Can the impacts of connected and automated vehicles be predicted?

A huge research effort is going on in order to develop connected and automated vehicles. Small-scale trials of automated vehicles in real traffic are already taking place. Can the societal impacts of a transition to fully connected and automated vehicles be predicted? This question has been studied in the Horizon2020 project Levitate. To predict the impacts of connected and automated vehicles, one must first identify and describe potential impacts. A list of 33 potential impacts, classified as direct, systemic and wider was developed. A survey was made of methods that can be applied in order to quantify and predict these impacts. Not all potential impacts can be predicted with any confidence. There is, first of all, large uncertainty about when and how long the transition to connected and automated vehicles will be. It is also impossible to predict some potentially quite important impacts, e.g. whether the transition to automation will be associated with a transition to various forms of shared mobility or whether individual ownership and use of vehicles will continue at present levels. Another important aspect which is difficult to predict is whether automated vehicles will continue to have internal combustion engines or be electric or based on fuel cells. Several methods must be applied to predict the impacts of connected and automated vehicles. As far as impacts on traffic operations are concerned, various forms of traffic simulation have been widely applied. Broadly speaking, connected and automated vehicles are expected to lead to increased road capacity, fewer accidents and less emissions. Increased road capacity may in turn generate induced travel demand, which to some extent will fill up the new capacity. Road safety is likely to be improved, but there is large uncertainty about how non-automated road users and automated vehicles can interact in ways that maintain current safety levels or, preferably, improve safety.

当前正开展海量研究工作，以推进联网自动驾驶汽车（connected and automated vehicles）的研发。目前已在真实交通场景中开展自动驾驶汽车的小规模实车测试。向完全联网自动驾驶汽车转型所带来的社会影响能否被精准预测？这一问题已在欧盟地平线2020（Horizon2020）计划‘Levitate’项目中得到研究。若要预测联网自动驾驶汽车的各类影响，首先需识别并系统梳理其潜在影响维度。研究团队最终梳理出33项潜在影响，并将其划分为直接影响、系统性影响与泛社会影响三类。同时，研究人员调研了可用于量化与预测此类影响的各类技术方法。但并非所有潜在影响都能被可靠预测。首先，联网自动驾驶汽车转型的启动时点与持续周期均存在极大不确定性。此外，部分极具战略重要性的潜在影响亦无法被精准预判，例如：自动驾驶转型是否会催生各类共享出行模式的普及，抑或是车辆的个人保有量与使用频率能否维持当前水平。另一难以预判的关键维度是：自动驾驶汽车未来是否仍搭载内燃机，抑或是采用电力驱动、燃料电池技术。针对联网自动驾驶汽车的影响预测，需综合运用多种技术方法。就交通运行层面的影响而言，各类交通仿真技术已得到广泛应用。总体而言，联网自动驾驶汽车有望提升道路通行能力、减少交通事故发生率并降低尾气排放。但道路通行能力的提升可能会诱增出行需求，进而在一定程度上填补新增的通行空间。道路交通安全或可得到改善，但非自动驾驶道路使用者与自动驾驶汽车的交互方式能否维持乃至优化当前的安全水平，仍存在极大不确定性。