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An Integrated Tour-based Truck Travel Forecasting Model Ian Harrington Central Transportation Planning Staff Boston, Massachusetts Outline of Presentation Why prepare a new truck model? Identifying available data Trip generation model structure Trip distribution model structure

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An integrated tour based truck travel forecasting model l.jpg

An Integrated Tour-basedTruck Travel Forecasting Model

Ian Harrington

Central Transportation Planning Staff

Boston, Massachusetts


Outline of presentation l.jpg
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


Why prepare a new truck model l.jpg
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


Data available for truck travel forecasts l.jpg
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


Trip generation model structure l.jpg
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


Trip generation model structure6 l.jpg
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


Regional truck tour ends l.jpg
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


Regional truck tour ends8 l.jpg
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


Regional truck tour ends9 l.jpg
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%


Regional truck tour ends10 l.jpg
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%


Regional truck tour ends11 l.jpg
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


Intermediate starts and stops l.jpg
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


Intermediate starts and stops13 l.jpg
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


Intermediate starts and stops14 l.jpg
Intermediate Starts and Stops

Supply of intermediate starts and stops based on operational data:

S&S = 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


Intermediate starts and stops15 l.jpg
Intermediate Starts and Stops

Intraregional truck tour starts and stops:

Intra S&S = 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%


Intermediate starts and stops16 l.jpg
Intermediate Starts and Stops

Regional truck interregional tour

starts and stops:

Reg IX S&S = Tour Ends/2 * % Tours Ext

* Stops/Tour

Assume interregional tours have one-half the number of stops per tour within region


Intermediate starts and stops17 l.jpg
Intermediate Starts and Stops

External truck intermediate starts and stops:

Ext S&S = Total S&S – Intra S&S

– Local IX S&S


Regional truck entrances exits l.jpg
Regional Truck Entrances/Exits

Regional truck interregional tour external tour ends:

Reg IX Ext TE = 2 * Reg IX S&S

Stops/Tour

Assume interregional tours have one half the number of stops per tour within region


External truck entrances exits l.jpg
External Truck Entrances/Exits

External truck tour ends

Ext TE = 2 * Ext S&S

Stops/Tour

Assume interregional tours have one-half the number of stops per tour within region


Through truck entrances exits l.jpg
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


Truck trip distribution l.jpg
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


Truck trip distribution22 l.jpg
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

P:Local Reg TEs

Prods

A:Local Reg S&Ss

Ext A

Prods

TAZ B

P:Local Reg S&Ss

P:Local Reg S&Ss

Prods

A:Local Reg TEs

A:Local Reg S&Ss

Ext B

P:Thru TEs

Prods

A:Thru TEs

a


Truck trip distribution23 l.jpg
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

P:Reg IX S&Ss

P:Reg IX S&Ss

Prods

A:Reg IX Ext S&Ss

A:Reg IX Ext TEs

P:Reg IX Ext TEs

Ext A

A:Reg IX S&Ss

Prods

TAZ B

P:Ext S&Ss

P:Ext S&Ss

Prods

A:Ext S&Ss

A:Ext TEs

Ext B

P:Ext TEs

Prods

A:Ext S&Ss

a


Trip table estimation l.jpg
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


Forecasting future truck travel l.jpg
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


Summary l.jpg
Summary

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


Contact information l.jpg
Contact Information

Ian Harrington

[email protected]

Chief Transportation Planner

David S. Kruse

[email protected]

Central Transportation Planning Staff to the Boston Region Metropolitan Planning Organization (www.bostonmpo.org)


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