California Vehicle Inventory and Use Survey - Transportation ...

Jeong, Tok, Ritchie, and Park

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California Vehicle Inventory and Use Survey: Pilot Study Insights Kyungsoo Jeong Ph.D. Candidate Department of Civil and Environmental Engineering and Institute of Transportation Studies University of California Irvine, CA, USA, 92697 [email protected] (Corresponding author) Andre Tok Assistant Project Scientist Institute of Transportation Studies University of California Irvine, CA, USA, 92697 [email protected] Stephen G. Ritchie, Ph.D. Professor Department of Civil and Environmental Engineering and Institute of Transportation Studies University of California, Irvine Irvine, CA, USA, 92697 [email protected] Junhyeong Park Ph.D. Candidate Department of Civil and Environmental Engineering and Institute of Transportation Studies University of California Irvine, CA, USA, 92697 [email protected] Word Count: 5,500 Tables and Figures: 4 Tables + 4 Figures = 2,000 Total Word Count: 7,500

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ABSTRACT

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With the discontinuation of the national Vehicle Inventory and Use Survey (VIUS) in the U.S. in 2002, there has been insufficient data available for well over a decade on commercial vehicle activity. The goal of this pilot survey effort was to develop a preliminary design for a proposed California Vehicle Inventory and Use Survey (Cal-VIUS), and to test it with a scaled-down sample to provide guidance on the full-scale survey design. The sample was drawn from vehicle records obtained from the California Department of Motor Vehicles (DMV) and International Registration Plan (IRP) datasets using a stratified sampling technique to capture intrastate and interstate commercial vehicle activity in California. Limitations identified in the 2002 VIUS were addressed in the Cal-VIUS pilot survey questionnaire, which was administered on an online survey platform. The survey was designed to collect annual and trip-based activity data through two complementary surveys – a webbased Fleet Manager Survey, followed by an app-based Driver Survey. These were conducted between December 29, 2014 and February 28, 2015 and between February 24 and February 26, 2015, respectively. Results from the Fleet Manager Survey showed that the stratification design was adequate to describe the heterogeneous characteristics of vehicle activities between strata with respect to vehicle miles traveled within California. The pilot survey results are expected to provide valuable insights to those developing future truck-related survey studies.

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Keywords: Vehicle Inventory and Use Survey (VIUS), California truck activity, Survey design, Web-based Survey.

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INTRODUCTION

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Commercial vehicles are used for a wide spectrum of purposes such as goods and equipment movement, construction, and service functions, to name just a few. Despite their obvious benefits to economic growth, their activities have a significant impact on road infrastructure, traffic operations, and the environment. Hence, it is essential to be able to quantify their impacts at the regional and national level. One approach is to understand the population attributes of commercial vehicles, their operational characteristics, and the relationship between their movements and impacts. Agencies in California, for example, have undertaken a number of efforts for the development of regional and statewide models related to commercial vehicles including freight forecasting, emission estimation and energy demand models (1,2, 3). However, the lack of current and relevant data on commercial vehicle activity has been identified as a significant limitation in these research efforts.

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In the U.S., Vehicle Inventory and Use Survey (VIUS) was conducted by the U.S. Census Bureau to collect data on the physical and operational characteristics of the nation's truck population from 1963, and thereafter quinquennially from 1967 until 2002 (4). The most recent 2002 VIUS data have been used to provide essential estimates and values to a number of freight and truck studies at the state-level in California, as for other states and regions in the US. However, major limitations and concerns have been identified regarding the use of this data. Since the last VIUS was conducted well over a decade ago, there is significant concern with the relevance of the data in representing the existing U.S. truck fleet, given the time elapsed. Further confounding this concern is the significant chain of economic and industrial events that have impacted the trucking industry during this span of time. In addition, further analysis of VIUS data has revealed significant limitations for use at the state level. For example, the sample responses that can be associated with activity within California are biased towards mostly in-state commercial vehicles with at least half of their annual vehicle miles traveled (VMT) performed within California. No information on California-related activity can be obtained for commercial vehicles that perform less than half of their annual VMT within California. In addition, the sample size for California is not sufficient to represent the California truck population, resulting in a very small number of valid responses for some truck body classes (e.g. van-open top, tank-dry bulk, and etc.). Finally, the 2002 VIUS requested only the typical trailer configuration pulled by tractors. Hence, trucks that pull several different trailer types over the course of a year would only report the most common one, and responses relating to various commodities hauled by the truck would be inaccurately associated with only the "typical" trailer type. Because of these limitations, the current distinct characteristics of California commercial vehicles cannot be accurately and precisely estimated from the sampling framework of the 2002 VIUS.

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Despite the pressing need for data on the population and characteristics of commercial vehicles that have operations within the State of California, no effort has been made to date to update or address the identified inadequacies of VIUS for the state. Current data collection methodologies such as vehicle classification using Weigh-In-Motion (WIM) data and regional surveys have been able to partially address these specific needs. Efforts have been made to estimate the California truck population and its usage by truck type and associated purpose using available datasets such as the 2002 VIUS, intercept surveys, as well as other sources (2, 5). However, there are concerns relating to these estimates due to their dependency on the 2002 VIUS results. Hence, the upcoming California Vehicle Inventory and Use Survey (Cal-VIUS) study is planned to be a timely replacement and enhancement of the 2002 VIUS for California and to directly address the current needs of commercial vehicle-related research.


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The primary goal of this study was to develop a preliminary design for Cal-VIUS together with a pilot implementation of a web-based survey platform to evaluate the survey design and instrument.

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LITERATURE REVIEW

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Mail-out-mail-back and intercept interview survey methods have been widely adopted to collect data on commercial vehicles at state or national levels. The 2002 VIUS surveyed approximately 136,000 trucks from a total of nearly 89 million trucks registered in the United States via mail-out-mail-back surveys (4). The State of California was represented as one of the geographic strata in this survey, with a sample size of 3,212 trucks selected from a vehicle registration list comprising five truck types: 1) pickups; 2) minivans, other light vans, and sport utilities; 3) light single-unit trucks (Gross Vehicle Weight (GVW) < 26,000 lb); 4) heavy single-unit trucks (GVW ≥ 26,000 lb); and 5) truck-tractors. The response rate for this survey was approximately 74.5%, which is extremely high for a mail-outmail-back survey. This high response rate was likely attributable to the mandatory response requirement.

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The Canadian Vehicle Survey was conducted from 1999 to 2009, and targeted all motor vehicles including commercial vehicles by using a computer assisted telephone interview and mailout-mail-back survey at quarterly intervals (6). The population was initially partitioned into 78 strata using a two-stage sampling design according to vehicle type, jurisdiction, and vehicle age. In the second stage, samples were selected from each stratum using a systematic sampling approach based on registration address to avoid over-burdening respondents with multiple vehicles. However, this survey has been discontinued and is currently replaced by automated on-board data collection devices that archive truck data directly from vehicles (7).

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The State of California has invested significant effort in collecting commercial vehicle activity data through intercept surveys. The California Air Resources Board (CARB) and California Department of Transportation (Caltrans) have conducted in-person interview surveys with truck drivers at weigh stations, state inspection facilities and roadside rest areas to collect current trip information for medium or heavy-duty trucks (8,9). These studies primarily focused on inter-regional and local trips within California. To fill the data gap for interstate truck characteristics within California, Lutsey (10) collected data from 433 randomly selected truck drivers at seven different inspection stations along the California border.

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Clark, et al (11) conducted an intercept and interview survey to obtain origin-destination and associated characteristics of freight trucks which had operations in the State of Washington. This survey gathered data seasonally at 27 weigh stations during a four-week period during each season spanning April 2002 to January 2003. A systematic site selection approach was adopted to avoid interviewing the same vehicles during the same day. On average, 6,000 trucks per month were randomly selected. Although this intercept survey for heavy-duty or interstate trucks can partially capture estimates of truck operations for a specific day, the resulting statistics are not easily generalizable to the state and annual level because the targeted population changes with time and location, and the total sample size was very small. In addition, the effort required to determine the appropriate survey locations to effectively capture the cross-section of intrastate and interstate trucks operating within the state is a non-trivial task.


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The Oregon Department of Transportation conducted pilot studies to test data collection methods for the truck population in the Portland metropolitan area, which facilitated the comparison of response rates between data collection methods as well as across the questions, and evaluated the accuracy of the data collected (12). The study performed two pilot studies: an intercept and interview survey for inter-regional freight movements and a combination of mail and fax surveys for intraregional freight movements. In the intercept and interview survey, the survey was tested for a selected day at three locations comprising a weigh station, a port, and a warehouse in the region of Portland. The second pilot survey was designed to compare contact methods using mail and fax, and sampling frames.

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SURVEY DESIGN

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A series of systematic steps in the survey process were conducted to develop a draft survey for the Cal-VIUS study, using the available resources.

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Defining the target population and sampling frame

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For the purpose of the full-scale Cal-VIUS, the target population was determined as commercial vehicles with GVW above 8,500 lbs. with operations in California, except for ambulances, buses, motor homes, farm tractors, and unpowered trailer units. This target population is composed of three categories: 1) commercial vehicles registered and operated only in California, 2) commercial vehicles registered in California with operations in and out of California, and 3) commercial vehicles registered out of California, but with some or all of their operations in California.

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Although the 2002 VIUS was designed to collect data at the national level with a sampling frame that included the above categories, its questionnaire design prevented a clear identification of vehicles in the last two categories. As a result, it is not possible to estimate population VMT at the state level from VIUS. This is because state-level VMT could only be obtained from vehicles that reported a home base (where they performed 50% or more of their annual VMT). Hence, the portion of VMT operated in California that is contributed by vehicles with no home base (typically long haul commercial vehicles) or with a different home base, cannot be obtained. To address this data gap, the present study utilized two vehicle registration lists – data from the California Department of Motor Vehicle (DMV) and the International Registration Plan (IRP) – to define a sampling frame. These databases are not publically available. However, the CARB was able to provide the research team with anonymized versions of these datasets.

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The DMV dataset contains a list of vehicles registered in California that were not registered with the IRP. This dataset primarily represents commercial vehicles registered and operated only in California. This dataset includes physical information such as body type, fuel type, model year, GVW class, and etc. as well as anonymized vehicle identification information. Vehicles with operations in and out of California were generally represented by the IRP dataset. The IRP is a registration program between the U.S. (with the exception of Oklahoma) and Canada to allocate registration fees to jurisdictions where vehicles are operated. A fleet from a participating jurisdiction that possesses vehicles with GVW above 26,000 lbs. or three or more axles that operate interstate must be registered under IRP. However, fleets comprising only vehicles with two axles with GVW 26,000 lbs. or less are not required to register with the IRP (13). Commercial vehicles whose fleet declared operations in California were retrieved from the IRP data. In addition to fleet information such as fleet ID, fleet address, and fleet travel miles, the IRP dataset also includes information such as vehicle type, model year, and GVW for each vehicle.


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Although the sampling frame defined by these data sets provides near complete coverage of the vehicles of interest in this survey, there exists three deficiencies. The first concern is the inability to identify specific vehicles within the IRP dataset with actually travel within California. This is because California operations are only reported at the fleet level. Hence, some vehicles within a fleet with reported travel in California may not have actually traveled within the state. Although these vehicles are outside of the target population, there is no way to exclude them from the IRP dataset. The second deficiency is incompleteness because some truck populations could not be captured using the defined sampling frame. This is because two registration states – the State of Oregon and Oklahoma – were not represented in the IRP dataset. Electronic files from Oregon did not exist in 2013, and Oklahoma does not participate in the IRP. In addition, vehicles registered in Canada were excluded from the sampling frame because of very low expected response rates and logistical issues associated with conducting the survey. Finally, there were concerns associated with the timeliness of the datasets. Although the target year of the survey was 2014, the dataset was obtained from 2013 database records. Hence, the dataset also contains a subset of vehicle records whose vehicle possession or registration with IRP changed in 2014. Despite these concerns, it was concluded that these two truck registration datasets were the best available to construct the sampling frame, because of the limited alternatives available.

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Sample design for the pilot study

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For the pilot study, sample design focused on the population of commercial vehicles with GVW above 26,000 lbs. that had some or all of their operations within California. There were several reasons for deciding on the 26,000 GVW threshold. It was assumed that some of these vehicles were associated with long-haul freight movements, which is of particular interest. However, long-haul vehicle activities within California were not properly captured from the 2002 VIUS. Another concern is that fleets comprising only vehicles with 2 axles and GVW less than 26,000 lbs. are not required to register with IRP, even if they travel outside their home jurisdiction. Hence, it is not possible to capture this subset of vehicles from the IRP dataset.

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The population defined for the pilot study was categorized into non-overlapping strata using a stratified random sampling technique to maximize between-strata variation and minimize withinstrata variation in terms of vehicle activity performed within California (e.g. VMT). Vehicle type was assumed to be related to vehicle activity, which has been utilized for stratification in the VIUS. Hence, the sub population of DMV registered vehicles was first divided into single-unit (all single chassis trucks), tractor and construction (vehicles whose body type is concrete mixer, crane and dump), with the single-unit vehicles subsequently stratified into vehicles registered in urban and rural regions. Due to its distinct data structure, a different set of criteria was adopted in the stratification design for IRP. One assumption was that the fleet size may be related to the operational characteristics of commercial vehicles that have operations within California. According to the CARB’s Truck and Bus Regulation Small Fleet Option (14), fleets with less than four vehicles were considered small fleets. The rest were divided into large fleets whose fleet size was between 4 and 200, and very large fleets with over 200 vehicles. For small and large fleets, tractors registered in California and nearby states – Washington, Arizona, and Nevada – were selected in this pilot study. Single-unit vehicles were excluded from their population because of their relatively small population, and vehicles registered in the remainder of the U.S. were ruled out because of anticipated low response. Since very large fleets can be assumed to have very distinct operational characteristics, all vehicles within such fleets were included in that stratum.

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The design of the seven strata is summarized in Table 1. A minimum sample size of 30 per stratum was chosen for statistical significance, resulting in a total target sample size of 210. A 5%


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response rate was initially assumed for the DMV sub-population. For the IRP sub-population, a reduced response rate of 2.5% was assumed to account for a reduced obligation for out-of-state firms, a higher incidence of surveying vehicles with no travel activity in California, and a higher likelihood for encountering long haul truck owner operators that may not receive surveys promptly due to their longer travels. The recruitment size by stratum was calculated as the required sample size divided by the estimated response rate. This resulted in a total recruitment size of 6,000 vehicles drawn from the stratified population.

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Table 1. Sample Design for the Pilot Study

Strata

DMV

IRP

1

Single Unit in Urban Single Unit in Rural Tractor Construction 2 Small Fleet Tractor in CA, NB 2 Large Fleet Tractor in CA, NB Very Large Fleet Tractor & Single Unit Total

# Population 30,240 11,282 92,552 29,507 24,866 40,804 526,548 755,799

Required Estimated Sample Response Size Rate (%) 30 5.0% 30 5.0% 30 5.0% 30 5.0% 30 2.5% 30 2.5% 30 2.5% 210

Recruitment Size 600 600 600 600 1,200 1,200 1,200 6,000

1. Vehicles in all strata have GVW ≥ 26,000 lbs. 2. CA = California, NB = neighboring states including the state of Washington, Arizona, and Nevada.

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Note:

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Data collection method and survey instrument design

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A mail-out and online survey data collection method was proposed for this study. A cover letter was mailed out to each business address associated with the sampled vehicles, with a request for the vehicle owner or fleet manager to access and complete the survey online. This method provided several cost savings over the traditional mail-out-mail-back method, as it eliminated the requirement to mail back the completed survey, and the mail-out consisted of only the cover letter – not the full survey packet. In addition, the respondent was not burdened with returning the survey packet, further simplifying survey logistics. The online survey platform was also expected to enhance survey completion rates and response errors with the use of design logic, as respondents do not have to manually navigate through sections within the questionnaire to complete questions that are relevant to them.

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Two types of online surveys were implemented in the pilot study in an attempt to obtain more accurate and comprehensive vehicle activity data: a web-based Fleet Manager Survey, and a smartphone app-based Driver Survey (with web-based option). The Fleet Manager Survey was designed to be completed by the fleet manager or owner of the vehicle. The purpose of this survey was to obtain information about the fleet and vehicle characteristics as well as a summary of operational activities in the year 2014, for each sampled vehicle in the fleet. For sampled vehicles that shared the same mailing address, the list of vehicles was presented within a single cover letter. This approach was preferred over sending multiple letters to the same address as it would have involved a higher cost, and might have been construed as spam mail.


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The Driver Survey was designed to be completed by the driver or operator of the vehicle(s) via a smartphone or web browser. The driver was recruited via an email address provided through the Fleet Manager Survey. Therefore, the sampled vehicles for the two surveys are identical. However, since only a fraction of respondents to the Fleet Manager Survey were expected to provide the vehicle driver’s email address, only part of the sample could be reached for the Driver Survey out of all the Fleet Manager Surveys completed. The purpose of the Driver Survey was to obtain a 3-day diary of trip activities within California and neighboring states. Figure 1 shows the process of the data collection method for this study.

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Figure 1. Cal-‐VIUS survey process for pilot study

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The survey questions were generally based on the 2002 VIUS. However, some existing questions were modified to address limitations identified with the 2002 VIUS questionnaire. In addition, new questions were also added to provide additional information that was of interest to California state agencies.

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The Fleet Manager Survey collected preliminary information (e.g. IRP registration, primary location, and etc.), vehicle physical characteristics, vehicle operational characteristics, vehicle annual activity and a request for participating in the Driver Survey. The length of survey varied according to the responses obtained due to its underlying logical structure, up to a maximum possible number of 55 questions. The Driver Survey was designed to obtain vehicle activity and associated information at a starting location and the following stop locations (e.g. odometer reading, commodity type, and etc.).

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The total recruitment of 6,000 vehicles was aggregated by fleet resulting in 4,405 cover letters. The cover letter template was composed in English with an attached Spanish translation, and provided instructions to complete the survey. The initial mail-out of the Fleet Manager Survey cover


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letter was made on December 26, 2014, followed by a reminder letter on February 15, 2015. Responses for the Fleet Manager Survey were received between December 29, 2014 and February 28, 2015. The driver portion of the survey was conducted between February 24 and February 26, 2015. Financial incentives were offered to a limited number of respondents, on a first-come-first served basis, as follows:

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• Incomplete Fleet Manager Survey with non-operation within California: $4 • Completed Fleet Manager Survey with incomplete Driver Survey: $6 • Completed Fleet Manager Survey with completed Driver Survey: $10 for each respondent

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PILOT SURVEY RESULTS

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Summary of survey responses

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A total of 158 responses was obtained from the Fleet Manager Survey, representing 2.6 % of the recruitment sample. Among them, completed surveys for 123 vehicles were obtained. The response rates for the completed survey by stratum were lower than the estimated response rates assumed in the pilot sample design, as shown in Table 2. However, the response rates in the DMV strata were higher than ones in the IRP strata, as anticipated.

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Table 2. Pilot study summary of responses and response rates

Dropped-‐ Disposed Out Responses before 2014

DMV

Strata1

IRP

Not Operated in CA

Operated in CA

Single Unit in Urban

3

2

2

17

Single Unit in Rural

10

9

4

15

Tractor

5

10

1

8

Construction

6

2

0

12

2

4

2

1

5

2

5

3

8

8

2

1

9

4

35

29

25

69

Small Fleet Tractor in CA, NB

Large Fleet Tractor in CA, NB Very Large Fleet Tractor & Single Unit Total

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Completed Responses

Note:

Sub-‐total (Resp. rate)

21 (3.5%) 28 (4.7%) 19 (3.2%) 14 (2.3%) 8 (0.7%) 19 (1.6%) 14 (1.2%) 3 123 (2.1%)

Total Responses (Resp. rate)

24 (4.0%) 38 (6.3%) 24 (4.0%) 20 (3.3%) 12 (1.0%) 24 (2.0%) 16 (1.3%) 158 (2.6)

1. Vehicles in all strata have GVW ≥ 26,000 lbs. 2. CA = California, NB = neighboring states including the state of Washington, Arizona, and Nevada. 3. A total of 78 fleet managers qualified financial incentives.


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Completed responses for the possession and operation of vehicles during 2014 were categorized into three types: 1) disposed before 2014, 2) not operated in California during 2014 and 3) operated in California during 2014. 69 respondents reported that their vehicle operated within California during 2014. Of these respondents, 16 provided the driver’s email of the targeted vehicle for the Driver Survey. Although three truck drivers took the survey, all reported driving their vehicles outside California during the specified data collection period. Therefore, vehicle activities at the triplevel and the Driver Survey instrument could not be tested from the pilot study.

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Figure 2 represents the timeline of completed responses from the Fleet Manager Survey spanning the survey period. While 38 surveys were completed from initial mail-out date to February 16, 85 surveys were collected after the reminder was mailed out. This showed that the year-end and holiday period likely had a negative impact on the initial response rate and the reminder played a significant role in increasing the response rate.

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Figure 2. Response timeline for the completed responses

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Analysis of vehicle activity

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In this analysis, vehicle activities were grouped into two main categories – operated only within California and operated within and outside California. shows the distribution of general vehicle configurations observed from 69 vehicles by operation type. Of the 50 vehicles observed in operation only within California, 88% were single unit trucks, followed by tractors without a sleeper cabin. On the other hand, tractors with a sleeper cabin were the most frequent vehicle configuration (63%) involved in operation within and outside California, compared to single unit trucks (26%) and tractors without a sleeper cabin (10%). Also, none of the tractors with sleeper cabins were reported to have activity only within California. Hence, it can be inferred that tractor-trailers with a sleeper cabin are more likely to be associated with long-haul operations. More significantly, recent deployment of the


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Truck Activity Monitoring System (TAMS) in the California San Joaquin Valley (15), using truck classifications developed by Hernandez et al. (16) with the ability to distinguish tractors with and without sleeper cabs, can be used to observe interstate truck travel along major truck corridors.

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Table 3. Summary of VMT and Working Days by Operation Type

CA & US

CA Only

Categories

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Single Unit in Urban Single Unit in Rural Tractor Construction Single Unit in Urban Small Fleet Tractor in 2 CA, NB Large Fleet Tractor in 2 CA, NB Very Large Fleet Tractor & Single Unit Overall

Note:

# Valid Resp.

U.S. VMT

California VMT (miles//year)

Est. Daily Traveled Miles Working Days (miles/day) 3 3 Mean s.d. Mean s.d. 67 52 177 112 116 58 200 101 109 73 204 84 98 58 121 105 114 14 308 81

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(miles/year) 3 Mean s.d. 15,738 18,831 26,835 17,811 24,458 21,379 13,685 16,917 41,000 12,728

Mean 15,738 26,835 24,458 13,685 35,500

s.d. 18,831 17,811 21,379 16,917 13,435

3

86,667

23,094

25,500

17,543

255

45

110

85

6

75,567

49,726

16,410

20,568

223

122

51

51

3

84,354

7,541

2,716

2,168

278

66

10

10

50

35,197

34,831

19,310

18,385

132

93

151

111

3

1. Vehicles in all strata have GVRW ≥ 26,000 lbs. 2. CA = California, NB = neighboring states including the state of Washington, Arizona, and Nevada. 3. s.d. = standard deviation

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Figure 3. Comparison of vehicle configurations by operation type

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To address the data gap of truck VMT within California in the 2002 VIUS, the Cal-VIUS pilot survey was designed to estimate total annual miles driven both in the U.S and in California, for


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those sampled vehicles driven in California during 2014. 50 valid responses were used in this analysis after excluding outlier data with infeasible values.

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VMT characteristics in the U.S. and California are organized by the operation type and survey strata as shown in . Daily traveled miles within California were estimated using the reported annual VMT and working days within California. From the vehicles that only operated within California, it is observed that tractors generally had the highest annual VMT and daily traveled miles, while construction vehicles had the lowest annual VMT and daily traveled miles. It should be noted that this survey did not distinguish highway miles from off-road miles for the reported VMT. Singleunit vehicles with GVW over 26,000 lbs. registered in rural areas were driven more than those registered in urban areas. As expected, tractors that were operated within and outside California had much higher annual VMT than tractors operated only within California. Although tractors operated within and outside California had relatively lower annual VMT in California, they had higher average daily traveled miles. It should be noted that VMTs for tractors in small and large fleets for the IRP population were collected from vehicles registered in California and neighboring states. If all vehicles in the U.S. are targeted in the full-scale survey, the VMT within California is expected to be lower than the observed responses from the pilot survey. Finally, it is observed that vehicles belonging to very large fleets had much lower miles within California, which shows that this stratum has unique operational characteristic, so that it was appropriate to consider it as a separate group in the sample design.

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The results obtained from the pilot survey were compared with the California portion of the 2002 VIUS. For comparison, vehicles that had GVW exceeding 26,000 lbs. and a home base in California were used, in line with the target population for the pilot survey. Vehicles which were registered in California and reported 100 % for their percent of VMT within the home base state were categorized as “Operated only within California”. On the other hand, it was assumed that vehicles which were registered in California or neighboring states and traveled outside the home base state were identified as “Operated within and outside California”. The records were further partitioned by vehicle and body type information. Since urban and rural truck registration locations could not be distinguished from the 2002 VIUS, these two strata defined for single-unit trucks were aggregated into a single stratum representing all single unit trucks that only operated in California for this comparative analysis. In addition, small fleet and large fleet groups that operated within and outside California were combined to represent tractors with operation within and outside California as a single stratum. When the strata were combined, the weighted mean of VMTs was computed based on the population sizes. Table 4 shows that the VMTs within California from the pilot study were lower than these from the 2002 VIUS. For tractors operated within and outside California, the VMT in the U.S from the pilot study was slightly higher than the 2002 VIUS. However, reported VMT in California was lower from the samples in the Cal-VIUS pilot study. This is likely because the sample from 2002 VIUS reported as their home base (indicating that at least half of their VMT was performed in California), while the samples from the Cal-VIUS pilot study were registered in California, Nevada, Arizona and Washington, and did not have the home base requirement. This analysis illustrates the significant bias in using the 2002 VIUS to estimate state-level VMT due its inability to capture state VMT from vehicles with no home base or home bases in other states.


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Table 4. Comparison of Average Annual VMTs from the 2002 VIUS and Cal-‐VIUS Pilot

Categories

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1

Only Operated within CA

Single Unit Tractor Construction

Operated within and outside CA

Tractor

Note:

2002 VIUS # Valid record 182 429 91 102

Cal-‐VIUS pilot

Avg. VMT (miles/yr) U.S. CA 22,850 22,850 49,058 49,058 23,305 23,305 76,568

44,796

# Valid record 21 6 9 9

Avg. VMT (miles/yr) U.S. CA 15,738 15,738 24,458 24,458 13,685 13,685 79,770

19,852

1. Vehicles in all strata have GVW ≥ 26,000 lbs.

To compare differences of vehicle activity characteristics between strata, smooth density distributions of VMT within California by three categories were developed, to which the MannWhitney Wilcoxon test (U-test) was applied, as shown in Figure 4. Since the approximated distributions of VMTs were not normal, the U-test was adopted to test the hypothesis H# that the two sample distributions of VMT were identical (17). Figure 4-a and b illustrate that single units registered in urban areas were associated with lower annual and daily travel miles. In the operation only within California category, construction trucks were driven fewer annual miles than single units registered in urban areas, as shown in Figure 4-c. On the other hand, Figure 4-d shows that the daily VMT distributions of these two vehicle categories are similar. The likely reason for these observations is that construction trucks were less frequently used as shown in . Two tractor groups were compared according to their operation type, excluding tractors from the very large fleet stratum. While the annual VMTs were analogously distributed, the distributions of daily VMT were different. The reason for this was that the working days within California of intrastate tractors were generally higher than interstate tractors. The results from the U-tests show that the hypothesis for “Daily VMT within CA of tractor by operation type” can be rejected at the 5% significance level as shown in Figure 4-f. In addition, a similarity in daily VMT distribution within CA of single unit trucks by registered location is rejected at 10% significance level (see Figure 4-b). This comparison shows that each stratum designed for the pilot study had different characteristics in terms of VMT within California.


U-‐Test: 𝐻# not rejected (p-‐value: 0.275> 0.05) a) Annual VMT within CA of single unit by registered 1,2 location

U-‐Test: 𝐻# not rejected (p-‐value: 0.593> 0.05) c) Annual VMT within CA of single unit in urban and 1,2 construction truck

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U-‐Test: Reject 𝑯𝟎 (p-‐value: 0.072< 0.1) b) Daily VMT within CA of single unit by registered 1,3 location

U-‐Test: 𝐻# not rejected (p-‐value: 0.316> 0.05) d) Daily VMT within CA of single unit in urban and 1 construction truck

U-‐Test: 𝐻# not rejected (p-‐value: 0.607> 0.05) e) Annual VMT within CA of tractor by operation 1,2 type Note:

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U-‐Test: Reject 𝑯𝟎 (p-‐value: 0.012< 0.05) 1,2 f) Daily VMT within CA of tractor by operation type

1. H# : the two sample distributions of VMT were identical 2. Hypothesis test at a 5% significance level 3. Hypothesis test at a 10% significance level

Figure 4. Comparison of VMT distribution by categories

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CONCLUSION AND REMARKS

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This study proposed a sample design and an enhanced data collection method (a mail-out-online survey) to collect information on the physical and operational characteristics of commercial vehicles


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that are driven within California. A two-step survey method comprising a web-based Fleet Manager Survey followed by a smartphone app-based (or web-based) Driver Survey was designed to gather annual activities and 3-day trip level activities of commercial vehicles for the State of California, respectively.

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The Driver Survey was not fully tested due to a limited response. However, data obtained from the Fleet Manager Survey provided useful insights into vehicle operations in California. The following recommendations are provided for future state-level truck surveys based on the findings from this study:

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• Timely registration data is recommended since an out-of-date sampling frame can lead to sampling biases and errors due to the inability to capture newly registered vehicles and sampling of vehicles that have changed operations. • The online-based survey could cause non-response bias from the samples that do not have access to the Internet. Therefore, it is recommended that a mail-out paper-based survey option be provided at the respondent’s request. • The survey burden should be further reduced. It took on average 27 minutes to complete each Fleet Manager Survey. Fleet managers with multiple sampled vehicles have the heaviest burden to complete surveys for all identified vehicles. This can be reduced by identifying and removing questions that can be gathered from other available public data sources. • Obtaining the Driver Survey via the fleet manager/owner was not as effective as planned. However, some useful observations can be still gathered from this exploratory study. There were several factors that contributed to the poor response in the Driver Survey. First, the drivers were not the primary survey contacts because no information was available to reach them directly. Furthermore, there was a general reluctance for driver email addresses to be shared for participation in the Driver Survey, and far fewer drivers apparently had access to a smart phone or the Internet than had been anticipated. Intercept surveys could be an alternative strategy to obtain trip level operations from trucks in California. However, further analysis needs to be undertaken to address logistical challenges and sampling biases associated with this survey approach. • Market outreach through trucking and industry association and preferably endorsement of the survey, would likely improve response rates.

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The analysis of VMT obtained from the survey responses showed that the observed vehicle activities were heterogeneous across strata designed for the pilot study, and demonstrated the benefit of using the stratified sampling approach for this pilot study.

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ACKNOWLEDGEMENTS

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The research reported in this paper was supported by the California Air Resources Board. The authors also gratefully acknowledge guidance on the survey design provided by the California Department of Transportation and California Energy Commission. The statements and conclusions in this report are those of the authors and not necessarily those of the California Air Resources Board. The mention of commercial products, their source, or their use in connection with material reported herein is not to be construed as actual or implied endorsement of such products. The online survey platform was


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implemented in Survey Analytics (http://surveyanalytics.com). The contents do not necessarily reflect the official views or policies of the State of California. This paper does not constitute a standard, specification, or regulation.

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REFERENCES

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1. California Department of Transportation (Caltrans), California Statewide Freight Forecasting Model.http://www.dot.ca.gov/hq/tpp/offices/omsp/statewide_modeling/docs/cstdm_fact_shee t.pdf Accessed April 5, 2015 2. California Air Resources Board (CARB). EMFAC2011 Technical Documentation, 2011 3. California Energy Commission (CEC), 2011 Integrated Energy Policy Report: Commission Final Report, 2012. http://www.energy.ca.gov/2011_energypolicy Accessed April 5, 2015. 4. Bureau of the Census. Vehicle Inventory and Use Survey. US Department of Commerce, 2004. 5. California Hybrid, Efficient and Advanced Truck Research Center (CalHEAT). Vehicle and Technologies Characterization and Baseline, 2011. 6. Statistics Canada. Canadian Vehicle Survey: Annual 2009. Statistics Canada Transport Division, 2010. 7. Transport Canada. Canadian Vehicle Use Study, 2013 8. California Air Resources Board (CARB), California Air Resources Board. Staff Report: Proposed Regulation for In- Use On-Road Diesel Vehicles, Appendix G: Emissions Inventory Method and Results, 2008. http://www.arb.ca.gov/regact/2008/truckbus08/appg.pdf. Accessed April 10, 2014 9. Caltrans. California Heavy Duty Truck Travel Survey on Selected Sites, 2001. 10. Lutsey, N. Assessment of out-of-state truck activity in California. Transport Policy 16, no. 1, 2009, pp. 12-18. 11. Clark, M, E. Jessup, and K. Casavant. Freight Truck Origin and Destination Study: Methods, Procedures and Data Dictionary. Strategic Freight Transportation Analysis, 2002. 12. Jessup, E., K. Casavant and C. Lawson. Truck Trip Data Collection Methods. Oregon Department of Transportation, 2004. 13. International Registration Plan, Inc. http://www.irponline.org/?page=EDUFAQ. Accessed May 5, 2014 14. California Air Resources Board (CARB), Truck and Bus Regulation Small Fleet Option, 2014. http://www.arb.ca.gov/msprog/onrdiesel/documents/FAQsmall.pdf Accessed August 10, 2014 15. Truck Activity Monitoring System (TAMS), http://freight.its.uci.edu/tams. 16. Hernandez, S., Tok, A., and Ritchie, S. G. Multiple-Classifier Systems for Truck Body Classification at WIM Sites with Inductive Signature Data. In Transportation Research Board 94th Annual Meeting (No. 15-1377), 2015. 17. Washington, Simon P., Matthew G. Karlaftis, and Fred L. Mannering. Statistical and econometric methods for transportation data analysis. CRC press, 2010.