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:自主驾驶技术是促进智能交通的至关重要的技术,其中车辆自动化发挥着重要作用。为了加速其发展,汽车工程师学会(SAE)将自动化规范为不同的SAE级别,并成功推动了研究和产品以提高道路安全性、效率和便利性。同时,高级驾驶员辅助系统(ADAS)和自动驾驶系统(ADS)广泛发展以支持车辆自动化,并在自动化技术方面取得成功。然而,安全风险始终是开发者和用户关注的问题,并阻碍了自主驾驶车辆的部署。虽然自动驾驶汽车人员受伤风险的研究正在进行和广泛展开,但目前有限的研究比较了ADAS和ADS,特别是从系统的角度来看。我们全面进行了这项比较研究。与现有作品不同的是,我们首先整合多源数据,以确保分析结果更可靠。接下来,我们采用随机参数多项式logit模型进行描述性统计和统计推断,以分析调查因素和观察到的碰撞数据之间的交互作用。此外,我们比较了SAE L2-5不同自动化级别下的碰撞严重程度,以进一步揭示不同因素之间的交互作用。根据分析结果,我们发现不同因素影响了ADS和ADAS之间的伤害严重程度。来自ADAS的碰撞与驾驶员类型、路面、被撞物体和影响区域更相关,ADS碰撞与道路类型、事故前运动、影响区域和车辆状况更相关。我们的研究结果提供了对当前ADS和ADAS安全结果的见解,有助于利益相关者更好地探索自主驾驶汽车的安全性以加速自主驾驶汽车的部署。