Table 2. AI applications supporting... | Emerald Publishing

Table 2.

AI applications supporting transportation resilience

AI technique	Transportation application	Resilience function	Resilience capacity supported
Machine learning	Traffic flow prediction	Early disruption identification	Absorptive capacity
Anomaly detection	Infrastructure monitoring	Failure and incident detection	Absorptive capacity
Reinforcement learning	Dynamic routing	Adaptive network reconfiguration	Adaptive capacity
Demand forecasting	Freight and capacity planning	Resource optimization	Adaptive capacity
Digital twins	Scenario simulation	Evaluation of response alternatives	Recovery capacity
Predictive analytics	Infrastructure risk forecasting	Anticipatory decision-making	Absorptive and adaptive capacity
AI-based learning systems	Postdisruption analysis	Continuous improvement	Recovery capacity

AI technique	Transportation application	Resilience function	Resilience capacity supported
Machine learning	Traffic flow prediction	Early disruption identification	Absorptive capacity
Anomaly detection	Infrastructure monitoring	Failure and incident detection	Absorptive capacity
Reinforcement learning	Dynamic routing	Adaptive network reconfiguration	Adaptive capacity
Demand forecasting	Freight and capacity planning	Resource optimization	Adaptive capacity
Digital twins	Scenario simulation	Evaluation of response alternatives	Recovery capacity
Predictive analytics	Infrastructure risk forecasting	Anticipatory decision-making	Absorptive and adaptive capacity
AI-based learning systems	Postdisruption analysis	Continuous improvement	Recovery capacity

Source(s): Author’s synthesis based on transportation resilience and intelligent transportation systems literature