Resilience in transportation networks and connected autonomous vehicles: a PRISMA-ScR scoping review

Engineering notes

The study found that CAVs significantly improve the Robustness and Redundancy by maintaining a constant flow of traffic and creating alternative routes during disruptions.

Chinese explanation / 中文解读

中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。

Original abstract

Abstract Connected Autonomous Vehicles (CAVs) are changing transportation networks and introducing new ways to strengthen and adapt to disruptive events. This systematic scoping review uses PRISMA-ScR to examine how CAVs affect transportation network resilience, focusing on four key attributes of resilience: Robustness, Redundancy, Resourcefulness, and Rapidity (“4Rs”). The review analyzes 106 peer-reviewed articles published between 2014 and 2025. Quantitative synthesis of the “4Rs” centered framework reveals a significant research imbalance: Robustness ( n = 106) and Resourcefulness ( n = 102) are the most extensively documented attributes, followed by Redundancy ( n = 83), while Rapidity ( n = 31) remains the least explored. The review identifies Traffic Congestion (34.91%), Cyber Disruptions (14.15%), and Communication Failures (12.26%) as the primary disruptive events quantified in the literature. The study found that CAVs significantly improve the Robustness and Redundancy by maintaining a constant flow of traffic and creating alternative routes during disruptions. Likewise, Resourcefulness is benefited due to the ability of CAVs to collect information in real time, allowing for effective resource allocation and decision-making during system recovery, while Rapidity remains the least explored attribute, particularly in the post-disruption phase. Furthermore, the empirical basis distribution is predominantly simulation/analytical studies (71 out of 106), while purely empirical studies remain limited (13/106), and pilot/field/FOT evidence is scarce (4/106). Overall, the study highlights the main factors to be taken into account in the implementation of CAVs.

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