diff --git a/activitysim/abm/models/trip_destination.py b/activitysim/abm/models/trip_destination.py
index 853cfc35e..407d50844 100644
--- a/activitysim/abm/models/trip_destination.py
+++ b/activitysim/abm/models/trip_destination.py
@@ -30,12 +30,12 @@
 )
 from activitysim.core.configuration.base import PreprocessorSettings
 from activitysim.core.configuration.logit import LocationComponentSettings
+from activitysim.core.exceptions import DuplicateWorkflowTableError, InvalidTravelError
 from activitysim.core.interaction_sample import interaction_sample
 from activitysim.core.interaction_sample_simulate import interaction_sample_simulate
 from activitysim.core.skim_dictionary import DataFrameMatrix
 from activitysim.core.tracing import print_elapsed_time
 from activitysim.core.util import assign_in_place, reindex
-from activitysim.core.exceptions import InvalidTravelError, DuplicateWorkflowTableError
 
 logger = logging.getLogger(__name__)
 
@@ -273,12 +273,16 @@ def destination_sample(
     return choices
 
 
-def aggregate_size_term_matrix(maz_size_term_matrix, network_los):
+def aggregate_size_term_matrix(maz_size_term_matrix, network_los, all_tazs=None):
     df = maz_size_term_matrix.df
     assert ALT_DEST_TAZ not in df
 
     dest_taz = network_los.map_maz_to_taz(df.index)
     taz_size_term_matrix = df.groupby(dest_taz).sum()
+    if all_tazs is not None:
+        taz_size_term_matrix = taz_size_term_matrix.reindex(
+            all_tazs, fill_value=0
+        ).rename_axis(taz_size_term_matrix.index.name, axis=0)
 
     taz_size_term_matrix = DataFrameMatrix(taz_size_term_matrix)
 
@@ -612,7 +616,16 @@ def destination_presample(
 
     alt_dest_col_name = model_settings.ALT_DEST_COL_NAME
 
-    TAZ_size_term_matrix = aggregate_size_term_matrix(size_term_matrix, network_los)
+    if state.settings.sharrow:
+        # when using sharrow, we use the skim_dataset structure, and need to ensure
+        # that all TAZs are represented in the size_term_matrix, even those with no MAZs
+        all_tazs = state.get_dataframe("land_use_taz").index
+    else:
+        all_tazs = None
+
+    TAZ_size_term_matrix = aggregate_size_term_matrix(
+        size_term_matrix, network_los, all_tazs
+    )
 
     TRIP_ORIGIN = model_settings.TRIP_ORIGIN
     PRIMARY_DEST = model_settings.PRIMARY_DEST
@@ -627,6 +640,17 @@ def destination_presample(
         network_los.map_maz_to_taz(alternatives.index)
     ).sum()
 
+    # We now have aggregated alternatives indexed by TAZ instead of MAZ.
+    # For sharrow, we need the TAZ indexing to be "complete", i.e. include all TAZ ids,
+    # even those that had no MAZs (and so were missing from the aggregation result).
+    # this is needed because we are going to taking the entire set of TAZ alternatives
+    # as a vector which will need to align with the TAZ skims.
+    if state.settings.sharrow:
+        all_tazs = state.get_dataframe("land_use_taz").index
+        alternatives = alternatives.reindex(all_tazs, fill_value=0).rename_axis(
+            alternatives.index.name, axis=0
+        )
+
     # # i did this but after changing alt_dest_col_name to 'trip_dest' it
     # # shouldn't be needed anymore
     # alternatives.index.name = ALT_DEST_TAZ
@@ -1520,13 +1544,13 @@ def run_trip_destination(
                             """
 
                         When using the trip destination model with sharrow, it is necessary
-                        to set a value for `purpose_index_num` in the trip destination 
-                        annotate trips preprocessor.  This allows for an optimized compiled 
+                        to set a value for `purpose_index_num` in the trip destination
+                        annotate trips preprocessor.  This allows for an optimized compiled
                         lookup of the size term from the array of size terms.  The value of
-                        `purpose_index_num` should be the integer column position in the size 
-                        matrix, with usual zero-based numpy indexing semantics (i.e. the first 
+                        `purpose_index_num` should be the integer column position in the size
+                        matrix, with usual zero-based numpy indexing semantics (i.e. the first
                         column is zero).  The preprocessor expression most likely needs to be
-                        "size_terms.get_cols(df.purpose)" unless some unusual transform of 
+                        "size_terms.get_cols(df.purpose)" unless some unusual transform of
                         size terms has been employed.
 
                         """
diff --git a/activitysim/abm/test/trip_dest/configs/_dummy_coefficients.csv b/activitysim/abm/test/trip_dest/configs/_dummy_coefficients.csv
new file mode 100644
index 000000000..9d471534a
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/_dummy_coefficients.csv
@@ -0,0 +1,2 @@
+coefficient_name,value,constrain
+coef_one,1,T
diff --git a/activitysim/abm/test/trip_dest/configs/constants.yaml b/activitysim/abm/test/trip_dest/configs/constants.yaml
new file mode 100644
index 000000000..b093206ab
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/constants.yaml
@@ -0,0 +1,3 @@
+max_walk_distance: 3
+walkSpeed: 3.00
+walkThresh: 1.50
diff --git a/activitysim/abm/test/trip_dest/configs/destination_choice_size_terms.csv b/activitysim/abm/test/trip_dest/configs/destination_choice_size_terms.csv
new file mode 100644
index 000000000..5d0b192b8
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/destination_choice_size_terms.csv
@@ -0,0 +1,24 @@
+segment,model_selector,Acres,Population
+work_low,workplace,0,0.602938343
+work_med,workplace,0,0.487310988
+work_high,workplace,0,0.359519129
+work_veryhigh,workplace,0,0.169128839
+university,school,1,0
+preschool,school,0.07552,1
+gradeschool,school,1,0
+highschool,school,1,0
+escort,non_mandatory,0.465,0.144
+shopping,non_mandatory,1,0
+eatout,non_mandatory,0.4,0.6
+othmaint,non_mandatory,0,0.518
+social,non_mandatory,0.2,0.478
+othdiscr,non_mandatory,0.252252252,0.272272272
+atwork,atwork,0,0.258
+work,trip,0.2,0.166666667
+escort,trip,0.655,0.144
+shopping,trip,0.86,0
+eatout,trip,0.2,1
+othmaint,trip,0.001,0.518
+social,trip,0.3,0.478
+othdiscr,trip,0.252252252,0.272272272
+univ,trip,0.999001,0
\ No newline at end of file
diff --git a/activitysim/abm/test/trip_dest/configs/network_los.yaml b/activitysim/abm/test/trip_dest/configs/network_los.yaml
new file mode 100644
index 000000000..fdc77dc2f
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/network_los.yaml
@@ -0,0 +1,14 @@
+read_skim_cache: False
+write_skim_cache: False
+zone_system: 2
+taz_skims: 
+  omx: min*.omx
+maz: maz.csv
+maz_to_maz:
+  tables:
+   - maz_to_maz_walk.csv
+skim_time_periods:
+    time_window: 1440
+    period_minutes: 60
+    periods: [0, 5, 9, 15, 18, 20, 24]
+    labels: ['EA', 'AM', 'MD', 'PM', 'EV', 'EA']
diff --git a/activitysim/abm/test/trip_dest/configs/settings.yaml b/activitysim/abm/test/trip_dest/configs/settings.yaml
new file mode 100644
index 000000000..6cd0132bd
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/settings.yaml
@@ -0,0 +1,56 @@
+sharrow: test
+recode_pipeline_columns: true
+
+expression_profile: False
+households_sample_size: 0
+sharrow_cache_dir: sharrow_cache
+chunk_training_mode: explicit
+check_for_variability: False
+use_shadow_pricing: False
+want_dest_choice_sample_tables: False
+trace_hh_id: 
+cleanup_trace_files_on_resume: True
+
+input_table_list:
+  - tablename: households
+    filename: households.csv
+    index_col: household_id
+    rename_columns:
+      MAZ: home_zone_id
+      hhno: household_id
+    recode_columns:
+      home_zone_id: land_use.zone_id
+    keep_columns:
+      - home_zone_id
+      - income
+  - tablename: persons
+    filename: persons.csv
+    index_col: person_id
+    rename_columns:
+      PERID: person_id
+    keep_columns:
+      - household_id
+      - age
+      - PNUM
+  - tablename: land_use # MAZ,TAZ,Acres,Population
+    filename: land_use.csv
+    index_col: zone_id
+    rename_columns:
+      MAZ: zone_id
+    recode_columns:
+      zone_id: zero-based
+      TAZ: land_use_taz.TAZ
+    keep_columns:
+      - TAZ
+      - Acres
+      - Population
+  - tablename: land_use_taz
+    filename: taz.csv
+    index_col: TAZ
+    recode_columns:
+      TAZ: zero-based
+
+resume_after:
+
+models:
+  - trip_destination
diff --git a/activitysim/abm/test/trip_dest/configs/trip_destination.csv b/activitysim/abm/test/trip_dest/configs/trip_destination.csv
new file mode 100644
index 000000000..fcd8b48df
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/trip_destination.csv
@@ -0,0 +1,10 @@
+Description,Expression,work,univ,school,escort,shopping,eatout,othmaint,social,othdiscr,atwork
+size term,"@np.log1p(size_terms.get(df.alt_dest, df.purpose)) # sharrow: np.log1p(size_terms['sizearray'])",1,1,1,1,1,1,1,1,1,1
+no attractions,"@size_terms.get(df.alt_dest, df.purpose) == 0 # sharrow: size_terms['sizearray'] == 0",-999,-999,-999,-999,-999,-999,-999,-999,-999,-999
+stop proximity to home (outbound),@df.outbound * od_skims['distwalk'],-0.3800,0,0,0,0,0,0,0,0,0
+stop proximity to home (inbound),@~df.outbound * dp_skims['distwalk'],-0.1500,0,0,0,0,0,0,0,0,0
+stop proximity to main destination (outbound),@df.outbound * dp_skims['distwalk'],-0.26,,,,,,,,,
+"Sample of alternatives correction factor","@np.minimum(np.log(df.pick_count/df.prob), 60)",1,1,1,1,1,1,1,1,1,1
+Mode choice logsum from origin to stop,od_logsum,1.821,1.821,1.821,1.821,1.821,1.821,1.821,1.821,1.821,1.821
+Mode choice logsum from stop to destination,dp_logsum,1.821,1.821,1.821,1.821,1.821,1.821,1.821,1.821,1.821,1.821
+meaty,@odt_skims['meat'],-0.01,-0.01,-0.01,-0.01,-0.01,-0.01,-0.01,-0.01,-0.01,-0.01
diff --git a/activitysim/abm/test/trip_dest/configs/trip_destination.yaml b/activitysim/abm/test/trip_dest/configs/trip_destination.yaml
new file mode 100644
index 000000000..a4a2c418e
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/trip_destination.yaml
@@ -0,0 +1,35 @@
+SAMPLE_SIZE: 30
+
+DESTINATION_SAMPLE_SPEC: trip_destination_sample.csv
+DESTINATION_SPEC: trip_destination.csv
+COEFFICIENTS: _dummy_coefficients.csv
+
+LOGSUM_SETTINGS: trip_mode_choice.yaml
+
+# optional (comment out if not desired)
+DEST_CHOICE_LOGSUM_COLUMN_NAME: destination_logsum
+
+# comment out DEST_CHOICE_LOGSUM_COLUMN_NAME if saved alt logsum table
+DEST_CHOICE_SAMPLE_TABLE_NAME: trip_destination_sample
+
+# model-specific logsum-related settings
+TRIP_ORIGIN: origin
+ALT_DEST_COL_NAME: alt_dest
+PRIMARY_DEST: destination
+
+REDUNDANT_TOURS_MERGED_CHOOSER_COLUMNS:
+  - tour_mode
+
+preprocessor:
+  SPEC: trip_destination_annotate_trips_preprocessor
+  DF: trips
+  TABLES:
+    - tours
+    - persons
+
+# drop failed trips and cleanup failed trip leg_mates for consistency
+# (i.e. adjust trip_count, trip_num, first for missing failed trips)
+CLEANUP: False
+
+# this setting is used by testing code to force failed trip_destination
+# fail_some_trips_for_testing: False
diff --git a/activitysim/abm/test/trip_dest/configs/trip_destination_annotate_trips_preprocessor.csv b/activitysim/abm/test/trip_dest/configs/trip_destination_annotate_trips_preprocessor.csv
new file mode 100644
index 000000000..157ae07b4
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/trip_destination_annotate_trips_preprocessor.csv
@@ -0,0 +1,9 @@
+Description,Target,Expression
+,tour_mode,"reindex(tours.tour_mode, df.tour_id)"
+,_tod,"np.where(df.outbound,reindex_i(tours.start, df.tour_id),reindex_i(tours.end, df.tour_id))"
+,trip_period,network_los.skim_time_period_label(_tod)
+,is_joint,"reindex(tours.tour_category, df.tour_id)=='joint'"
+,purpose_index_num,"size_terms.get_cols(df.purpose)"
+,tour_mode_is_walk,"reindex(tours.tour_mode, df.tour_id)=='WALK'"
+,tour_mode_is_bike,"reindex(tours.tour_mode, df.tour_id)=='BIKE'"
+,tour_leg_dest,"np.where(df.outbound,reindex(tours.destination, df.tour_id), reindex(tours.origin, df.tour_id)).astype(int)"
diff --git a/activitysim/abm/test/trip_dest/configs/trip_destination_sample.csv b/activitysim/abm/test/trip_dest/configs/trip_destination_sample.csv
new file mode 100644
index 000000000..549e5e2da
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/trip_destination_sample.csv
@@ -0,0 +1,8 @@
+Description,Expression,work,univ,school,escort,shopping,eatout,othmaint,social,othdiscr,atwork
+,_od_DIST@od_skims['distwalk'],1,1,1,1,1,1,1,1,1,1
+,_dp_DIST@dp_skims['distwalk'],1,1,1,1,1,1,1,1,1,1
+size term,"@np.log1p(size_terms.get(df.alt_dest, df.purpose)) # sharrow: np.log1p(size_terms['sizearray'])",1,1,1,1,1,1,1,1,1,1
+no attractions,"@size_terms.get(df.alt_dest, df.purpose) == 0 # sharrow: size_terms['sizearray'] == 0",-999,-999,-999,-999,-999,-999,-999,-999,-999,-999
+stop proximity to home (outbound),@df.outbound * _od_DIST,-0.3800,0,0,0,0,0,0,0,0,0
+stop proximity to home (inbound),@~df.outbound * _od_DIST,-0.1500,0,0,0,0,0,0,0,0,0
+stop proximity to main destination (outbound),@df.outbound * _dp_DIST,-0.26,,,,,,,,,
diff --git a/activitysim/abm/test/trip_dest/configs/trip_mode_choice.csv b/activitysim/abm/test/trip_dest/configs/trip_mode_choice.csv
new file mode 100644
index 000000000..947247bba
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/trip_mode_choice.csv
@@ -0,0 +1,6 @@
+Label,Description,Expression,DRIVEALONEFREE,SHAREDRIDE,WALK
+#,Drive alone ,,,,
+util_DRIVEALONEFREE_Unavailable_for_persons_less_than_16,DRIVEALONEFREE - Unavailable for persons less than 16,age < 16,-999,,
+util_DRIVEALONEFREE_Person_is_between_16_and_19_years_old,DRIVEALONEFREE - Person is between 16 and 19 years old,@(df.age >= 16) & (df.age <= 19),coef_age1619_da,,
+util_SHARED2FREE_In_vehicle_time,SHARED2FREE - In-vehicle time,@odt_skims['meat'],,coef_ivt,
+util_WALK_Time_short,WALK - Time up to 1.5 miles,@od_skims['distwalk'],,,coef_walktime_short
diff --git a/activitysim/abm/test/trip_dest/configs/trip_mode_choice.yaml b/activitysim/abm/test/trip_dest/configs/trip_mode_choice.yaml
new file mode 100644
index 000000000..557e0dd82
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/trip_mode_choice.yaml
@@ -0,0 +1,52 @@
+# trip_mode_choice.yaml
+
+compute_settings:
+  fastmath: false  # use of isnan in utility functions requires fastmath=False
+
+SPEC: trip_mode_choice.csv
+COEFFICIENTS: trip_mode_choice_coefficients.csv
+COEFFICIENT_TEMPLATE: trip_mode_choice_coefficients_template.csv
+
+LOGIT_TYPE: NL
+
+NESTS:
+  name: root
+  coefficient: coef_nest_root
+  alternatives:
+      - name: AUTO
+        coefficient: coef_nest_AUTO
+        alternatives:
+          - DRIVEALONEFREE
+          - SHAREDRIDE
+      - name: NONMOTORIZED
+        coefficient: coef_nest_NONMOTORIZED
+        alternatives:
+          - WALK
+
+CONSTANTS:
+  orig_col_name: origin
+  dest_col_name: destination
+  I_MODE_MAP:
+    DRIVEALONEFREE: 1
+    SHAREDRIDE: 2
+    WALK: 3
+  I_SOV_MODES: 1
+  I_AUTO_MODES: [1,2]
+  I_WALK_MODE: 3
+
+# so far, we can use the same spec as for non-joint tours
+preprocessor:
+  SPEC: trip_mode_choice_annotate_trips_preprocessor
+  DF: df
+  TABLES:
+    - land_use
+    - tours
+
+MODE_CHOICE_LOGSUM_COLUMN_NAME: mode_choice_logsum
+
+TOURS_MERGED_CHOOSER_COLUMNS:
+  - tour_category
+  - tour_mode
+  - start
+  - end
+  - age
diff --git a/activitysim/abm/test/trip_dest/configs/trip_mode_choice_annotate_trips_preprocessor.csv b/activitysim/abm/test/trip_dest/configs/trip_mode_choice_annotate_trips_preprocessor.csv
new file mode 100644
index 000000000..e0d2844e0
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/trip_mode_choice_annotate_trips_preprocessor.csv
@@ -0,0 +1,8 @@
+Description,Target,Expression
+,i_tour_mode,df.tour_mode.map(I_MODE_MAP)
+,tour_mode_is_SOV,i_tour_mode == I_SOV_MODES
+,tour_mode_is_auto,i_tour_mode.isin(I_AUTO_MODES)
+,tour_mode_is_walk,i_tour_mode == I_WALK_MODE
+,inbound,~df.outbound
+,first_trip,df.trip_num == 1
+,last_trip,df.trip_num == df.trip_count
\ No newline at end of file
diff --git a/activitysim/abm/test/trip_dest/configs/trip_mode_choice_coefficients.csv b/activitysim/abm/test/trip_dest/configs/trip_mode_choice_coefficients.csv
new file mode 100644
index 000000000..4618bf244
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/trip_mode_choice_coefficients.csv
@@ -0,0 +1,32 @@
+coefficient_name,value,constrain
+coef_one,1,T
+coef_zero,0,T
+coef_nest_root,1,T
+coef_nest_AUTO,0.72,T
+coef_nest_AUTO_DRIVEALONE,0.35,T
+coef_nest_AUTO_SHAREDRIDE2,0.35,T
+coef_nest_AUTO_SHAREDRIDE3,0.35,T
+coef_nest_NONMOTORIZED,0.72,T
+coef_nest_TRANSIT,0.72,T
+coef_nest_TRANSIT_WALKACCESS,0.5,T
+coef_nest_TRANSIT_DRIVEACCESS,0.5,T
+coef_nest_RIDEHAIL,0.36,T
+coef_nest_SCHOOL_BUS,0.5,T
+coef_ivt_disc,-0.03,F
+coef_ivt_maint,-0.034,F
+coef_ivt_school,-0.02,F
+coef_ivt_univ,-0.032,F
+coef_ivt_work,-0.01,F
+coef_ivt_atwork,-0.064,F
+coef_walktime_short_disc,-0.0558,F
+coef_walktime_short_maint,-0.0558,F
+coef_walktime_short_school,-0.0542,F
+coef_walktime_short_univ,-0.0542,F
+coef_walktime_short_work,-0.1,F
+coef_walktime_short_atwork,-0.0558,F
+coef_age1619_da_disc,0,F
+coef_age1619_da_maint,0,F
+coef_age1619_da_school,0,F
+coef_age1619_da_univ,0,F
+coef_age1619_da_work,0,F
+coef_age1619_da_atwork,0,F
diff --git a/activitysim/abm/test/trip_dest/configs/trip_mode_choice_coefficients_template.csv b/activitysim/abm/test/trip_dest/configs/trip_mode_choice_coefficients_template.csv
new file mode 100644
index 000000000..8e3f77d91
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/configs/trip_mode_choice_coefficients_template.csv
@@ -0,0 +1,17 @@
+coefficient_name,eatout,escort,othdiscr,othmaint,school,shopping,social,univ,work,atwork
+coef_one,,,,,,,,,,
+coef_nest_root,,,,,,,,,,
+coef_nest_AUTO,,,,,,,,,,
+coef_nest_AUTO_DRIVEALONE,,,,,,,,,,
+coef_nest_AUTO_SHAREDRIDE2,,,,,,,,,,
+coef_nest_AUTO_SHAREDRIDE3,,,,,,,,,,
+coef_nest_NONMOTORIZED,,,,,,,,,,
+coef_nest_TRANSIT,,,,,,,,,,
+coef_nest_TRANSIT_WALKACCESS,,,,,,,,,,
+coef_nest_TRANSIT_DRIVEACCESS,,,,,,,,,,
+coef_nest_RIDEHAIL,,,,,,,,,,
+coef_nest_SCHOOL_BUS,,,,,,,,,,
+#,,,,,,,,,,
+coef_ivt,coef_ivt_disc,coef_ivt_maint,coef_ivt_disc,coef_ivt_maint,coef_ivt_school,coef_ivt_maint,coef_ivt_disc,coef_ivt_univ,coef_ivt_work,coef_ivt_atwork
+coef_walktime_short,coef_walktime_short_disc,coef_walktime_short_maint,coef_walktime_short_disc,coef_walktime_short_maint,coef_walktime_short_school,coef_walktime_short_maint,coef_walktime_short_disc,coef_walktime_short_univ,coef_walktime_short_work,coef_walktime_short_atwork
+coef_age1619_da,coef_age1619_da_disc,coef_age1619_da_maint,coef_age1619_da_disc,coef_age1619_da_maint,coef_age1619_da_school,coef_age1619_da_maint,coef_age1619_da_disc,coef_age1619_da_univ,coef_age1619_da_work,coef_age1619_da_atwork
diff --git a/activitysim/abm/test/trip_dest/data/households.csv b/activitysim/abm/test/trip_dest/data/households.csv
new file mode 100644
index 000000000..068c894d5
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/data/households.csv
@@ -0,0 +1,11 @@
+income,hhno,MAZ
+83800,1,101
+83800,2,102
+54650,3,103
+54650,4,104
+54650,5,108
+80000,6,109
+40000,7,111
+65000,8,121
+45800,9,122
+9600,10,101
diff --git a/activitysim/abm/test/trip_dest/data/land_use.csv b/activitysim/abm/test/trip_dest/data/land_use.csv
new file mode 100644
index 000000000..329b64fb2
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/data/land_use.csv
@@ -0,0 +1,10 @@
+MAZ,TAZ,Acres,Population
+101,2,3.2,553
+102,2,2.6,9089
+103,3,0.4,14
+104,5,3.7,376
+108,11,6.6,884
+109,11,9.1,234
+111,11,1.1,67
+121,2,8.2,1
+122,3,45.6,0
diff --git a/activitysim/abm/test/trip_dest/data/maz.csv b/activitysim/abm/test/trip_dest/data/maz.csv
new file mode 100644
index 000000000..f24add676
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/data/maz.csv
@@ -0,0 +1,10 @@
+MAZ,TAZ
+101,2
+102,2
+103,3
+104,5
+108,11
+109,11
+111,11
+121,2
+122,3
diff --git a/activitysim/abm/test/trip_dest/data/maz_to_maz_walk.csv b/activitysim/abm/test/trip_dest/data/maz_to_maz_walk.csv
new file mode 100644
index 000000000..5bf0804b3
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/data/maz_to_maz_walk.csv
@@ -0,0 +1,15 @@
+OMAZ,DMAZ,distwalk
+101,101,0.078
+101,102,0.178
+101,103,0.098
+101,104,0.118
+101,108,0.348
+101,109,0.118
+101,111,0.503
+101,121,0.578
+103,103,0.098
+103,104,0.118
+103,108,0.348
+103,109,0.118
+103,111,0.503
+103,121,0.578
diff --git a/activitysim/abm/test/trip_dest/data/mini.omx b/activitysim/abm/test/trip_dest/data/mini.omx
new file mode 100644
index 000000000..122693fb7
Binary files /dev/null and b/activitysim/abm/test/trip_dest/data/mini.omx differ
diff --git a/activitysim/abm/test/trip_dest/data/out_trips.csv b/activitysim/abm/test/trip_dest/data/out_trips.csv
new file mode 100644
index 000000000..d4456a9cd
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/data/out_trips.csv
@@ -0,0 +1,7 @@
+trip_id,tour_id,outbound,person_id,trip_num,trip_count,purpose,primary_purpose,origin,destination,failed,destination_logsum
+10001,500,True,1,1,1,work,work,0,3,False,
+10002,500,False,1,1,2,social,work,3,1,False,-5.062940251818796
+10003,500,False,1,2,2,home,work,1,0,False,
+20003,501,True,4,1,1,social,social,2,8,False,
+20004,501,False,4,1,2,eatout,social,8,1,False,13.322331251251137
+20005,501,False,4,2,2,home,social,1,2,False,
diff --git a/activitysim/abm/test/trip_dest/data/persons.csv b/activitysim/abm/test/trip_dest/data/persons.csv
new file mode 100644
index 000000000..11047e122
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/data/persons.csv
@@ -0,0 +1,16 @@
+PERID,PNUM,age,household_id
+0,1,69,1
+1,2,69,1
+2,1,61,2
+3,2,61,2
+4,1,61,3
+5,2,51,3
+6,1,52,4
+7,2,52,4
+8,1,73,5
+9,1,73,6
+10,1,73,7
+11,1,73,8
+12,1,65,9
+13,1,73,10
+14,2,65,10
diff --git a/activitysim/abm/test/trip_dest/data/taz.csv b/activitysim/abm/test/trip_dest/data/taz.csv
new file mode 100644
index 000000000..890e8cb1c
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/data/taz.csv
@@ -0,0 +1,6 @@
+TAZ
+2
+3
+5
+7
+11
diff --git a/activitysim/abm/test/trip_dest/data/tours.csv b/activitysim/abm/test/trip_dest/data/tours.csv
new file mode 100644
index 000000000..d413dc9f5
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/data/tours.csv
@@ -0,0 +1,3 @@
+tour_id,person_id,tour_mode,start,end,origin,destination,tour_category,purpose
+500,1,DA,10,20,0,3,mandatory,work
+501,4,WALK,15,22,2,8,non_mandatory,social
\ No newline at end of file
diff --git a/activitysim/abm/test/trip_dest/data/trips.csv b/activitysim/abm/test/trip_dest/data/trips.csv
new file mode 100644
index 000000000..48570c0b8
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/data/trips.csv
@@ -0,0 +1,7 @@
+trip_id,tour_id,outbound,person_id,trip_num,trip_count,purpose,primary_purpose,origin,destination,failed
+10001,500,TRUE,1,1,1,work,work,0,3,FALSE
+10002,500,FALSE,1,1,2,social,work,3,0,FALSE
+10003,500,FALSE,1,2,2,home,work,3,0,FALSE
+20003,501,TRUE,4,1,1,social,social,2,8,FALSE
+20004,501,FALSE,4,1,2,eatout,social,8,2,FALSE
+20005,501,FALSE,4,2,2,home,social,8,2,FALSE
\ No newline at end of file
diff --git a/activitysim/abm/test/trip_dest/test_trip_destination.py b/activitysim/abm/test/trip_dest/test_trip_destination.py
new file mode 100644
index 000000000..fdfd9b6de
--- /dev/null
+++ b/activitysim/abm/test/trip_dest/test_trip_destination.py
@@ -0,0 +1,48 @@
+from __future__ import annotations
+
+import shutil
+from pathlib import Path
+
+import pandas as pd
+
+from activitysim import abm  # noqa: F401
+from activitysim.core import workflow as wf
+
+
+def test_trip_destination(tmp_path: Path):
+    shutil.copytree(
+        Path(__file__).parent.joinpath("configs"), tmp_path.joinpath("configs")
+    )
+    shutil.copytree(Path(__file__).parent.joinpath("data"), tmp_path.joinpath("data"))
+
+    state = wf.State.make_default(working_dir=tmp_path)
+
+    # init tours
+    tours = pd.read_csv(
+        tmp_path / state.filesystem.data_dir[0] / "tours.csv"
+    ).set_index("tour_id")
+    state.add_table("tours", tours)
+    state.tracing.register_traceable_table("tours", tours)
+    state.get_rn_generator().add_channel("tours", tours)
+
+    # init trips
+    trips = pd.read_csv(
+        tmp_path / state.filesystem.data_dir[0] / "trips.csv"
+    ).set_index("trip_id")
+    state.add_table("trips", trips)
+    state.tracing.register_traceable_table("trips", trips)
+    state.get_rn_generator().add_channel("trips", trips)
+
+    state.run.all()
+
+    out_trips = state.get_dataframe("trips")
+
+    # logsums are generated for intermediate trips only
+    assert out_trips["destination_logsum"].isna().tolist() == [
+        True,
+        False,
+        True,
+        True,
+        False,
+        True,
+    ]
diff --git a/activitysim/core/configuration/base.py b/activitysim/core/configuration/base.py
index 6936e6d1a..2a18adec2 100644
--- a/activitysim/core/configuration/base.py
+++ b/activitysim/core/configuration/base.py
@@ -161,7 +161,7 @@ class ComputeSettings(PydanticBase):
 
     """
 
-    fastmath: bool = True
+    fastmath: bool = False
     """Use fastmath when evaluating this component with sharrow.
 
     The fastmath option can be used to speed up the evaluation of expressions in
@@ -170,6 +170,14 @@ class ComputeSettings(PydanticBase):
     computations are NaN or Inf.  This can lead to errors when the assumptions
     are violated.  If running in sharrow test mode generates errors, try turning
     this setting off.
+    
+    .. versionchanged:: 1.6
+
+        In ActivitySim versions 1.5 and earlier, the default value for this
+        setting was `True`, meant to favor superior runtime performance when
+        using sharrow. However, due to the difficulty of diagnosing and fixing
+        bugs that arise from the use of `fastmath`, the default setting has been
+        changed to `False`. 
     """
 
     use_bottleneck: bool | None = None
diff --git a/activitysim/core/los.py b/activitysim/core/los.py
index 5ac90f930..7f6f5b4c8 100644
--- a/activitysim/core/los.py
+++ b/activitysim/core/los.py
@@ -497,6 +497,9 @@ def load_data(self):
             else:  # SkimDataset
                 assert len(skims.dataset.indexes["otaz"]) == len(
                     self.state.get_dataframe("land_use_taz")
+                ), (
+                    f"land_use_taz table length {len(self.state.get_dataframe('land_use_taz'))} does not match "
+                    f"taz skim length {len(skims.dataset.indexes['otaz'])}"
                 )
 
     def create_skim_dict(self, skim_tag, _override_offset_int=None):
diff --git a/activitysim/core/skim_dataset.py b/activitysim/core/skim_dataset.py
index 14c7ed862..2ee7aff00 100644
--- a/activitysim/core/skim_dataset.py
+++ b/activitysim/core/skim_dataset.py
@@ -594,6 +594,7 @@ def load_sparse_maz_skims(
     maz_to_maz_tables=(),
     max_blend_distance=None,
     data_file_resolver=None,
+    max_float_precision: int = 32,
 ):
     """
     Load sparse MAZ data on top of TAZ skim data.
@@ -677,11 +678,19 @@ def load_sparse_maz_skims(
                 max_blend_distance_i = max_blend_distance.get(
                     colname, max_blend_distance_i
                 )
+                current_data = df[colname]
+                if max_float_precision:
+                    # if current data is a float dtype of higher precision than `max_float_precision`, downcast it.
+                    if np.issubdtype(current_data.dtype, np.floating):
+                        if current_data.dtype.itemsize > (max_float_precision // 8):
+                            current_data = current_data.astype(
+                                f"float{max_float_precision}"
+                            )
                 dataset.redirection.sparse_blender(
                     colname,
                     df.OMAZ,
                     df.DMAZ,
-                    df[colname],
+                    current_data,
                     max_blend_distance=max_blend_distance_i,
                     index=land_use_index,
                 )
diff --git a/docs/dev-guide/changes.md b/docs/dev-guide/changes.md
index 2cd584b3c..98879d4a5 100644
--- a/docs/dev-guide/changes.md
+++ b/docs/dev-guide/changes.md
@@ -8,39 +8,49 @@ configurations or code to fail to run correctly.
 
 ## Upcoming Changes
 
-This section describes changes that are implemented in current development 
-branch (i.e., the main branch on GitHub), but not yet released in a stable version 
-of ActivitySim.  See below under the various version headings for changes in 
+This section describes changes that are implemented in current development
+branch (i.e., the main branch on GitHub), but not yet released in a stable version
+of ActivitySim.  See below under the various version headings for changes in
 released versions.
 
+### Changed Default for Sharrow "Fastmath" Optimization
+
+The default setting for the "fastmath" optimization in sharrow has been changed
+from `True` to `False`.  This optimization can improve performance in some cases,
+but can also cause subtle and hard to diagnose bugs, particularly when the
+data being processed contains `NaN` or `Inf` values.  By defaulting to
+`False`, we aim to improve platform stability for most users.  Users who wish
+to enable the "fastmath" optimization can do so by setting the `fastmath` option
+to `True` in the `compute_settings` for each model component where it is desired.
+
 
 ## v1.5.1
 
-This release includes a handful of minor updates and fixes, as well as enhancements 
-to the ActivtySim documentation. Users should generally not expect any breaking 
-changes relative to v1.5.0, except that when running a simulation there will be a 
+This release includes a handful of minor updates and fixes, as well as enhancements
+to the ActivtySim documentation. Users should generally not expect any breaking
+changes relative to v1.5.0, except that when running a simulation there will be a
 significant reduction in logging messages displayed on screen and written to the run log.
 
 
 ## v1.5
 
-This release includes most of the new features and enhancements developed as part 
+This release includes most of the new features and enhancements developed as part
 of the Phase 10 work.
 
 ### Preprocessing & Annotation
 
-We have expanded preprocessing & annotation functionality, which is now standardized 
-in formatting and available on most model components.  Existing model implementations 
-may need to make minor upgrades to model configuration files to conform with the new 
-standardized formatting. 
+We have expanded preprocessing & annotation functionality, which is now standardized
+in formatting and available on most model components.  Existing model implementations
+may need to make minor upgrades to model configuration files to conform with the new
+standardized formatting.
 
 ### Estimation Mode
 
-Estimation mode has been updated to work with Larch v6.  This new version of Larch 
-is modernized and more stable across platforms, and is more consistent with ActivitySim 
-spec files (as both are now built on Sharrow).  The overall workflow for re-estimating 
-model parameters is very similar to before, but users will need to use Larch v6 instead 
-of Larch v5.  In addition, some new capabilities have been added for modifying model 
+Estimation mode has been updated to work with Larch v6.  This new version of Larch
+is modernized and more stable across platforms, and is more consistent with ActivitySim
+spec files (as both are now built on Sharrow).  The overall workflow for re-estimating
+model parameters is very similar to before, but users will need to use Larch v6 instead
+of Larch v5.  In addition, some new capabilities have been added for modifying model
 specifications in Larch (instead of re-running ActivitySim).
 
 ### Using UV for Dependency Management
@@ -52,21 +62,21 @@ for details on how to install ActivitySim using UV.
 
 ### Skim Naming Conflict Resolution
 
-The SkimDataset structure (required when using sharrow, optional in legacy mode) 
-requires every skim variable to have a unique name. It also merges OMX variables 
-based on time period, so that e.g. `BIKETIME__AM` and `BIKETIME__PM`, which would 
-be 2-d arrays in the OMX file, become just two different parts of a 3-d array 
-called `BIKETIME` in the SkimDataset. This is problematic when the skims also 
-contain a 2-d array called `BIKETIME`, as that has no temporal dimension, and it 
-gets loaded into a 2-d array in the SkimDataset, with the same name as the 3-d array, 
+The SkimDataset structure (required when using sharrow, optional in legacy mode)
+requires every skim variable to have a unique name. It also merges OMX variables
+based on time period, so that e.g. `BIKETIME__AM` and `BIKETIME__PM`, which would
+be 2-d arrays in the OMX file, become just two different parts of a 3-d array
+called `BIKETIME` in the SkimDataset. This is problematic when the skims also
+contain a 2-d array called `BIKETIME`, as that has no temporal dimension, and it
+gets loaded into a 2-d array in the SkimDataset, with the same name as the 3-d array,
 and thus one is overwritten and lost.
 
-ActivitySim now includes a skims input check to identify this overwriting condition, 
-and raise an error if it is happening, so that the user can correct the condition 
-via (1) the `omx_ignore_patterns` setting, (2) revising the skim generation process 
-to not create the overlapping named skims in the file in the first place, 
-or (3) renaming one or both skims if the users actually wants both skims variables 
-in the model. The error message generated includes a link to instructions and 
+ActivitySim now includes a skims input check to identify this overwriting condition,
+and raise an error if it is happening, so that the user can correct the condition
+via (1) the `omx_ignore_patterns` setting, (2) revising the skim generation process
+to not create the overlapping named skims in the file in the first place,
+or (3) renaming one or both skims if the users actually wants both skims variables
+in the model. The error message generated includes a link to instructions and
 discussion of these alternatives.
 
 ### Settings Checker
@@ -93,12 +103,12 @@ See [Expression Profiling](Expression-Profiling) for details.
 
 A new telecommute status model component has been added to ActivitySim. This component
 models the telecommute status of workers, which can be used to determine
-whether a worker telecommutes full-time, part-time, or not at all. A simple 
-implementation of the telecommute status model can be based on the worker's telecommute 
-frequency. For example, if a worker telecommutes 4 days a week, then there is 
-a 80% probability for them to telecommute on the simulation day. The telecommute 
-status model software can accommodate more complex model forms if needed. An example 
-telecommute status model specification can be found in 
+whether a worker telecommutes full-time, part-time, or not at all. A simple
+implementation of the telecommute status model can be based on the worker's telecommute
+frequency. For example, if a worker telecommutes 4 days a week, then there is
+a 80% probability for them to telecommute on the simulation day. The telecommute
+status model software can accommodate more complex model forms if needed. An example
+telecommute status model specification can be found in
 [ActivitySim/sandag-abm3-example#30](https://github.com/ActivitySim/sandag-abm3-example/pull/30).