰撞区域及车辆状况相关。本研究为当前ADS与ADAS的安全性能提供了见解，有助于利益相关者更好地探索自动驾驶汽车安全性，从而加速其部署进程。