Adaptive Signal Control and AI-Driven Analytics at New Jersey’s Arterial Management Center Reduced Corridor Travel Delays by 10 to 30 Percent.
NJDOT deployed a centralized arterial management platform integrating SCATS adaptive signal control, multimodal data fusion, and AI/ML forecasting to optimize statewide traffic operations.
NJ, United States
Enhancing Traffic Operations through Real-Time, Data-Driven Strategies at NJDOT’s Arterial Management Center (AMC)
Summary Information
NJDOT established an Arterial Management Center (AMC) to address chronic congestion, fluctuating traffic patterns, and fragmented signal coordination. Operated with consultant support, AMC integrated real-time traffic information feeds (RITIS, 511NJ, SPATEL) with SCATS adaptive traffic signal control. Advanced analytics, microsimulation (VISSIM), and optimization tools (Synchro) were applied for predictive and proactive traffic management.
METHODOLOGY
Before-and-after corridor level analyses were conducted using VISSIM microsimulation and Synchro optimization. Real-time AI/ML forecasting models were trained on multimodal datasets (SPATEL, RITIS, SCATS). Performance audits were conducted using rigorous QA/QC protocols, and econometric modeling of user delay to estimate cost savings and return on investment (ROI).
FINDINGS
- Post-implementation analyses revealed travel delay reductions of 10 to 30 percent across targeted corridors.
- Cost-benefit analysis estimated a positive ROI through delay cost savings and optimized infrastructure investment that minimized unplanned maintenance activities and O&M costs.
