AI event reveals its impact on transportation infrastructure, safety and operations

AI event reveals its impact on transportation infrastructure, safety and operations

Traffic safety professionals, engineers, public agency officials and industry innovators gathered at Harrisburg University of Science & Technology for the inaugural Artificial Intelligence (AI) in Transportation Conference, a one-day event focused on how artificial intelligence is reshaping the way the industry plans, manages and maintains transportation systems.

The takeaway was clear: AI technologies are already improving roadway safety, asset condition monitoring and incident response, and the tools are market ready.

Here are five key innovations discussed at the June event in Pennsylvania.

• Incident prediction and proactive traffic management: AI models forecast traffic congestion before they happen. This foresight enables agencies to deploy detours, adjust signal timing and manage lane closures before breakdowns, reducing the chances of secondary crashes.

• Dashcam integration for crash and work zone verification: AI-enhanced analysis of roadway footage supports real-time confirmation of crash scenes, work zones and road work activity. These tools improve situational awareness, assist with post-incident review and help with documentation for planning and operations.

• Design audits for compliance and safety reviews: AI is automating design checks for compliance with department of transportation (DOT) design standards and specifications.

• AI-driven safety analysis and road feature evaluation: Machine vision and 3D LiDAR are being used to assess stopping sight distances and identify where additional safety interventions—like guardrails—are most needed.

• Infrastructure inspection using crowdsourced data and emerging technologies: AI is transforming infrastructure assessment by leveraging crowdsourced roadway data alongside emerging technologies such as aerial imagery, sensors and drones. These tools enable agencies to conduct efficient inspections of pavement, striping, signage and guardrails—especially in hard-to-access locations—while improving asset condition tracking and maintenance planning.

While automation is accelerating processes, summit speakers emphasized that human expertise remains central. Successful deployment requires structured workflows, staff training and multidisciplinary collaboration across engineers, policymakers and field crews.

For those interested in real-world applications, ATSSA’s recently released AI case study, “Driving Transportation Safety Forward with AI,” provides field-tested examples of how AI is improving safety and streamlining decision-making across transportation networks.

— ATSSA Innovation & Technical Services Manager Nagham Matout El-Zine