diff --git a/activitysim/abm/models/util/test/test_person_available_periods.py b/activitysim/abm/models/util/test/test_person_available_periods.py
new file mode 100644
index 000000000..f5cb97eed
--- /dev/null
+++ b/activitysim/abm/models/util/test/test_person_available_periods.py
@@ -0,0 +1,90 @@
+# ActivitySim
+# See full license in LICENSE.txt.
+
+import pandas as pd
+import pandas.testing as pdt
+
+from activitysim.abm.models.util.overlap import person_available_periods
+from activitysim.core import workflow
+
+
+def test_person_available_periods():
+    state = workflow.State.make_default(__file__)
+
+    # state.add_injectable("timetable", timetable)
+
+    persons = pd.DataFrame(index=[1, 2, 3, 4])
+
+    state.add_table("persons", persons)
+
+    timetable = state.get_injectable("timetable")
+
+    # first testing scenario with no tours assigned
+    all_open = person_available_periods(
+        state, persons, start_bin=None, end_bin=None, continuous=False
+    )
+
+    all_open_expected = pd.Series([19, 19, 19, 19], index=[1, 2, 3, 4])
+    pdt.assert_series_equal(all_open, all_open_expected, check_dtype=False)
+
+    # adding tours to the timetable
+
+    tours = pd.DataFrame(
+        {
+            "person_id": [1, 1, 2, 2, 3, 4],
+            "tour_num": [1, 2, 1, 2, 1, 1],
+            "start": [5, 10, 5, 20, 10, 20],
+            "end": [6, 14, 18, 21, 23, 23],
+            "tdds": [1, 89, 13, 181, 98, 183],
+        },
+        index=[1, 2, 3, 4, 5, 6],
+    )
+    # timetable.assign requires only 1 tour per person, so need to loop through tour nums
+    for tour_num, nth_tours in tours.groupby("tour_num", sort=True):
+        timetable.assign(
+            window_row_ids=nth_tours["person_id"],
+            tdds=nth_tours.tdds,
+        )
+
+    # testing time bins now available
+    tours_all_bins = person_available_periods(
+        state, persons, start_bin=None, end_bin=None, continuous=False
+    )
+    tours_all_bins_expected = pd.Series([16, 7, 7, 17], index=[1, 2, 3, 4])
+    pdt.assert_series_equal(tours_all_bins, tours_all_bins_expected, check_dtype=False)
+
+    # continuous time bins available
+    continuous_test = person_available_periods(
+        state, persons, start_bin=None, end_bin=None, continuous=True
+    )
+    continuous_test_expected = pd.Series([10, 6, 6, 16], index=[1, 2, 3, 4])
+    pdt.assert_series_equal(
+        continuous_test, continuous_test_expected, check_dtype=False
+    )
+
+    # start bin test
+    start_test = person_available_periods(
+        state, persons, start_bin=11, end_bin=None, continuous=True
+    )
+    start_test_expected = pd.Series([8, 6, 1, 5], index=[1, 2, 3, 4])
+    pdt.assert_series_equal(start_test, start_test_expected, check_dtype=False)
+
+    # end bin test
+    end_test = person_available_periods(
+        state, persons, start_bin=None, end_bin=11, continuous=False
+    )
+    end_test_expected = pd.Series([9, 1, 6, 12], index=[1, 2, 3, 4])
+    pdt.assert_series_equal(end_test, end_test_expected, check_dtype=False)
+
+    # assortment settings test
+    assortment_test = person_available_periods(
+        state, persons, start_bin=8, end_bin=15, continuous=True
+    )
+    assortment_test_expected = pd.Series([7, 3, 0, 8], index=[1, 2, 3, 4])
+    pdt.assert_series_equal(
+        assortment_test, assortment_test_expected, check_dtype=False
+    )
+
+
+if "__main__" == __name__:
+    test_person_available_periods()