TrafficSimulation

Ever wonder why the PIE crawls even when there’s no accident? We usually blame "phantom jams", but the truth is, the phantom is often us. Between the right-lane hoggers and the kan-cheong weavers, our tiny individual habits create massive ripples for everyone. By making the connection between personal behavior and collective outcomes more visible to road users, TrafficSimulator hopes to highlight how changing driver behavior could reduce congestion without expensive infrastructure changes.

I built an interactive web simulation that identifies your driving profile through a 5-question quiz, then visualizes how your habits affect real traffic flow. Users can adjust the percentage of drivers like them on a simulated road and watch congestion patterns emerge in real-time. The tool features profile-specific car animations, an educational tutorial system, and dynamic traffic modeling that shows cause-and-effect immediately. Key limitations: currently demonstrates highway scenarios only; city intersections and mixed traffic not yet modeled.

I used the traffic-simulation-de JavaScript traffic simulation model (open-source code) from movsim/traffic-simulation-de on GitHub to generate and visualize traffic flows in our project. This simulator provides interactive traffic scenario simulations and is available under the GPL-3.0 license.

The simulation is now publicly accessible and ready for user testing. The goal is to measure whether seeing personalized traffic impacts creates "aha moments" that shift driver self-awareness. Key metrics to track: time spent experimenting with different driver mix ratios, whether users complete the full simulation, and any qualitative feedback on behavioral insights gained. The visual, gamified approach aims to make abstract traffic theory immediately tangible and personally relevant.