improved biogeme trip choice model

matsim-scenarios · Jul 21, 2024 · 7d4f2c2 · 7d4f2c2
1 parent bfb7397
commit 7d4f2c2
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Showing 2 changed files with 21 additions and 11 deletions.
diff --git a/src/main/java/org/matsim/prepare/choices/ComputeTripChoices.java b/src/main/java/org/matsim/prepare/choices/ComputeTripChoices.java
@@ -233,15 +233,15 @@ private List<Object> computeAlternatives(TripRouter router, Network network, Per
 				}
 			}
 
+			if (!PersonUtils.canUseCar(person) && mode.equals(TransportMode.car)) {
+				valid = false;
+			}
+
 			// Filter rows that have been chosen, but would not be valid
 			if (choice.equals(mode) && !valid) {
 				return null;
 			}
 
-			if (!PersonUtils.canUseCar(person) && mode.equals(TransportMode.car)) {
-				valid = false;
-			}
-
 			row.addAll(List.of(travelDistance / 1000, travelTime / 3600, walkDistance / 1000, valid));
 		}
 

diff --git a/src/main/python/choicemodels/estimate_biogeme_trip_choice.py b/src/main/python/choicemodels/estimate_biogeme_trip_choice.py
@@ -7,7 +7,7 @@
 import biogeme.biogeme as bio
 import biogeme.database as db
 import biogeme.models as models
-from biogeme.expressions import Beta
+from biogeme.expressions import Beta, bioDraws, PanelLikelihoodTrajectory, log, MonteCarlo
 
 from prepare import read_trip_choices
 
@@ -17,29 +17,33 @@
 if __name__ == "__main__":
     parser = argparse.ArgumentParser(description="Estimate the trip choice model")
     parser.add_argument("--input", help="Path to the input file", type=str, default="../../../../trip-choices.csv")
+    parser.add_argument("--mxl-modes", help="Modes to use mixed logit for", nargs="+", type=set,
+                        default=["pt", "bike", "ride"])
     parser.add_argument("--est-performing", help="Estimate the beta for performing", action="store_true")
     parser.add_argument("--no-income", help="Don't consider the income", action="store_true")
 
     args = parser.parse_args()
 
     ds = read_trip_choices(args.input)
 
-    df = ds.df.drop(columns=["person"])
-
     # Convert all the columns to numeric
-    df = df * 1
+    df = ds.df * 1
 
     database = db.Database("data/choices", df)
     v = database.variables
 
-    database.remove(v["choice"] == 0)
+    database.panel("person")
 
     km_costs = defaultdict(lambda: 0.0, car=-0.149, ride=-0.149)
 
     ASC = {}
     for mode in ds.modes:
         # Base asc
-        ASC[mode] = Beta(f"ASC_{mode}", 0, None, None, 1 if mode == "walk" else 0)
+        ASC[mode] = Beta(f"ASC_{mode}", 0, None, None, FIXED if mode == "walk" else ESTIMATE)
+
+        if mode in args.mxl_modes:
+            sd = Beta(f"ASC_{mode}_s", 1, 0, None, ESTIMATE)
+            ASC[mode] += sd * bioDraws(f"{mode}_RND", "NORMAL_ANTI")
 
     U = {}
     AV = {}
@@ -57,7 +61,13 @@
         U[i] = u
         AV[i] = v[f"{mode}_valid"]
 
-    logprob = models.loglogit(U, AV, v["choice"])
+    if not args.mxl_modes:
+        logprob = models.loglogit(U, AV, v["choice"])
+
+    else:
+        obsprob = models.logit(U, AV, v["choice"])
+        condprobIndiv = PanelLikelihoodTrajectory(obsprob)
+        logprob = log(MonteCarlo(condprobIndiv))
 
     biogeme = bio.BIOGEME(database, logprob)