Urban traffic bottlenecks cause recurring congestion impacting freight logistics, retail success, and city infrastructure. Efficient, scientific identification of these bottlenecks is critical for targeted interventions. Ticon’s advanced platforms, TrafficZoom and TrafficScope, offer data at high resolution (35-foot segments, 5-minute intervals) covering over 95% of roadways to enable objective, automated bottleneck identification, congestion visualization, and ranking of street and intersection performance.

Studies show that broad traffic demand reductions only moderately reduce delays; real improvements come from optimized local traffic management such as signal optimization. For instance, signal timing adjustments increased free-flow speeds by up to 25% under less dense conditions.

Ticon’s methodology combines diverse data sources—detector, GPS, connected vehicles—and uses advanced modeling validated across nine U.S. states with less than 10% error in traffic volume estimates, outperforming traditional counting methods.

These analytics help municipalities decide between control optimizations and roadway expansions, fine-tune ITS deployments, and prioritize interventions based on measurable impacts. Evidence reveals that up to 50% travel delay reductions are achievable through signal optimization, but effectiveness varies by segment, underscoring the need for granular data.

Urban planners and commercial operators alike benefit from precise bottleneck identification to maximize investment returns and improve corridor flow at lower costs than full expansions. Moving from reactive fixes to proactive, data-driven network optimization is key to improving congestion, safety, and economic vitality in cities.