An Integrated Tourbased Truck Travel Forecasting Model

1
An Integrated Tour-basedTruck Travel Forecasting
Model

• Ian Harrington
• Central Transportation Planning Staff
• Boston, Massachusetts

2
Outline of Presentation

• Why prepare a new truck model?
• Identifying available data
• Trip generation model structure
• Trip distribution model structure
• Trip table adjustment
• Forecasting future truck travel

3
Why Prepare a New Truck Model?

• Previous truck trip tables based on old survey
  data
• Using truck trip tables allows for no estimation
  of impact of changes in demographics,
  infrastructure, tolls, or other changes in
  regional transportation system

4
Data Available forTruck Travel Forecasts

• Truck ownership data
• Truck/Vehicle Inventory and Use Surveys
• Residential location and characteristics
• Survey of sample of local businesses
• Field observations of trucks
• Truck trip generation rates
• Interregional truck trip table
• Vehicle classification counts

5
Trip Generation Model Structure

• Trucks fall into the following use categories
• Tankers
• Household Goods
• Truckload/Less-than-Truckload
• Food and Warehouse Distribution
• Intermodal
• Package
• Heavy
• Retail
• Pickup/Van

6
Trip Generation Model Structure

• Truck tours consist of the following trip types
• Regional Truck Tour Ends
• Intermediate Starts and Stops
• Regional Truck Entrances/Exits
• External Truck Entrances/Exits
• Through Truck Entrances/Exits

7
Regional Truck Tour Ends

• Number of truck tour ends is a function of
• Number of trucks
• Number of tours per day
• Portion of days each truck active
• TE 2 Trucks Tours Days Active
• Day
• Estimated for each truck use category

8
Regional Truck Tour Ends

• Number of trucks per employee by industrial
  sector based on CTPS survey

Average
Sector
Trucks/Emp
Government
0.060
Manufacturing
0.045
Agric, Mining, Constr
0.539
Transport, Comm, Util
0.262
Service
0.030
Fin, Insur, Real Estate
0.003
Retail
0.039
Wholesale
0.147
0.076
9
Regional Truck Tour Ends

• Cross-classification of trucks by use category
  and industry based on CTPS field observations

Hhld
LTL
Food
Pickup
Sector
Tankers
Goods
Truckload
Warehouse
Intermodal
Package
Heavy
Retail
and Van
Government
0.0
0.0
0.0
0.0
0.0
20.0
48.0
0.0
32.0
Manufacturing
0.0
0.0
0.0
42.2
0.0
0.0
31.0
1.7
25.0
AMC
0.3
0.0
0.0
0.3
0.0
0.0
42.1
0.3
57.2
TCU
2.7
13.2
34.2
1.5
4.0
11.9
13.5
0.2
18.8
Service
0.7
0.0
0.0
1.2
0.0
0.0
27.6
0.5
69.8
FIRE
0.0
0.0
0.0
0.0
0.0
0.0
23.1
0.0
76.9
Retail
19.9
0.0
0.0
11.2
0.0
0.0
2.7
53.4
12.8
Wholesale
5.9
0.0
0.0
78.6
0.0
0.0
2.7
5.9
6.8
10
Regional Truck Tour Ends

• Trucks in Government and Manufacturing industries
  have distinct distributions by use category

Hhld
LTL
Food
Sector
Tankers
Goods
Truckload
Warehouse
Intermodal
Government
0.0
0.0
0.0
0.0
0.0
Manufacturing
0.0
0.0
0.0
42.2
0.0
Pickup
Sector
Package
Heavy
Retail
and Van
Government
20.0
48.0
0.0
32.0
Manufacturing
0.0
31.0
1.7
25.0
11
Regional Truck Tour Ends

• Operational data from TIUS/VIUS data for
  Massachusetts

Days
Tours
Active
per Day
Tankers
61.0
2.01
Household Goods
63.8
0.9
LTL/TL
91.2
0.9
Food/Warehouse
81.5
1
Intermodal
88.5
0.95
Package
81.5
1.2
Heavy
68.8
1.15
Retail
94.0
1.1
Pickup/Van
86.9
1.3
12
Intermediate Starts and Stops

• Based upon truck trip generation rates in
  literature with adjustments for Eastern MA

1995 Intermediate
Hhld
LTL
Food
Inter-
PU/
Tankers
Goods
/TL
Warehouse
modal
Package
Heavy
Retail
Van
Total
Government
0.0034
0.0004
0
0.05
0
0.04
0.02
0.015
0.09
0.219
Manufacturing
0.004
0.0003
0.05
0.09
0.003
0.05
0.06
0.021
0.15
0.428
Agric, Mining, Constr
0.003
0.00005
0.05
0.05
0
0.03
0.03
0.02
0.1
0.283
Transport, Comm, Util
0.0035
0.0003
0.05
0.05
0.001
0.044
0.044
0.01
0.05
0.253
Service
0.0017
0.0004
0
0.05
0
0.06
0.019
0.015
0.09
0.236
Fire, Insur, Real Estate
0.003
0.0005
0
0.05
0
0.05
0.02
0.015
0.09
0.229
Retail
0.003
0.0002
0.01
0.53
0.0003
0.04
0.02
0.01
0.09
0.704
Wholesale
0.002
0.0001
0.05
0.06
0.0023
0.04
0.02
0.01
0.11
0.294
Households
0.0095
0.0009
0
0.002
0
0.03
0.035
0.015
0.121
0.213
Group Quarters
0.0010
0.0011
0
0.0008
0
0.0115
0.0035
0.0058
0.0465
0.070
13
Intermediate Starts and Stops

• Truck trips generated per employee at government
  and manufacturing worksites

Hhld
LTL
Food
Inter-
Tankers
Goods
/TL
Warehouse
modal
Government
0.0034
0.0004
0
0.05
0
Manufacturing
0.004
0.0003
0.05
0.09
0.003
PU/
Package
Heavy
Retail
Van
Total
Government
0.04
0.02
0.015
0.09
0.2188
Manufacturing
0.05
0.06
0.021
0.15
0.4283
14
Intermediate Starts and Stops

• Supply of intermediate starts and stops based on
  operational data
• SS Stops/Tour Tour Ends/2

Stops
Stops
per Tour
per Tour
Tankers
7
Package
21
Household Goods
2
Heavy
4
LTL/Truckload
4
Retail
6
Food Warehouse
14
Business PU/Van
4
Intermodal
2
15
Intermediate Starts and Stops

• Intraregional truck tour starts and stops
• Intra SS Tour Ends/2 (1 - Tours Ext)
• Stops/Tour

Pct Trips
Pct Trips
External
External
Tankers
24.0
Package
2.0
Household Goods
16.5
Heavy
11.0
LTL/Truckload
39.3
Retail
5.0
Food Warehouse
8.5
Business PU/Van
18.0
Intermodal
50.0
16
Intermediate Starts and Stops

• Regional truck interregional tour
• starts and stops
• Reg IX SS Tour Ends/2 Tours Ext
• Stops/Tour
• Assume interregional tours have one-half the
  number of stops per tour within region

17
Intermediate Starts and Stops

• External truck intermediate starts and stops
• Ext SS Total SS Intra SS
• Local IX SS

18
Regional Truck Entrances/Exits

• Regional truck interregional tour external tour
  ends
• Reg IX Ext TE 2 Reg IX SS
• Stops/Tour
• Assume interregional tours have one half the
  number of stops per tour within region

19
External Truck Entrances/Exits

• External truck tour ends
• Ext TE 2 Ext SS
• Stops/Tour
• Assume interregional tours have one-half the
  number of stops per tour within region

20
Through Truck Entrances/Exits

• Based on external survey truck volumes, subtract
  estimated crossings from total
• Thru TE Tot Vol Reg IX Ext TE Ext TE

21
Truck Trip Distribution

• Use estimated trip ends and adjust initial gamma
  functions to match estimated regional trip length
  frequencies by use category based on TIUS/VIUS
  data for Massachusetts and an interregional trip
  table
• Use double-TAZ setup to match appropriate trip
  end pairs in trip tables

22
Truck Trip Distribution

• Match appropriate pairs of trip productions and
  attractions for intraregional and through truck
  trips

TAZ A
Ext A
TAZ B
Extern B
Attrs
Attrs
Attrs
Attrs
TAZ A
PLocal Reg TEs
Prods
ALocal Reg SSs
Ext A
Prods
TAZ B
PLocal Reg SSs
PLocal Reg SSs
Prods
ALocal Reg TEs
ALocal Reg SSs
Ext B
PThru TEs
Prods
AThru TEs
a
23
Truck Trip Distribution

• Match appropriate pairs of trip productions and
  attractions for interregional truck trips

TAZ A
Ext A
TAZ B
Extern B
Attrs
Attrs
Attrs
Attrs
TAZ A
PReg IX SSs
PReg IX SSs
Prods
AReg IX Ext SSs
AReg IX Ext TEs
PReg IX Ext TEs
Ext A
AReg IX SSs
Prods
TAZ B
PExt SSs
PExt SSs
Prods
AExt SSs
AExt TEs
Ext B
PExt TEs
Prods
AExt SSs
a
24
Trip Table Estimation

• Since estimated truck trip tables are based on so
  many assumptions, need to check distribution
  results
• Create set of truck vehicle counts by use
  category using vehicle classification counts and
  a cross-classification of truck use category and
  FHWA truck class
• Use resultant trip table as seed for new gamma
  functions

Three
Five
Six
Seven
Eight
Nine
Ten
Eleven
Totals
Tankers
757
2,499
587
12
336
800
43
0
5,033
2.2
Household Goods
1,722
532
12
0
67
136
0
0
2,470
1.1
LTL/Truckload
60
943
185
0
1,027
1,066
64
58
3,404
1.5
Food Warehouse
7,956
5,056
834
0
865
1,242
12
12
15,978
7.1
Intermodal
0
0
0
0
386
326
0
0
711
0.3
Package
9,032
3,681
125
0
0
0
0
0
12,837
5.7
Heavy
7,403
19,215
4,744
850
1,107
2,342
423
0
36,085
16.1
Retail
19,970
1,636
12
0
48
106
0
0
21,772
9.7
Business PU/Van
125,174
1,348
0
0
0
0
0
0
126,521
56.3
TOTALS
172,073
34,910
6,498
862
3,836
6,019
543
70
224,812
25
Forecasting Future Truck Travel

• Apply truck trip generation model -- with future
  scenario employment, household, group quarters,
  and external station trip ends -- to estimate
  tour ends, starts and stops, and entrances/exits
• Apply gamma functions and productions and
  attractions for initial estimate of truck trip
  tables
• Apply trip table adjustment factors to produce
  future-year truck trip tables based upon
  future-year demographics and network
  characteristics

26
Summary

• Now our truck travel forecasting model is
  sensitive to changes in regional demographic
  characteristics, infrastructure, tolls, and the
  regional transportation system.

27
Contact Information

• Ian Harrington
• ianh_at_ctps.org
• Chief Transportation Planner
• David S. Kruse
• dkruse_at_ctps.org
• Central Transportation Planning Staff to the
  Boston Region Metropolitan Planning Organization
  (www.bostonmpo.org)