Commercial Vehicles and Trucks

Introduction

Commercial vehicles and trucks contribute significantly to congestion on major facilities in an urban area. In most instances, their travel behavior is distinct from residents of that urban area. To better capture commercial vehicle traffic in TRMG2, a separate set of commercial vehicle models were developed. These include trip generation, time of day, and distribution for three commercial vehicle types: commercial autos, vans, and pickups (CV), single unit trucks (SUT), and multi-unit trucks (MUT).

These classes are defined using the federal vehicle classification.

CV - Classes 1-3
SUT - Classes 5-7
MUT - Classes 8-13

The models use the Quick Response Freight Manual (QRFM) approach and are re-estimated when possible using the Triangle’s 2010 Commercial Vehicle survey.

Trip Rates

Initial estimation attempts led to counter-intuitive coefficeints and poor model fit statistics. A fundamental problem may have been regressing a 2010 survey against 2016 land use data. In addition, stakeholders noted some concerns with the survey. Given these issues, initial rates were borrowed from the New River Valley MPO travel model.

Variable	CV	SUT	MUT
Industry	1.00	0.260	0.135
Retail	0.89	0.253	0.065
Office	0.44	0.068	0.009
Service_RateLow	0.44	0.068	0.009
Service_RateHigh	0.44	0.068	0.009
HH	0.25	0.099	0.038

The initial rates were adjusted by comparing link flows to counts where they were available by SUT and MUT. Commercial vehicles used the same adjustment factor as SUT. The final rates are shown below.

Variable	CV	SUT	MUT
Industry	0.870	0.226	0.100
Retail	0.774	0.220	0.048
Office	0.383	0.059	0.007
Service_RateLow	0.383	0.059	0.007
Service_RateHigh	0.383	0.059	0.007
HH	0.218	0.086	0.028

Time of Day

The 2010 survey included trip departure time, which was used to categorize trips by time period. The table below shows the estimated time of day factors (time of day definitions).

Vehicle Type	AM	MD	PM	NT
CV	0.141	0.452	0.075	0.331
SUT	0.216	0.444	0.035	0.306
MUT	0.193	0.393	0.037	0.378

The relative distribution between peak and off-peak periods look reasonable, but the distribution between AM and PM peaks are not. There is almost no traffic in the PM period and far too much in the AM. This skew looks worse considering that the PM period is longer than the AM. Based on experience in other regions, Caliper spread peak demand evenly over the AM and PM periods according to the hours in each period. The final table is shown below.

Vehicle Type	AM	MD	PM	NT
CV	0.091	0.452	0.125	0.331
SUT	0.105	0.444	0.145	0.306
MUT	0.097	0.393	0.133	0.378

Directionality factors are not calculated for commercial vehicles and trucks. Instead, they are assumed to be evenly split by direction.

Distribution

Once generated, commercial vehicle and truck trips are distributed among zones using a gravity model. Unfortunately, the CV survey did not contain information on both ends of the trip, which meant it could not be used to estimate model parameters. Model parameters were borrowed from the NRVMPO travel model and are shown below.

Class	Constraint	a	b	c
CV	Production	5	1.00	0.1
SUT	Production	5	0.75	0.1
MUT	Production	5	0.60	0.1

The table below shows the resulting average commercial vehicle trip lengths in the model.

Class	Average Time (min)	Averge Distance (mi)
CV	10.0	7.1
SUT	12.0	8.9
MUT	13.3	10.1

The charts below show the trip length frequency distribution graphs (in miles).