DEVELOPING A NEW CROSSCLASSIFICATION
Trucks dominate US transportation, driving most shipments. Having the right information about the types of trucks, how far they travel, and where they go helps to better plan for infrastructure projects. Agencies use regional travel models to look at truck flow and distribution in di erent areas. We’ve come up with a cross-classification for these models for more precise trip generation.
TRUCK TRIP GENERATION BY VEHICLE CLASSIFICATION ALLOWS MODELS TO:
Adapt truck categories, compatible across di erent data sources
Better account for two axle trucks with 8,500<GVWR<14,000 lbs
Factor trips from warehouses and logistics hubs more accurately
Validate with tra ic data or additional truck GPS info
Reliable and accurate estimation of emission and GHG
MODEL CHALLENGES
Warehouse trip generation rates are inconsistent between types of operation
Truck models use multiple data sources to estimate truck volumes. These data sources have di erent and complex classification schemes
Emission models using a weight-based classification system don’t align with real-world tra ic observations which are usually based on length or number of axles of the truck
Tinotenda Jonga | Fehr & Peers t.jonga@fehrandpeers.com
Fatemeh Ranaiefar Fehr & Peers f.ranaiefar@fehrandpeers.com
Kaveh Shabani | Cambridge Systematics, Inc. kshabani@camsys.com
STUDY GOALS
Create precise trip generation rates for di erent types of warehouses and logistics areas
Establish methods for converting between di erent truck classification systems
Improve calibration and validation of truck flows in regional travel demand models
FREIGHT WEIGHT & AXLE-BASED CLASS DISTRIBUTIONS
Source: National VIUS (2002)
There is significant overlap between axle and weight based classification especially for smaller trucks
THESE ARE NECESSARY TO ENSURE THAT TRIP GENERATION AND TRUCK CLASSIFICATION DATA WORK TOGETHER SEAMLESSLY WITHIN REGIONAL TRAVEL DEMAND MODELS
ITE has expanded the warehouse categories and respective sample size. However, the sample size for some of these categories and time periods are very limited.
Prologis International Park of Commerce (IPC) is an 1800-acre, fully entitled, master-planned park located in Tracy, California
LHDT: 8,500 lbs<GVWR<14,000 MHDT: 14,000 lbs >GVWR< 33,000 lbs HHDT: GVWR>33,000 lbs Au o LHDT MHDT HHDT 1 Moto c yc es 100 - -2 Pa seng er Ca r 100 - -3 Two- Ax e Fou - T e S ng e- U n T uc ks 89 14 8 84 1 99 0 03 4 Bu es - - -5 Two- Ax e S - T e S ng e- U n Truc k - 34 2 64 1 8 6 Three- Ax e S ng e- U n T uc ks - 3 2 25 3 71 5 7 Four o More Ax e S ng e- U n T u ks - - 3 97 8 Four o Fewe Ax e S ng e- T a er Truc ks - 27 6 4 7 67 7 9 F ve- A e S ng e- Tra e T uc ks - 0 1 2 5 97 4 10 S x o More A e S ng e- Tra e T uc ks - 9 1 2 2 88 7 11 F ve o Fewe Ax e Mu - T a ler T uc ks - - 5 1 94 9 12 13 S x o More A e Mu t - Tra e T u ks - - - 100 F HW A-13 Cla s s De i n t on Vehi c e C a s s Def n t on % ) WAREHOUSE TRIP GENERATION RATES CATEGORIZED BY TRUCK TYPE AT 70 DIFFERENT FACILITIES TE 150 W a ehou ng 1 Ed 1 1 0 6 1 71 0 1 0 06 0 2 0 17 0 0 23 TE 154 H h- Cub e T a ns oa d a nd ho t term s o a g e wa ehouse 1 Ed 1 8 0 22 1 4 0 1 0 01 0 1 0 15 0 0 17 TE 155 H h- Cub e Fu men Cen e - N on- So ng 1 Ed 1 8 0 23 1 81 - - 0 2 27 TE 155 H h- Cub e Fu men Cen e - So t ng 1 Ed 6 5 0 19 6 44 - - - - -TE 156 H h- Cub e Pa c e hub w ehouse 1 Ed 4 5 0 58 4 63 0 8 71 TE 156 H g h- Cub e Co d to a g 1 Ed 1 7 0 75 2 12 - - - - -TE 150 W a ehou ng 1 Ed - - - - - 1 74 - - - - 0 2 - - - - 24 TE 154 H h- Cub e T a ns oa d 1 Ed - - - - - 1 4 - - - - 0 1 - - - - 16 TE 155 H h- Cub e Fu men 1 Ed - - - - - 1 81 - - - - 0 1 - - - - 16 TE 152 H h- Cub e W a ehou e Ed - - - - - 1 68 - - - - 0 1 - - - - 16 T ucks Autos Truck Tota W a ehous ng T p Ra e Com par s on Tr p a e pe 1000 s quare oo ) Data Da y AM Peak Hour PM Peak Hour Au os To al Autos Trucks Tota HISTORY OF WAREHOUSE TRIP GENERATION RATES IN THE ITE MANUAL Medium Heav y Med um Heav y Med um Heav y Truck T ucks Trucks Truck Trucks Trucks June 2 19 Count 0 2 1 15 0 1 12 0 4 0 1 A 39 Bu d ng 1 0 08 0 45 1 52 15 0 1 0 0 0 18 0 18 0 02 0 2 C y o T a c y On 1 6 0 07 0 62 2 14 24 0 1 0 0 0 29 0 28 0 03 0 3 PC & Pa e son Pa s On y 1 9 0 07 8 2 0 13 0 1 0 0 0 19 0 17 01 0 3 0 2 PC On y 1 2 0 09 0 36 1 5 15 0 2 0 02 0 19 0 18 01 0 2 0 2 P C Onl co mpar ed o June 20 9 Co unt 21% 36% 54% 52% 3 % 36% W arehous ng Tr p Rate Com pa on Da a Da y AM Peak Hour PM Peak Hou Au os Tota Autos Tota Au os 96% 42% 46% Tota June 201 Coun s a 8 Bu d ng s a w h n a ound he nt rna t ona Pa k o Comme PC 23 0 03 02 June 2 21 Count a 9 Bu d ng s c os Sa n oa q u n Count nc ud ng 5 b u d ng om June 2 19 c oun s
FHWA TRUCK CLASSIFICATION EPA TRUCK CLASSIFICATION EXAMPLES FROM INDUSTRY
CONTACTS:
Tinotenda Jonga | Fehr & Peers | t.jonga@fehrandpeers.com
Fatemeh Ranaiefar | Fehr & Peers | f.ranaiefar@fehrandpeers.com
Kaveh Shabani | Cambridge Systematics, Inc. | kshabani@camsys.com
TRUCK CLASSIFICATION SCHEMES
Da ta Veh i cle Cla s s es
FH W A 8 v ehic le c la s s es for GV W R > 6,000
Notes
Sta tes a nd FH W A a ls o us e GV W R for v ehic le s ize a nd weig ht limits for roa d wa y s a nd b rid g es monitoring
• To develop crosswalks, a data source that captures both GVWR and number of axles is needed.
• Vehicles with di erent weight characteristics can have a similar number of axles, so distinguishing between classes is not trivial.
EPA
Lig ht- Duty (GV W R < 8,500 lb s .)
H ea v y - Duty (GV W R > 8,500 lb s .)
I n the Env ironmenta l Protec tion Ag enc y d a ta , within the hea v yd uty c la s s , there is a med ium- d uty d ies el eng ine c la s s
• Truck classes are used in various steps of the travel demand model (trip generation, trip distribution, composite cost function).
V I U S
Da ta a re s umma rized b a s ed on a v era g e GV W R a nd numb er of a xles . The exp a ns ions of V I U S is d one us ing GV W R from v ehic le reg is tra tion d a ta
The V ehic le I nv entory a nd U s e Surv ey p rov id es d a ta on the p hy s ic a l a nd op era tiona l c ha ra c teris tic s of the U .S. c ommerc ia l truc k p op ula tion
• Emission models such as EMFAC or MOVES use emission factors specific to each truck GVWR class
W I M W heel (s ing le or d ua l tires ) loa d s , a xles loa d s , a nd GV W R d a ta
GPS Da ta Cla s s es b a s ed on a g g reg a ted GV W R c a teg ories
W eig ht- I n- Motion is a p rima ry tec hnolog y us ed for monitoring v ehic le weig hts a nd a xle loa d s on roa d wa y s
The GPS d a ta p rov id ed b y on- b oa rd telema tic s d ev ic es inc lud es truc k weig ht b a s ed on GV W R d ec od ed from v ehic les V I N numb ers
CONTACTS:
Tinotenda Jonga | Fehr & Peers | t.jonga@fehrandpeers.com
Fatemeh Ranaiefar | Fehr & Peers | f.ranaiefar@fehrandpeers.com
Kaveh Shabani | Cambridge Systematics, Inc. | kshabani@camsys.com