Cities are under pressure to move smarter, faster, and more sustainably, and artificial intelligence (AI) is stepping up to meet that demand. From traffic flow predictions to adaptive infrastructure planning, tools like machine learning (ML) and generative AI (GenAI) are changing how transportation systems operate at every level.
Federal agencies are taking notice. In its 2024 AI Assurance whitepaper, the U.S. Department of Transportation (USDOT) identified AI and highly automated systems as national priorities.
At Omnisight, we help cities modernize their transportation management systems with AI solutions. Discover how these tools improve visibility, response, and planning—and how our Fusion Sensor helps make implementation easier and more future-ready.
Benefits of AI in Transportation Management
Traffic, delays, and safety risks continue to challenge city transportation teams. Emerging technologies in transportation—especially AI—offer new ways to manage these issues. With better data and faster analysis, cities can act sooner, adjust more effectively, and get more out of the systems they already have.
Here are just a few of the benefits of AI technologies and examples of real-world applications in modern transportation systems:
- Fewer traffic jams. AI-powered sensors use adaptive signal timing (AST) to adjust traffic lights in real time, easing congestion. For example, the AI-powered traffic lights at many Pittsburgh intersections reduced travel times by 25% and cut idling by over 40%. They demonstrate how AI can deliver fast, measurable improvements in traffic flow.
- Accurate tracking of people and vehicles. Sensors with radar and AI-enabled video can detect cars, bikes, and pedestrians. Urban planners use this data to identify problem areas, like high-risk crossings or bottlenecks, before they become bigger issues.
- Faster congestion and accident detection. When traffic slows or stops unexpectedly, AI tools detect the change and notify the right teams. That means quicker response times for first responders and better planning for long-term congestion relief.
- More efficient parking management. With AI-connected cameras and sensors in parking lots, transportation departments can guide drivers to open spaces, flag parking violations, and monitor for safety concerns—all without adding new staff.
- Detailed data collection. AI and machine learning (ML) tools help cities collect traffic data over time, revealing patterns that lead to better sustainable transportation management planning. This supports safer, more efficient, and more accessible streets across neighborhoods.
AI also supports transportation equity—helping planners identify underserved areas that lack safe pedestrian crossings, reliable transit options, or efficient traffic flow. This enables smarter, more inclusive infrastructure investments.
Challenges and Considerations of AI Transportation Technologies
When correctly implemented, artificial intelligence can benefit city transportation management authorities. However, they also introduce new technical, regulatory, and ethical risks for cities to manage:
- Data privacy. AI-powered transportation systems rely on continuous data from cameras, sensors, and connected vehicles. Local agencies must ensure every component complies with local and federal privacy laws. In California, for example, Assembly Bill 1008 now classifies AI-processed data as personal information, adding new layers of responsibility for public agencies.
- Implementation costs. Upgrading to AI-driven systems often means replacing or retrofitting existing infrastructure, which can be expensive. Smaller municipalities or those with limited funding may need to scale projects gradually or seek outside funding.
The USDOT's Strengthening Mobility and Revolutionizing Transportation (SMART) Grant Program supports local projects that use advanced technologies, such as AI, to improve transportation efficiency and safety. - Maintenance and reliability. AI systems aren’t set-and-forget. They need regular software updates, calibration, and support to stay accurate. Missed maintenance can lead to false alerts or system downtime, impacting the reliability of day-to-day traffic operations.
How Omnisight’s Fusion Sensor Supports Modernization Plans
The Fusion Sensor is Omnisight’s all-in-one traffic sensor. It is built to help cities, towns, and rural areas adopt AI-powered traffic management without overhauling their existing infrastructure or stretching their budgets.
- Multiple sensors in one. The Fusion Sensor uses data fusion to combine HD video, HD3D radar, and artificial intelligence in a single compact device. Instead of investing in multiple separate sensor systems, you can use the Fusion Sensor to monitor traffic jams, count people, protect work zones, or collect vehicle information data.
- Easy to connect. Fusion Sensor installs quickly and integrates with existing networks to minimize downtime. It supports both wired Ethernet and wireless communication (Wi-Fi, Bluetooth, or LTE), so teams can get it running without overhauling cables or investing in proprietary systems.
- Onboard data processing. With onboard TrueEdge processing, the sensor analyzes radar, video, and other inputs directly on the device—no external servers needed. It delivers actionable updates up to 20 times per second, helping first responders and traffic teams act faster while lowering infrastructure overhead.
- Low power consumption. Each unit runs on less than 30 watts, making it a strong fit for solar installations or renewable energy plans. Municipal teams working toward net-zero goals can incorporate the Fusion Sensor without straining their power infrastructure.
Create Safer and Better Managed Roads With Omnisight
Traffic safety doesn’t have to come at the cost of time, budget, or complexity. The Fusion Sensor gives cities and towns a practical way to improve road management.
Schedule a consultation with Omnisight to see how the Fusion Sensor fits into your plans. We’ll help you find a solution that supports your goals and works with what you already have.
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