新增加自定义流量文件评估仿真效果

envs/edge_vsl_env.py

@@ -127,6 +127,7 @@ class SUMOEdgeVSLEnvironment:
         )
         self.controlled_length_km = corridor_assets.controlled_length_m / 1000.0
         self.default_edge_speeds = self._build_default_segment_speeds()
+        self.max_segment_speeds = self.default_edge_speeds.copy()
 
         self.action_dims = [self.num_speed_actions] * self.num_edges
         self.features_per_edge = 3
@@ -345,14 +346,22 @@ class SUMOEdgeVSLEnvironment:
         self._close_sumo()
 
     def _decode_action(self, action: np.ndarray) -> np.ndarray:
-        return np.array([self.speed_actions_ms[int(a)] for a in action])
+        requested_speeds = np.array([self.speed_actions_ms[int(a)] for a in action], dtype=float)
+        return np.minimum(requested_speeds, self.max_segment_speeds)
 
     def _apply_vsl(self, edge_speeds: np.ndarray):
         for idx, segment_id in enumerate(self.control_edges):
             if idx in self.passive_segment_indices:
                 continue
             for edge_id in self.segment_edge_map.get(segment_id, []):
-                traci.edge.setMaxSpeed(edge_id, float(edge_speeds[idx]))
+                edge_info = self.parser.edge_info.get(edge_id)
+                original_edge_speed = (
+                    float(edge_info.speed_limit)
+                    if edge_info is not None
+                    else float(edge_speeds[idx])
+                )
+                safe_speed = min(float(edge_speeds[idx]), original_edge_speed)
+                traci.edge.setMaxSpeed(edge_id, safe_speed)
 
     def _get_edge_detector_data(self) -> Tuple[List[float], List[float], List[int], List[float]]:
         speeds, occs, counts, valid_speeds = [], [], [], []

scripts/evaluate_models.py

@@ -110,6 +110,12 @@ def parse_args():
         default=None,
         help="Override SUMO simulation step length for evaluation only. Default: use training config.",
     )
+    parser.add_argument(
+        "--route-file",
+        type=str,
+        default=None,
+        help="Override SUMO route/flow file for evaluation only. Supports absolute paths or project-relative paths.",
+    )
     return parser.parse_args()
 
 
@@ -221,6 +227,14 @@ def deep_merge_dicts(base: dict, override: dict) -> dict:
     return merged
 
 
+def resolve_project_path(path_str: Optional[str]) -> Optional[str]:
+    if not path_str:
+        return None
+    if os.path.isabs(path_str):
+        return path_str
+    return os.path.abspath(os.path.join(PROJECT_ROOT, path_str))
+
+
 def resolve_model_load_path(model_name: str, checkpoint_dir: str) -> str:
     if model_name in {"ppo", "gpro", "appo", "mappo", "tcamappo", "dcmappo", "dqn"}:
         best_path = os.path.join(checkpoint_dir, "model_best.pt")
@@ -482,6 +496,7 @@ def evaluate_single_model(
     end_time: int,
     with_gui: bool,
     step_length: Optional[float],
+    route_file: Optional[str],
 ) -> Tuple[pd.DataFrame, pd.DataFrame, dict]:
     config = load_config_for_checkpoint(checkpoint_dir, fallback_config_path) if checkpoint_dir else load_config_for_checkpoint("", fallback_config_path)
     runtime_config = copy.deepcopy(config)
@@ -497,6 +512,8 @@ def evaluate_single_model(
     runtime_config["sumo"]["gui"] = with_gui
     if step_length is not None:
         runtime_config["sumo"]["step_length"] = step_length
+    if route_file is not None:
+        runtime_config["sumo"]["route_file"] = route_file
     runtime_config.setdefault("runtime", {})["output_dir"] = os.path.join(output_dir, model_name)
     runtime_config["runtime"]["metrics_subdir"] = "eval_sumo_metrics"
     runtime_config["runtime"]["collect_detector_cells"] = True
@@ -631,11 +648,12 @@ def evaluate_single_model(
         "end_time": effective_end_time,
         "with_gui": with_gui,
         "step_length": runtime_config["sumo"].get("step_length"),
+        "route_file": runtime_config["sumo"].get("route_file", ""),
     }
     return step_df, edge_df, detector_df, meta
 
 
-def evaluate_worker(task: Tuple[str, Optional[str], str, str, int, Optional[int], Optional[int], bool, Optional[float]]):
+def evaluate_worker(task: Tuple[str, Optional[str], str, str, int, Optional[int], Optional[int], bool, Optional[float], Optional[str]]):
     return evaluate_single_model(*task)
 
 
@@ -873,6 +891,9 @@ def print_summary(summary_df: pd.DataFrame, output_dir: str):
 
 def main():
     args = parse_args()
+    route_file = resolve_project_path(args.route_file)
+    if route_file is not None and not os.path.isfile(route_file):
+        raise FileNotFoundError(f"Custom route file not found: {route_file}")
     checkpoint_root = resolve_checkpoint_root(args.checkpoint_root)
     model_dirs = discover_model_dirs(checkpoint_root, args.models)
     if not model_dirs:
@@ -904,6 +925,7 @@ def main():
                 args.end_time,
                 args.with_gui,
                 args.step_length,
+                route_file,
             )
         )
 
@@ -922,6 +944,7 @@ def main():
             args.end_time,
             args.with_gui,
             args.step_length,
+            route_file,
         ),
     )