Next-Gen Pedestrian Safety: How AI is Revolutionizing Urban Mobility and Protection

AI and geospatial data are transforming pedestrian safety with real-time insights, predictive analytics, and equity-first planning.

In today’s rapidly urbanizing world, pedestrian safety has become a growing concern for city leaders, planners, and communities alike. The simple act of walking—once considered the most basic, risk-free mode of transportation—is now fraught with hazards. From distracted driving to outdated infrastructure, cities are struggling to protect their most vulnerable road users.

Yet, while traditional approaches often rely on outdated data or static infrastructure, the future of pedestrian safety is taking a different turn—one powered by Artificial Intelligence (AI).

AI is no longer limited to autonomous vehicles or traffic light optimization. It's reshaping how we understand, monitor, and proactively manage pedestrian movement in urban environments. With real-time data, predictive modeling, and geospatial intelligence, public leaders now have the tools to make walking in cities not just safer—but smarter.

‍

The Urgent Need to Rethink Pedestrian Safety

Recent statistics paint a grim picture. In the U.S., over 7,500 pedestrians were killed in traffic-related incidents in 2022—the highest number in four decades, according to the Governors Highway Safety Association. That’s a 77% increase since 2010.

Why the surge?

• A sharp rise in SUV use, which poses a higher fatality risk to pedestrians
• Distracted driving and walking—phones in hand, heads down
• Inadequate lighting and infrastructure, especially in lower-income neighborhoods
• A lack of real-time situational awareness for city planners and transportation departments

‍

Most cities still rely on crash reports and reactive measures. But what if we could identify risks before someone gets hurt? That’s where AI comes in.

Why Traditional Solutions Are Falling Short

For decades, cities have leaned on the same toolbox:

• Speed humps
• Warning signs
• Zebra crossings
• Flashing beacons

‍

While helpful, these are reactive solutions—deployed after incidents occur or complaints are made. They don’t adapt to time of day, crowd dynamics, or traffic fluctuations. And they don’t generate data to inform better long-term planning.

To truly improve pedestrian safety, cities need real-time visibility, dynamic decision-making, and forward-looking analysis.

How AI Is Reimagining Pedestrian Protection

Artificial Intelligence is no longer just a futuristic buzzword—it's actively transforming how we protect pedestrians in cities today. From identifying near-misses to forecasting future risks, AI helps public leaders move beyond reactive approaches and take proactive, data-informed action.

At Urban SDK, we're helping cities implement AI technologies that provide real-time visibility, pattern recognition, and actionable insights—designed specifically to reduce injuries, improve walkability, and support equitable urban planning.

Here’s a closer look at four powerful ways AI is reshaping pedestrian safety:

Computer Vision for Real-Time Pedestrian Detection

AI-powered camera systems are transforming traditional intersections into intelligent, adaptive pedestrian environments. These systems do much more than just watch—they interpret, predict, and respond to real-time activity.

Our computer vision modules can:

• Detect pedestrians as they approach or enter crosswalks
• Differentiate between individuals, families, cyclists, children, or seniors
• Recognize vulnerable users like people in wheelchairs or using strollers
• Estimate crowd size and direction of movement
• Trigger dynamic responses—such as extending crossing signals, dimming vehicle headlights, or alerting autonomous vehicles

‍

Why it matters:

These adaptive signals give cities a tool to prioritize pedestrian movement over vehicle flow in critical areas—like school zones, stadiums, or downtown crossings—especially during peak hours or poor visibility conditions.

It’s a big step toward responsive infrastructure that prioritizes human safety.

Near-Miss Detection for Identifying Hidden Risks

Traditional safety reports rely on crash data. But for every reported incident, there may be dozens of "near misses"—dangerous interactions where pedestrians are almost hit but no formal record exists.

Our AI-based systems can analyze:

• Sudden hard braking near crosswalks
• Vehicles turning too quickly into pedestrian pathways
• Drivers running yellow or red lights
• Close encounters with jaywalkers or distracted walkers
• Repeated violations in specific zones (e.g., speeding past stop signs)

‍

Using traffic camera footage or connected sensor data, we can detect and quantify these incidents, surfacing invisible patterns that help local agencies take preventative action.

The result:

Cities can identify unsafe intersections before someone gets hurt—empowering data-driven decisions for design changes, signage updates, or enforcement campaigns.

Predictive Analytics for Risk Forecasting

Urban safety shouldn’t be reactive—it should be strategic. That’s why we use AI-powered predictive models to help cities forecast pedestrian risk zones based on dynamic, multi-layered data sets.

Our platform can combine:

• Historical crash data
• Time-of-day and day-of-week traffic volume
• Pedestrian density trends
• Road design factors
• Seasonal weather impacts
• Special event overlays

This allows cities to:

• Prioritize upgrades in corridors with rising risk
• Adjust signal timing during peak pedestrian hours
• Plan safe walking routes for schoolchildren or commuters
• Justify grant applications with predictive insights

Predictive analytics shifts safety planning from guesswork to foresight—and allows for smarter capital allocation and stronger public trust.

Geospatial AI and Walkability Intelligence

Most cities measure walkability by checking a box—are there sidewalks and lights? But with geospatial AI, we go far beyond that.

Our tools allow cities to:

• Map pedestrian flows in real time—across neighborhoods, event venues, school zones, and downtown corridors
• Identify infrastructure gaps such as missing curb ramps, unsafe crosswalks, or sidewalk discontinuities
• Overlay foot traffic data with land use, population density, equity scores, and public transit access
• Score each neighborhood using customized walkability and safety indices

By visualizing this data spatially, cities can uncover hidden safety gaps and invest in inclusive, equity-forward infrastructure improvements.

This matters especially for underserved communities, where infrastructure often lags behind and where walkability is a critical factor in daily life.

Real-World Applications: AI in Action

These forward-thinking programs around the globe demonstrate how AI is already reshaping pedestrian safety—and provide inspiration for cities ready to take the next step.

Peachtree Corners, Georgia – LiDAR-Enhanced Safety

Peachtree Corners is leading by example with a fully operational smart city infrastructure lab—testing LiDAR-powered systems that detect pedestrian and vehicle movement in 3D. These sensors feed real-time analytics into their traffic management systems, helping to identify conflict points and dynamically adapt intersection behavior.

This initiative gives public officials granular insights into how pedestrians and vehicles interact, making it easier to redesign crossings, adjust signal phasing, and reduce crashes.

Las Vegas, Nevada – Adaptive Crosswalk Signals

In Las Vegas, smart crosswalks are now equipped with AI-powered sensors that detect waiting pedestrians and adjust traffic signal timing based on real-time demand. This adaptive timing approach reduces pedestrian wait times—especially in low-visibility conditions—and improves crosswalk compliance among drivers.

The pilot has shown increased pedestrian satisfaction and smoother vehicle flow, demonstrating how even small infrastructure upgrades powered by AI can yield major safety improvements.

Pittsburgh, Pennsylvania – AI Simulations for Safer Streets

Researchers at Carnegie Mellon University are using large language models (LLMs) to simulate Pittsburgh’s road networks and pedestrian zones. The simulations are designed to highlight risk areas—like intersections prone to speeding or unsafe turning behavior—and test how changes in signage, signal timing, or design would reduce crashes.

This cutting-edge use of generative AI helps city leaders pre-test street design ideas virtually, saving time, budget, and resources while enhancing community safety.

South Korea – AI Smart Crosswalks

In South Korea, cities have deployed next-gen crosswalks embedded with thermal cameras, radar sensors, and responsive LED lighting. These systems detect pedestrian movement—even in rain, fog, or darkness—and automatically trigger warning lights for both walkers and drivers.

The initiative has led to a significant reduction in vehicle speed near crosswalks and fewer collisions in pilot areas. It’s a powerful example of how multi-sensor fusion and AI algorithms can create intelligent, adaptive safety zones.

Urban SDK Case Studies – Data-Driven Safety Solutions

We’ve partnered with cities and transportation agencies across the U.S. to help them improve pedestrian safety, streamline operations, and make data-driven decisions with confidence. Here are a few examples of how our platform is delivering real results:

City of Chesapeake, VA – Streamlining Speeding Complaint Responses

Chesapeake faced challenges with frequent speeding complaints and needed accurate speed data to make informed decisions. By integrating Urban SDK's platform, the city was able to:​

• Monitor average speeds on roadways
• Determine the need for traffic calming measures
• Quickly respond to public inquiries with accurate data​

Urban SDK enabled Chesapeake officials to clear 250 traffic complaints in the first 8 months of the partnership, saving the staff innumerable hours and taxpayers thousands of dollars.

Beyond that, it enhanced transparency, trust, and satisfaction among residents.

City of Fort Pierce, FL – Enhancing Traffic Management and Public Engagement

Fort Pierce aimed to improve traffic flow, secure funding, and engage with the public effectively. Utilizing Urban SDK's advanced data analytics, the city achieved:​

• Efficient management of traffic flow
• Successful grant applications for infrastructure projects
• Improved communication with residents regarding roadway issues​

The collaboration transformed Fort Pierce's approach to traffic management and road safety.

Florida Department of Transportation (FDOT) – Automating Incident Management

FDOT's District 2 sought a better way to track roadway incidents and understand clearance times. Partnering with Urban SDK, they:​

• Automated performance measures and analysis
• Standardized performance reporting
• Streamlined statewide data visualization​

This initiative provided FDOT with a holistic view of roadways, enabling quicker responses to citizen concerns.​

What Cities Can Do with Urban SDK

We offer public leaders and transportation agencies the tools they need to make smarter, safer decisions for pedestrians and all road users. Our platform helps cities:

• Monitor real-time pedestrian flows across key corridors
• Use custom dashboards to track high-risk intersections and corridor performance
• Visualize before-and-after data to evaluate infrastructure improvements
• Create presentation-ready charts for city council, public meetings, or grant proposals
• Set up alerts for speeding in school zones and walk-heavy districts

Instead of relying on outdated traffic counts or infrequent surveys, our platform delivers live, actionable insights—enabling smarter pedestrian safety decisions, every day.

The Benefits of AI-Driven Pedestrian Safety

By integrating AI and geospatial analytics into mobility infrastructure, cities can:

• Decrease pedestrian injuries and fatalities
• Prioritize upgrades in the areas that need them most
• Monitor vulnerable populations and promote equitable access
• Build public trust with transparent data-backed actions
• Support Vision Zero policies with measurable impact

Smart pedestrian safety isn’t just about modernizing systems—it’s a responsibility to protect lives. And with the right data, cities don’t have to wait for a problem to take action.

Key Challenges to Address

Data Privacy

Monitoring public spaces must be handled with care. Facial recognition and behavioral tracking raise concerns. Solutions should:

• Use anonymized data
• Communicate clearly with residents
• Follow strict ethical and legal guidelines

Implementation Costs

Installing AI infrastructure—such as cameras, sensors, and cloud-based analytics—can involve upfront costs that may challenge some municipal budgets. However, cities have several options to offset these expenses:

• Apply for federal transportation safety grants
• Leverage regional partnerships and public-private collaborations
• Start with pilot programs using our scalable, modular platform—purpose-built at Urban SDK to help cities move quickly, gather insights, and expand with confidence

Equity Gaps

AI has the power to solve inequality—but only if data is used responsibly. Urban SDK’s geospatial layers help ensure that underserved areas are not left behind in safety planning.

What Public Leaders Should Do Next

Ask Yourself:

• Are we relying too much on crash reports?
• Do we know where near-misses are occurring?
• Are we addressing risk before someone gets hurt?

Action Steps:

• Use AI-powered platforms to map foot traffic and risk in real time
• Pilot smart crosswalk or sensor-based solutions in high-traffic zones
• Integrate safety data into city council presentations, grant proposals, and infrastructure planning

Lead with Insights, Act with Data

Pedestrian safety can no longer rely on static signs or outdated assumptions. Today’s cities demand dynamic, responsive solutions powered by real-time data and predictive intelligence.

At Urban SDK, we’re helping public leaders move beyond reaction—toward anticipation, prevention, and smarter decision-making. Our platform delivers the insights you need to design safer, more equitable streets from day one.

Because the future of mobility isn’t just about moving faster.It’s about moving smarter—and safer for everyone.