Many urban joggers find their runs disrupted by traffic lights, forcing them to stop unpredictably and breaking their rhythm. This not only lowers the quality of their workout but can also be discouraging. While some try to time their runs to avoid red lights, this is often impossible without precise information about traffic light patterns. No existing tools help runners sync their pace with traffic signals to minimize stops, leaving a gap in the running experience.

A Personalized Pace Assistant for Urban Runners

One way to address this could be through a mobile app that helps joggers adjust their speed to match traffic light timings along their route. The app would let users input or select a running path, then access traffic light data (either pre-recorded or real-time) for that area. It could then calculate the ideal pace to minimize stops—for example, suggesting when to speed up slightly to catch a green light or slow down to avoid a red. The app might provide gentle audio or visual cues to guide the runner without being intrusive.

Over time, the app could learn a user’s typical pace and preferences to offer more tailored suggestions. The goal wouldn’t be to force runners into rigid pacing but to help them flow with the city’s natural rhythms. Early versions might focus on fixed-interval traffic lights or select high-traffic routes before expanding.

Why Runners and Cities Might Embrace It

Regular urban joggers—especially those who frequently encounter traffic crossings—would benefit most, but the concept could also extend to cyclists or walkers. City transportation departments might support the idea if it leads to smoother pedestrian flow or fewer risky crossings. Potential monetization could come from:

• A freemium model with advanced features like offline maps or multi-city support.
• Partnerships with running brands or local tourism boards.
• Anonymized data insights for urban planners studying foot traffic patterns.

How It Compares to Existing Tools

Unlike apps like Strava or Citymapper, which focus on route tracking or general navigation, this idea is specifically designed to help runners harmonize with traffic signals. While tools like Waze offer real-time traffic updates for drivers, none address the niche need of optimizing a runner’s pace around stoplights. The key innovation is turning a frustration (unpredictable stops) into a solvable problem through timing synchronization.

An MVP could start with basic functionality for a single city, using manually collected light timing data, then expand as partnerships and user feedback refine the concept.