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Tesla.c
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#include "PMLL.h"
#include <cuda_runtime.h> // Use CUDA for Tesla Dojo acceleration
// Persistent Neural Memory for Tesla FSD
typedef struct {
int iteration_count;
double last_steering_correction; // Memory for last correction
double last_brake_intensity; // Memory for last braking action
char last_scene_data[512]; // Stores last encountered driving scenario
} TeslaMemoryState;
// Global Neural Cache (Dojo-Optimized)
TeslaMemoryState TeslaState;
// Multithreading for Sensor Fusion
void* sensor_fusion_thread(void* arg) {
while (1) {
// Fetch real-time Tesla sensor data
fetch_camera_data();
fetch_radar_data();
fetch_lidar_data();
// Process input for novel situations
process_novel_driving_scenarios();
}
}
// Initialize Tesla’s Neural Memory State
void initialize_tesla_memory(TeslaMemoryState *state) {
if (!load_state(state)) {
state->iteration_count = 0;
state->last_steering_correction = 0.0;
state->last_brake_intensity = 0.0;
strcpy(state->last_scene_data, "");
log_event("Tesla Neural Memory Initialized.");
} else {
log_event("Resumed Tesla Memory from Persistent Storage.");
}
}
// Persistent Autonomous Logic Loop (Tesla FSD AI)
void tesla_logic_loop(TeslaMemoryState *state) {
pthread_t sensor_thread;
pthread_create(&sensor_thread, NULL, sensor_fusion_thread, NULL);
while (1) {
TeslaSensorData input = get_real_time_sensor_data();
if (NovelTopic(input.scene_description, state)) {
NovelInput(input.scene_description, state);
}
// Process reinforcement learning corrections
state->iteration_count++;
state->last_steering_correction = input.steering_angle * 1.02;
state->last_brake_intensity = input.brake_force * 1.1;
char log_msg[512];
snprintf(log_msg, sizeof(log_msg),
"Iteration: %d, Steering Correction: %f, Brake Intensity: %f, Scene: %s",
state->iteration_count, state->last_steering_correction,
state->last_brake_intensity, state->last_scene_data);
log_event(log_msg);
save_state(state); // Persist learned corrections
usleep(5000); // 5ms delay to match Tesla FSD refresh rate
}
}