3.10 Auxiliary Demand - Revision history

Bpaul at 00:08, 13 March 2023

2023-03-13T00:08:25Z

Bpaul at 00:07, 13 March 2023

2023-03-13T00:07:58Z

Bpaul at 00:07, 13 March 2023

2023-03-13T00:07:45Z

Bpaul at 00:07, 13 March 2023

2023-03-13T00:07:25Z

Bpaul at 00:02, 13 March 2023

2023-03-13T00:02:41Z

Bpaul at 00:00, 13 March 2023

2023-03-13T00:00:53Z

Bpaul at 23:57, 12 March 2023

2023-03-12T23:57:41Z

Bpaul at 23:57, 12 March 2023

2023-03-12T23:57:21Z

Bpaul: Created page with "Category:3.0 Model Design
DaySim provides detailed predictions of the long-term and short-term travel choices of regional residents, but this tra..."

2023-03-11T01:09:19Z

Created page with "Category:3.0 Model Design DaySim provides detailed predictions of the long-term and short-term travel choices of regional residents, but this tra..."

New page

[[Category:3.0 Model Design]]

DaySim provides detailed predictions of the long-term and short-term travel choices of regional residents, but this travel demand does not fully represent all trips that use the regional transportation networks. DaySim only represents the internal passenger travel demand made by residents of the region which accounts for about 80-85% of the total regional demand (in the base year). There is other auxiliary demand which must be accounted for that is contributed by trucks and commercial vehicles, truck freight to/from the Port of Jacksonville and most importantly three (3) different flavors of external travel made by both residents of the planning area as well as non-residents. The three (3) different flavors of external travel are internal-to-external, external-to-internal and external-to-external (thrutrips). Commercial and truck traffic typically comprise a significant shore of all roadway volumes. In addition, non-residents enter the region through key external gateways to access jobs, shopping or other opportunities, and similarly, the residents may leave the region to satisfy other needs. This “auxiliary demand” is derived from the existing four-step model system.<h3 id="id-3.9AUXILIARYDEMAND-PortFreight">Port Freight</h3>The ‘Develop Freight Truck Trip Tables’ application is the first step in the integrated NERPM-AB model system. This application prepares an origin-destination freight truck trip table representing the freight demand produced by and attracted to the Port of Jacksonville, Florida (JAXPORT).<ul><li>Application Name = Develop Freight Truck Trip Tables from SWM</li><li>Application Purpose = Develops freight truck trip OD matrix representing travel to and from the Port of Jacksonville</li><li>Primary Input = Florida Statewide Model highway network and trip tables</li><li>Primary Output = Freight truck trip matrix (*.mat)</li></ul>The application performs a subarea extraction process using the Florida Statewide Model (SWM). The subarea extraction process (subarea assignment and matrix extraction) produces a matrix of truck trips destined to and originating from the traffic analysis zones representing JAXPORT in the Florida Statewide Model. The application produces this matrix and ultimately prepares a freight truck trip table renumbered to reflect the NERPM-AB traffic analysis zone structure and numbering scheme which is different than the SWM.The ‘Develop Freight Truck Trip Tables’ application includes separate processes to prepare 2010 base year JAXPORT demand and 2040 future year demand using the assumptions in the Florida Statewide Model. The 2010 and 2040 process is identical but for the SWM horizon year input files used to initiate the sub-area extraction. The application also includes a process to interpolate the freight truck trip tables for analysis years between 2010 and 2040 (or beyond) based on the implied growth.<h3 id="id-3.9AUXILIARYDEMAND-Non-HH">Non-HH</h3>Non household (non-hh) trips are generated and distributed separately. The ‘Generation’ and ‘Distribution’ applications in NERPM-AB create II truck, IE and EE truck, and IE and EE vehicle trip tables. This demand is added to the II vehicle demand created by DaySim before assignment. The table below illustrates the demand from the trip generation model which is retained in the NERPM-AB model system and which is replaced and overwritten by the DaySim activity-based demand model.<h4 class="BodyParagraph" id="id-3.9AUXILIARYDEMAND-TABLE3-10NERPM-ABMODELDEMANDESTIMATEDBYTRIPGENERATIONMODEL">TABLE 3-10 NERPM-AB MODEL DEMAND ESTIMATED BY TRIP GENERATION MODEL</h4><div class="table-wrap">
{| class="wikitable"
| class="highlight-red confluenceTd" data-highlight-colour="red" | Description
| class="highlight-red confluenceTd" data-highlight-colour="red" | Acronym
| class="highlight-red confluenceTd" data-highlight-colour="red" | NERPM-AB
|-
| class="confluenceTd" | Home-based work
| class="confluenceTd" | HBW
| class="confluenceTd" | Replaced by DaySim
|-
| class="confluenceTd" | Home-based shop
| class="confluenceTd" | HBSH
| class="confluenceTd" | Replaced by DaySim
|-
| class="confluenceTd" | Home-based social and recreational
| class="confluenceTd" | HBSR
| class="confluenceTd" | Replaced by DaySim
|-
| class="confluenceTd" | Home-based other
| class="confluenceTd" | HBO
| class="confluenceTd" | Replaced by DaySim
|-
| class="confluenceTd" | Nonhome-based
| class="confluenceTd" | NHB
| class="confluenceTd" | Replaced by DaySim
|-
| class="confluenceTd" | Four-wheeled truck
| class="confluenceTd" | LT
| class="confluenceTd" | Retained from NERPM42
|-
| class="confluenceTd" | Single-unit truck
| class="confluenceTd" | MT
| class="confluenceTd" | Retained from NERPM42
|-
| class="confluenceTd" | Combination truck-trailer
| class="confluenceTd" | HT
| class="confluenceTd" | Retained from NERPM42
|-
| class="confluenceTd" | Single-occupancy vehicle internal-external
| class="confluenceTd" | SOVIE
| class="confluenceTd" | Retained from NERPM42
|-
| class="confluenceTd" | High-occupancy vehicle internal-external
| class="confluenceTd" | HOVIE
| class="confluenceTd" | Retained from NERPM42
|-
| class="confluenceTd" | Light-duty truck internal-external
| class="confluenceTd" | LDIE
| class="confluenceTd" | Retained from NERPM42
|-
| class="confluenceTd" | Heavy-duty truck internal-external
| class="confluenceTd" | HDIE
| class="confluenceTd" | Retained from NERPM42
|-
| class="confluenceTd" | Single-occupancy vehicle external-external
| class="confluenceTd" | SOVEE
| class="confluenceTd" | Retained from NERPM42
|-
| class="confluenceTd" | High-occupancy vehicle external-external
| class="confluenceTd" | HOVEE
| class="confluenceTd" | Retained from NERPM42
|-
| class="confluenceTd" | Light-duty truck external-external
| class="confluenceTd" | LDEE
| class="confluenceTd" | Retained from NERPM42
|-
| class="confluenceTd" | Heavy-duty truck external-external
| class="confluenceTd" | HDEE
| class="confluenceTd" | Retained from NERPM42
|}</div>

@@ Line 3: / Line 3: @@
 <p class="BodyParagraph">DaySim provides detailed predictions of the long-term and short-term travel choices of regional residents, but this travel demand does not fully represent all trips that use the regional transportation networks. DaySim only represents the internal passenger travel demand made by residents of the region which accounts for about 80-85% of the total regional demand (<em>in the base year</em>). There is other auxiliary demand which must be accounted for that is contributed by trucks and commercial vehicles, truck freight to/from the Port of Jacksonville and most importantly three (3) different flavors of external travel made by both residents of the planning area as well as non-residents. The three (3) different flavors of external travel are internal-to-external, external-to-internal and external-to-external (<em>thru</em><em>trips</em>). Commercial and truck traffic typically comprise a significant shore of all roadway volumes. In addition, non-residents enter the region through key external gateways to access jobs, shopping or other opportunities, and similarly, the residents may leave the region to satisfy other needs. This “auxiliary demand” is derived from the existing four-step model system.
-</p><h3 id="id-3.9AUXILIARYDEMAND-PortFreight"><span style="color: rgb(255,102,0);">Port Freight</span></h3><p class="BodyParagraph">The '''''interpolate_port_truck_tt.py''''' script prepares an origin-destination freight truck trip table representing the freight demand produced by and attracted to the Port of Jacksonville, Florida (JAXPORT). The script takes JAXPORT demand for 2010 and 2040 as inputs and interpolates the freight truck trip tables for analysis years between 2010 and 2040 (or beyond) based on the implied growth.
+</p><h3 id="id-3.9AUXILIARYDEMAND-PortFreight"><span style="color: rgb(255,102,0);">Port Freight</span></h3><p class="BodyParagraph">The '''''interpolate_port_truck_tt.py''''' Python script prepares an origin-destination freight truck trip table representing the freight demand produced by and attracted to the Port of Jacksonville, Florida (JAXPORT). The script takes JAXPORT demand for 2010 and 2040 as inputs and interpolates the freight truck trip tables for analysis years between 2010 and 2040 (or beyond) based on the implied growth.
-</p><h3 id="id-3.9AUXILIARYDEMAND-Non-HH"><span style="color: rgb(255,102,0);">Non-HH</span></h3><p class="BodyParagraph">Non household (non-hh) trips are generated and distributed separately. The '''''tgen_main.py''''' script in the '''Auxiliary Demand Generation''' group of the procedure sequence generates the zonal productions and attractions. The procedure steps in the '''Trip Distribution - Auxiliary Models''' group run trip distributions and create II truck, IE and EE truck, and IE and EE vehicle trip tables. This demand is added to the II vehicle demand created by DaySim before assignment. The table below illustrates the demand from the trip generation model which is retained in the NERPM-AB model system and which is replaced and overwritten by the DaySim activity-based demand model.</p><h4 class="BodyParagraph" id="id-3.9AUXILIARYDEMAND-TABLE3-10NERPM-ABMODELDEMANDESTIMATEDBYTRIPGENERATIONMODEL">TABLE 3-10 NERPM-AB MODEL DEMAND ESTIMATED BY TRIP GENERATION MODEL</h4><div class="table-wrap">
+</p><h3 id="id-3.9AUXILIARYDEMAND-Non-HH"><span style="color: rgb(255,102,0);">Non-HH</span></h3><p class="BodyParagraph">Non household (non-hh) trips are generated and distributed separately. The '''''tgen_main.py''''' Python script in the '''Auxiliary Demand Generation''' group of the procedure sequence generates the zonal productions and attractions. The procedure steps in the '''Trip Distribution - Auxiliary Models''' group run trip distributions and create II truck, IE and EE truck, and IE and EE vehicle trip tables. This demand is added to the II vehicle demand created by DaySim before assignment. The table below illustrates the demand from the trip generation model which is retained in the NERPM-AB model system and which is replaced and overwritten by the DaySim activity-based demand model.</p><h4 class="BodyParagraph" id="id-3.9AUXILIARYDEMAND-TABLE3-10NERPM-ABMODELDEMANDESTIMATEDBYTRIPGENERATIONMODEL">TABLE 3-10 NERPM-AB MODEL DEMAND ESTIMATED BY TRIP GENERATION MODEL</h4><div class="table-wrap">
 {|  class="wikitable"
 |  class="highlight-red confluenceTd" data-highlight-colour="red" | <p class="TableHeadingGray"><strong>Description</strong></p>

@@ Line 5: / Line 5: @@
 </p><h3 id="id-3.9AUXILIARYDEMAND-PortFreight"><span style="color: rgb(255,102,0);">Port Freight</span></h3><p class="BodyParagraph">The '''''interpolate_port_truck_tt.py''''' script prepares an origin-destination freight truck trip table representing the freight demand produced by and attracted to the Port of Jacksonville, Florida (JAXPORT). The script takes JAXPORT demand for 2010 and 2040 as inputs and interpolates the freight truck trip tables for analysis years between 2010 and 2040 (or beyond) based on the implied growth.
-</p><h3 id="id-3.9AUXILIARYDEMAND-Non-HH"><span style="color: rgb(255,102,0);">Non-HH</span></h3><p class="BodyParagraph">Non household (non-hh) trips are generated and distributed separately. The '''''tgen_main.py''''' script in the '''Auxiliary Dmand Generation''' group of the procedure sequence generates the zonal productions and attractions. The procedure steps in the '''Trip Distribution - Auxiliary Models''' group run trip distributions and create II truck, IE and EE truck, and IE and EE vehicle trip tables. This demand is added to the II vehicle demand created by DaySim before assignment. The table below illustrates the demand from the trip generation model which is retained in the NERPM-AB model system and which is replaced and overwritten by the DaySim activity-based demand model.</p><h4 class="BodyParagraph" id="id-3.9AUXILIARYDEMAND-TABLE3-10NERPM-ABMODELDEMANDESTIMATEDBYTRIPGENERATIONMODEL">TABLE 3-10 NERPM-AB MODEL DEMAND ESTIMATED BY TRIP GENERATION MODEL</h4><div class="table-wrap">
+</p><h3 id="id-3.9AUXILIARYDEMAND-Non-HH"><span style="color: rgb(255,102,0);">Non-HH</span></h3><p class="BodyParagraph">Non household (non-hh) trips are generated and distributed separately. The '''''tgen_main.py''''' script in the '''Auxiliary Demand Generation''' group of the procedure sequence generates the zonal productions and attractions. The procedure steps in the '''Trip Distribution - Auxiliary Models''' group run trip distributions and create II truck, IE and EE truck, and IE and EE vehicle trip tables. This demand is added to the II vehicle demand created by DaySim before assignment. The table below illustrates the demand from the trip generation model which is retained in the NERPM-AB model system and which is replaced and overwritten by the DaySim activity-based demand model.</p><h4 class="BodyParagraph" id="id-3.9AUXILIARYDEMAND-TABLE3-10NERPM-ABMODELDEMANDESTIMATEDBYTRIPGENERATIONMODEL">TABLE 3-10 NERPM-AB MODEL DEMAND ESTIMATED BY TRIP GENERATION MODEL</h4><div class="table-wrap">
 {|  class="wikitable"
 |  class="highlight-red confluenceTd" data-highlight-colour="red" | <p class="TableHeadingGray"><strong>Description</strong></p>

@@ Line 5: / Line 5: @@
 </p><h3 id="id-3.9AUXILIARYDEMAND-PortFreight"><span style="color: rgb(255,102,0);">Port Freight</span></h3><p class="BodyParagraph">The '''''interpolate_port_truck_tt.py''''' script prepares an origin-destination freight truck trip table representing the freight demand produced by and attracted to the Port of Jacksonville, Florida (JAXPORT). The script takes JAXPORT demand for 2010 and 2040 as inputs and interpolates the freight truck trip tables for analysis years between 2010 and 2040 (or beyond) based on the implied growth.
-</p><h3 id="id-3.9AUXILIARYDEMAND-Non-HH"><span style="color: rgb(255,102,0);">Non-HH</span></h3><p class="BodyParagraph">Non household (non-hh) trips are generated and distributed separately. The '''''tgen_main.py''''' script in the Auxiliary Dmand Generation group of the procedure sequence generates the zonal productions and attractions. The procedure steps in the '''Trip Distribution - Auxiliary Models''' group run trip distributions and create II truck, IE and EE truck, and IE and EE vehicle trip tables. This demand is added to the II vehicle demand created by DaySim before assignment. The table below illustrates the demand from the trip generation model which is retained in the NERPM-AB model system and which is replaced and overwritten by the DaySim activity-based demand model.</p><h4 class="BodyParagraph" id="id-3.9AUXILIARYDEMAND-TABLE3-10NERPM-ABMODELDEMANDESTIMATEDBYTRIPGENERATIONMODEL">TABLE 3-10 NERPM-AB MODEL DEMAND ESTIMATED BY TRIP GENERATION MODEL</h4><div class="table-wrap">
+</p><h3 id="id-3.9AUXILIARYDEMAND-Non-HH"><span style="color: rgb(255,102,0);">Non-HH</span></h3><p class="BodyParagraph">Non household (non-hh) trips are generated and distributed separately. The '''''tgen_main.py''''' script in the '''Auxiliary Dmand Generation''' group of the procedure sequence generates the zonal productions and attractions. The procedure steps in the '''Trip Distribution - Auxiliary Models''' group run trip distributions and create II truck, IE and EE truck, and IE and EE vehicle trip tables. This demand is added to the II vehicle demand created by DaySim before assignment. The table below illustrates the demand from the trip generation model which is retained in the NERPM-AB model system and which is replaced and overwritten by the DaySim activity-based demand model.</p><h4 class="BodyParagraph" id="id-3.9AUXILIARYDEMAND-TABLE3-10NERPM-ABMODELDEMANDESTIMATEDBYTRIPGENERATIONMODEL">TABLE 3-10 NERPM-AB MODEL DEMAND ESTIMATED BY TRIP GENERATION MODEL</h4><div class="table-wrap">
 {|  class="wikitable"
 |  class="highlight-red confluenceTd" data-highlight-colour="red" | <p class="TableHeadingGray"><strong>Description</strong></p>

@@ Line 3: / Line 3: @@
 <p class="BodyParagraph">DaySim provides detailed predictions of the long-term and short-term travel choices of regional residents, but this travel demand does not fully represent all trips that use the regional transportation networks. DaySim only represents the internal passenger travel demand made by residents of the region which accounts for about 80-85% of the total regional demand (<em>in the base year</em>). There is other auxiliary demand which must be accounted for that is contributed by trucks and commercial vehicles, truck freight to/from the Port of Jacksonville and most importantly three (3) different flavors of external travel made by both residents of the planning area as well as non-residents. The three (3) different flavors of external travel are internal-to-external, external-to-internal and external-to-external (<em>thru</em><em>trips</em>). Commercial and truck traffic typically comprise a significant shore of all roadway volumes. In addition, non-residents enter the region through key external gateways to access jobs, shopping or other opportunities, and similarly, the residents may leave the region to satisfy other needs. This “auxiliary demand” is derived from the existing four-step model system.
-</p><h3 id="id-3.9AUXILIARYDEMAND-PortFreight"><span style="color: rgb(255,102,0);">Port Freight</span></h3><p class="BodyParagraph">The interpolate_port_truck_tt.py script prepares an origin-destination freight truck trip table representing the freight demand produced by and attracted to the Port of Jacksonville, Florida (JAXPORT). The script takes JAXPORT demand for 2010 and 2040 as inputs and interpolates the freight truck trip tables for analysis years between 2010 and 2040 (or beyond) based on the implied growth.
+</p><h3 id="id-3.9AUXILIARYDEMAND-PortFreight"><span style="color: rgb(255,102,0);">Port Freight</span></h3><p class="BodyParagraph">The '''''interpolate_port_truck_tt.py''''' script prepares an origin-destination freight truck trip table representing the freight demand produced by and attracted to the Port of Jacksonville, Florida (JAXPORT). The script takes JAXPORT demand for 2010 and 2040 as inputs and interpolates the freight truck trip tables for analysis years between 2010 and 2040 (or beyond) based on the implied growth.
-</p><h3 id="id-3.9AUXILIARYDEMAND-Non-HH"><span style="color: rgb(255,102,0);">Non-HH</span></h3><p class="BodyParagraph">Non household (non-hh) trips are generated and distributed separately. The ‘Generation’ and ‘Distribution’ applications in NERPM-AB create II truck, IE and EE truck, and IE and EE vehicle trip tables. This demand is added to the II vehicle demand created by DaySim before assignment. The table below illustrates the demand from the trip generation model which is retained in the NERPM-AB model system and which is replaced and overwritten by the DaySim activity-based demand model.</p><h4 class="BodyParagraph" id="id-3.9AUXILIARYDEMAND-TABLE3-10NERPM-ABMODELDEMANDESTIMATEDBYTRIPGENERATIONMODEL">TABLE 3-10 NERPM-AB MODEL DEMAND ESTIMATED BY TRIP GENERATION MODEL</h4><div class="table-wrap">
+</p><h3 id="id-3.9AUXILIARYDEMAND-Non-HH"><span style="color: rgb(255,102,0);">Non-HH</span></h3><p class="BodyParagraph">Non household (non-hh) trips are generated and distributed separately. The '''''tgen_main.py''''' script in the Auxiliary Dmand Generation group of the procedure sequence generates the zonal productions and attractions. The procedure steps in the '''Trip Distribution - Auxiliary Models''' group run trip distributions and create II truck, IE and EE truck, and IE and EE vehicle trip tables. This demand is added to the II vehicle demand created by DaySim before assignment. The table below illustrates the demand from the trip generation model which is retained in the NERPM-AB model system and which is replaced and overwritten by the DaySim activity-based demand model.</p><h4 class="BodyParagraph" id="id-3.9AUXILIARYDEMAND-TABLE3-10NERPM-ABMODELDEMANDESTIMATEDBYTRIPGENERATIONMODEL">TABLE 3-10 NERPM-AB MODEL DEMAND ESTIMATED BY TRIP GENERATION MODEL</h4><div class="table-wrap">
 {|  class="wikitable"
 |  class="highlight-red confluenceTd" data-highlight-colour="red" | <p class="TableHeadingGray"><strong>Description</strong></p>

@@ Line 3: / Line 3: @@
 <p class="BodyParagraph">DaySim provides detailed predictions of the long-term and short-term travel choices of regional residents, but this travel demand does not fully represent all trips that use the regional transportation networks. DaySim only represents the internal passenger travel demand made by residents of the region which accounts for about 80-85% of the total regional demand (<em>in the base year</em>). There is other auxiliary demand which must be accounted for that is contributed by trucks and commercial vehicles, truck freight to/from the Port of Jacksonville and most importantly three (3) different flavors of external travel made by both residents of the planning area as well as non-residents. The three (3) different flavors of external travel are internal-to-external, external-to-internal and external-to-external (<em>thru</em><em>trips</em>). Commercial and truck traffic typically comprise a significant shore of all roadway volumes. In addition, non-residents enter the region through key external gateways to access jobs, shopping or other opportunities, and similarly, the residents may leave the region to satisfy other needs. This “auxiliary demand” is derived from the existing four-step model system.
-</p><h3 id="id-3.9AUXILIARYDEMAND-PortFreight"><span style="color: rgb(255,102,0);">Port Freight</span></h3><p class="BodyParagraph">The interpolate_port_truck_tt.py script prepares an origin-destination freight truck trip table representing the freight demand produced by and attracted to the Port of Jacksonville, Florida (JAXPORT).</p><ul><li><strong>Application Name</strong> = Develop Freight Truck Trip Tables from SWM</li><li><strong>Application Purpose</strong> = Develops freight truck trip OD matrix representing travel to and from the Port of Jacksonville</li><li><strong>Primary Input</strong> = Florida Statewide Model highway network and trip tables</li><li><strong>Primary Output</strong> = Freight truck trip matrix (*.mat)</li></ul><p class="BodyParagraph">The application performs a subarea extraction process using the Florida Statewide Model (SWM). The subarea extraction process (subarea assignment and matrix extraction) produces a matrix of truck trips destined to and originating from the traffic analysis zones representing JAXPORT in the Florida Statewide Model. The application produces this matrix and ultimately prepares a freight truck trip table renumbered to reflect the NERPM-AB traffic analysis zone structure and numbering scheme which is different than the SWM.</p><p class="BodyParagraph">The ‘Develop Freight Truck Trip Tables’ application includes separate processes to prepare 2010 base year JAXPORT demand and 2040 future year demand using the assumptions in the Florida Statewide Model. The 2010 and 2040 process is identical but for the SWM horizon year input files used to initiate the sub-area extraction. The application also includes a process to interpolate the freight truck trip tables for analysis years between 2010 and 2040 (or beyond) based on the implied growth.
+</p><h3 id="id-3.9AUXILIARYDEMAND-PortFreight"><span style="color: rgb(255,102,0);">Port Freight</span></h3><p class="BodyParagraph">The interpolate_port_truck_tt.py script prepares an origin-destination freight truck trip table representing the freight demand produced by and attracted to the Port of Jacksonville, Florida (JAXPORT). The script takes JAXPORT demand for 2010 and 2040 as inputs and interpolates the freight truck trip tables for analysis years between 2010 and 2040 (or beyond) based on the implied growth.
 </p><h3 id="id-3.9AUXILIARYDEMAND-Non-HH"><span style="color: rgb(255,102,0);">Non-HH</span></h3><p class="BodyParagraph">Non household (non-hh) trips are generated and distributed separately. The ‘Generation’ and ‘Distribution’ applications in NERPM-AB create II truck, IE and EE truck, and IE and EE vehicle trip tables. This demand is added to the II vehicle demand created by DaySim before assignment. The table below illustrates the demand from the trip generation model which is retained in the NERPM-AB model system and which is replaced and overwritten by the DaySim activity-based demand model.</p><h4 class="BodyParagraph" id="id-3.9AUXILIARYDEMAND-TABLE3-10NERPM-ABMODELDEMANDESTIMATEDBYTRIPGENERATIONMODEL">TABLE 3-10 NERPM-AB MODEL DEMAND ESTIMATED BY TRIP GENERATION MODEL</h4><div class="table-wrap">

3.10 Auxiliary Demand - Revision history

Bpaul at 00:08, 13 March 2023

Bpaul at 00:07, 13 March 2023

Bpaul at 00:07, 13 March 2023

Bpaul at 00:07, 13 March 2023

Bpaul at 00:02, 13 March 2023

Bpaul at 00:00, 13 March 2023

Bpaul at 23:57, 12 March 2023

Bpaul at 23:57, 12 March 2023

Bpaul: Created page with "Category:3.0 Model Design DaySim provides detailed predictions of the long-term and short-term travel choices of regional residents, but this tra..."

Bpaul: Created page with "Category:3.0 Model Design
DaySim provides detailed predictions of the long-term and short-term travel choices of regional residents, but this tra..."