# Advanced Sensor Integration and AI Architectures for Next-Generation Traffic Navigation
## 2 Materials and Methods
### The Traffic Optimization Algorithm  
TOA is designed to calculate the \(GRQl_{k}\) by integrating multiple data sources. This procedure ensures users receive the most optimal and safe routes based on the analyzed parameters.  
The TOA uses the following procedure depicted in Figure 4:  
* Users initiate the route optimization process by specifying their desired destinations through latitude and longitude coordinates. These waypoints define the journey's start, end, and intermediate stops. The reported waypoints are stored in the system for subsequent processing and route calculation;
* The TOA constructs API requests using the user-specified waypoints, ensuring that the requests include parameters for real-time traffic data and a maximum of three alternative routes. TomTom's Routing API responds with detailed information for each alternative route, including \(TDl_{k}\), \(ET_{k}\), \(TDe_{k}\), and a sequence of geographical points defining the route path;
* For each alternative route, the TOA calculates the proximity of recorded incidents by determining if any reported coordinates fall within a 50-m radius of the route's geographical points. Incidents within this proximity are factored into the \(RSa_{k}\) and \(RSe_{k}\) parameters. The higher the number of proximate incidents, the lower the contribution of \(RSa_{k}\) and \(RSe_{k}\) to the overall \(GRQl_{k}\) score;  
Figure 3: Custom-designed assembly for event recording using ESP32-CAM and MPU-6050.  
* The SOA integrates the five key parameters (\(T\)\(D\)\(I\)\({}_{k}\), \(ET\)\({}_{k}\), \(T\)\(D\)\({}_{k}\), \(R\)\(S\)\({}_{k}\), and \(R\)\(S\)\({}_{k}\)) using the \(GRQ\)\(I\)\({}_{k}\) formula. Equation (1) normalizes the combined parameters to produce a \(GRQ\)\(I\)\({}_{k}\) score ranging from 1 (poorest quality) to 100 (optimal quality), enabling users to compare and select the best route;
* The system presents the alternative routes on an interactive map within the application's graphical user interface (GUI), highlighting areas with high incident densities. Each route is accompanied by its respective \(GRQ\)\(I\)\({}_{k}\) score and detailed metrics. Users compare the routes based on these metrics and select the most suitable option for their journey.  
In Figure 4, the parameter k represents the index of alternative routes generated by the TomTom Routing API. These routes are ranked in ascending order of estimated travel time, with lower values of k corresponding to shorter time routes, while higher values indicate progressively longer paths. The TOA evaluated four route alternatives. Practical and computational considerations drive the decision to limit the analysis to four. Users typically prefer routes with shorter travel times, as these are more practical and align with their preferences. Including routes beyond four would introduce alternatives with  
Figure 4: Logical schema of the TOA for calculating the \(GRQ\)\(I\)\({}_{k}\).  
significantly longer durations, which are unlikely to be chosen and may unnecessarily increase computational effort.  
The TOA employs a multifaceted approach to compute the \(GRQI_{k}\), integrating user inputs, real-time sensor data, advanced image analysis, and route metrics.