National Academies Press: OpenBook

Truck Drayage Productivity Guide (2011)

Chapter: Chapter 3 - Drayage Data and Information Sources

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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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Suggested Citation:"Chapter 3 - Drayage Data and Information Sources." National Academies of Sciences, Engineering, and Medicine. 2011. Truck Drayage Productivity Guide. Washington, DC: The National Academies Press. doi: 10.17226/14536.
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16 Data and Information Needs Drayage data are required for the following three basic purposes: • To measure and analyze drayage bottlenecks and delays, • To evaluate potential solutions and best practices, and • To calibrate DrayFLEET or other cost and emissions models. Bottlenecks extend the overall cycle time (e.g., terminal to customer and return) beyond what is necessary to accomplish the actual work of transporting the container. Bottlenecks will thus be manifest as larger-than-necessary cycle times. Identifying and measuring bottlenecks will require data on the overall cycle time, its components, and—especially—those components that contain potential bottlenecks. “Before-and-after” time series data or “with-and-without” cross-section data are needed to eval- uate potential solutions and best practices. Terminal operators often make process or facility improvements to avert the development of significant problems rather than waiting for the prob- lems to develop. The “improvement,” therefore, is sometimes only evident in comparing the pres- ent performance with a hypothetically worse performance. Although discussions with drayage firms and terminal operators can suggest likely bottlenecks and sources of delay, more intensive data mining is usually necessary to verify, quantify, analyze, and prioritize the issues. DrayFLEET and other emissions or cost models require data on port characteristics, cargo flows, distances, cost factors, etc. Depending on the issue to be analyzed, data may be needed on the whole drayage cycle, as follows: 1. Travel times to marine terminals, 2. Inbound gate queue times, 3. Inbound gate processing times, 4. Container yard transaction times, 5. Outbound gate queue times, 6. Outbound gate processing times, 7. Travel times to customers (or depots or rail terminals), and 8. Transaction times at customer locations (or depots or rail terminals). Each of these eight generic time segments may need to be investigated in depth and broken down into such levels of detail as are appropriate, supportable, and informative. There are sev- eral potential sources for these data as follows: C H A P T E R 3 Drayage Data and Information Sources

• Marine terminal operating systems, • Webcam terminal data, • Drayage companies, • State or local departments of transportation, • Surveys, and • Special studies. Data alone do not tell the whole story. As noted, discussions with drayage firms and terminal operators also can suggest bottlenecks and sources of delay. Once bottlenecks have been identified and delays quantified through data analysis, the insights of drayage firms and terminal operators are crucial in discerning cause-and-effect relationships and potential solutions. Drayage firms often are aware of best practices at other terminals or ports, and are in a position to compare operations and outcomes. In NCFRP Project 14, the study team benefited greatly from contacts with terminals and drayage firms, site visits, and opportunities to observe daily operations. Understanding the priorities of drayage drivers is particularly important when assessing the potential effectiveness of policies aimed at improving dray efficiency, such as extended gate hours. Also, drivers are motivated differently depending on their compensation method. Drivers who are paid per load have a different motivation than drivers who are paid by the hour. Marine Terminal Information Systems Every marine container terminal utilizes a terminal operating system (TOS) to help it manage and keep track of the flow of containers through its gate, yard, and berth. In the past, many termi- nals relied on their own in-house software and tools. In today’s fast-changing environment with rapid technological advances and constant practice changes, terminals are finding it more cost effective, convenient, and reliable to outsource this service to third parties. In addition to provid- ing the core functionalities for terminal operations, the TOS is often linked to other systems such as billing, gate automation technology, and Web-based applications where customers can track their containers, make payments, and/or make an appointment. Because of the need to provide customers with up-to-date information on a container, a great deal of information is tracked for every container. Regarding drayage operations, in the normal course of operations the marine terminal operators and their information systems record data on the following: • Volume—Daily gate transaction volumes (and therefore weekly, monthly, and annual values) by transaction type and time of day as well as shipping line, trucking company, container num- ber, and characteristics Most terminals also keep track of the number of double moves that are made at their terminals. • Gate processing—In-gate processing times, implicitly defined as the time between first contact (often at a first-stage pedestal) and the issuance of a yard slip or other directions to leave the gate and enter the container yard. Note that this time span could include a significant wait between the first contact point and the actual gate in a two-stage system. This time does not include the trucks’ queuing time while waiting to gain access to the first-stage pedestal. • Out-gate exit times—The terminal system may or may not capture the time at which a driver starts the out-gate transaction, but will definitely live-stamp the issuance of an EIR or other doc- ument completing the interchange process. • Turn times—A key performance measure associated with drayage operations is truck turn time. This is the difference between the truck’s exit time and the truck’s entered time. • Trouble tickets—Trouble tickets are a key factor in terminal delays, and are discussed in more detail below. Drayage Data and Information Sources 17

In theory, then, marine terminal operators should be able to provide complete, accurate infor- mation on gate flows and transactions from their information systems. In practice, the accuracy and accessibility of gate information will vary with the accuracy of inputs, the rigor with which the system is maintained, and the experience of those accessing the data. The operations manager and gate supervisors typically review the turn time report daily. Although the format of this report varies from terminal to terminal, it will include the turn times by transaction types (e.g., import, export), container types (e.g., dry van, reefer, flat rack), and the overall average, median, minimum, and maximum turn times. Some terminals will also include turn times of trouble transactions. To help the managers and supervisors understand how turn times were affected by the work load, the turn time report may also include the number of gate moves, warehouse moves, rail moves, the number of available equipment, and the number of trou- ble transactions. In requesting data from the terminal operators, researchers should be mindful of several chal- lenges and pitfalls, including the following: • Some terminal data may not be as easy to access and compile as the request may anticipate. To obtain the data, the terminal operator may have to create a special database query, which requires time and effort. • There may be gaps in the data. • Every container terminal is set up differently. Thus, analysis of performance measures such as turn time should consider the characteristics of that terminal. For example, some terminals have the RPMs inside their gates and others have them outside. Obviously, the truck turn times will be higher for those terminals with the RPMs inside their gates. There are very few common marine terminal operating systems in use, and each has its strengths and weaknesses in drayage transactions. The weaknesses tend to be addressed over time, but the feedback loop from frustrated drayage driver to terminal software engineer can be a long one. Terminal data files can be very large, with some annual compilations exceeding 1 million records. Also, terminal data are proprietary, and any data request must be accompanied by appro- priate safeguards for confidentiality. Gate Processing and Turn Time Data Container terminal operating systems collect information on gate activity. The gate data are entered by the clerks who check inbound and outbound trucks, or through automated systems such as swipe cards or optical character recognition (OCR) camera systems. When a drayage driver pulls a container from the terminal interchange, documents are completed to transfer legal custody of the container and chassis (and the contents, if loaded). Movement of loaded contain- ers, empty containers, and bare chassis to and from the marine terminals thus tends to be well documented, but some reconciliation between interchange documentation and gate records may be required. Bobtail trips have not been documented as carefully in the past, but should be more accurately recorded with increased security concerns. A marine terminal information system will typically assign a unique record number to each transaction. A transaction is defined as an instance where the terminal staff interact with a truck, either in the gate or in the yard. The most reliable data are captured at the in-gate and the out- gate. Sometimes records are generated within the terminal, such as a record of when the truck was loaded by a gantry crane. One challenge in analyzing terminal records is aligning transac- 18 Truck Drayage Productivity Guide

tion records with truck visits. For example, a truck may generate several transaction records in the course of a single visit in which it drops off one container and picks up another. Some data manipulation can be required to get the terminal database to “tell the story” of each individual truck trip. Trouble Ticket Records Trouble tickets are created by the marine terminal when a drayage driver’s planned transaction cannot be completed without special human intervention and resolution. Trouble tickets result most often from documentation or process issues, but occasionally are due to container location or equipment issues. Marine terminals typically keep historical records and monitor the reasons for trouble tickets. Some trouble tickets may result in a minor administrative delay whereas others may result in a longer delay or the abandonment of the transaction. On average, each trouble ticket adds about an hour to the turn time as well as requiring additional administrative time for the marine terminal and other operating personnel, depending upon the particular circumstances. The study team found that approximately 5% of all such transactions result in trouble tickets, and this rate was relatively consistent across the participating marine terminals. The analysis of trouble ticket data can be used to provide information and insight necessary to evaluate the overall effectiveness of communications and administrative processes in the logistics chain. At this level, the results cannot be used to blame or find fault with any individual party or group. The trouble ticket “reason” codes simply report the symptom and not the cause of the trou- ble. For example, in this kind of system a trouble ticket labeled as “dispatch error” may the fault of the motor carrier dispatcher or the party that provided the dispatcher with bad information. To perform this kind of analysis the researcher will need to 1. Obtain the raw data from the marine terminal. Typically, these data can be provided interac- tively or in an electronic format such as Excel or Access. 2. Analyze the data to produce a frequency distribution to determine if particular “reason” codes are more/much more important than others. 3. After reviewing the data, consult with the marine terminal to ensure that the codes are well defined and well understood, and determine when and where the codes are applied and by whom. Codes have been created to serve the marine terminal and are in the local jargon. At the end of the interview the researcher should thoroughly understand the definition of all the data elements as well as the reliability of the process used to create the data. A potential problem with trouble ticket data is that several different workers are typically applying the codes. Because there are many different workers and many codes with similar definitions, it is likely that codes are somewhat inconsistently applied. 4. As necessary, categorize and summarize data to provide meaningful information and to miti- gate the inconsistencies inherent in the data collection process. 5. If possible, correlate trouble ticket data with driver experience level, motor carrier, customer, marine terminal, transaction type, or marine carrier. Although this kind of analysis can begin to focus attention on problem areas, they are not, in and of themselves, sufficient to fix blame. To actually determine the fault, a thorough investigation would be required for each trouble ticket. 6. Provide the information and associated implications to the marine terminal. The results may be useful to the firm for management purposes, and review by the marine terminal provides a necessary reasonableness check on the research results. Trouble ticket data are most useful in determining which types of process exceptions are most common and where follow-up analysis would be most useful. For example, the NCFRP Project 14 Drayage Data and Information Sources 19

study team found that most trouble tickets were generated by process, information, and dispatch issues, rather than for equipment or security problems. Drayage Company Data Company Records Drayage companies keep records of the trucks that make up their fleet (trucks leased from owner-operators). Drayage companies also may have dispatch logs showing which trucks were dis- patched and for which containers they were dispatched. Drayage companies also keep safety inspec- tion records. Individual owner-operators keep records of their repairs and maintenance. Company data can be used to understand the various marine drayage tasks a driver is assigned to perform. A motor carrier typically bills for its services based on a driver’s report of work per- formed. These records document the activities of a driver, showing what work was done, how it was done, for what customer, and the time it required. In addition, motor carriers have dispatch logs showing which trucks were dispatched and for which containers they were dispatched. These companies also keep safety records. Individual owner-operators keep records of their repairs and maintenance. Although some motor carriers may maintain this information in a useful electronic format, actual recordkeeping varies widely and is tailored to suit the needs of the drayage firm, not the researcher. As a result, a large number of driver time records must often be manually examined and data recorded on an Excel spreadsheet. Then this information can be analyzed to estimate turn times for different marine terminals for different types of turns (i.e., double loaded move or bob- tail in/load out). The main problem with this type of data is that it is commercially very sensitive and not often available to the outside researcher. In addition, individual driver records have the problem associ- ated with any manual contemporaneous record; the quality and reliability depend on the level of diligence of the individual driver. GPS/AVL Data GPS/AVL Capabilities A growing number of drayage firms utilize global positioning systems (GPS) or automatic vehicle locators (AVL) to track and dispatch their vehicles. GPS/AVL records are sometimes required as a reporting requirement for trucks that participate in air quality grant programs. In other cases, GPS or RFID is used to ensure that drayage trucks do not enter city streets or other corridors that are not prepared to accommodate commercial loads. AVL systems also are used for theft recovery, and some insurers give discounts to drayage firms that use such systems. “Fleet telematics” systems take the concept further by permitting two-way data exchange between the vehicle and the home terminal. Such systems provide an unprecedented opportunity to obtain highly detailed objective data on drayage movements. For example, these systems are capable of automatically recording the following: • Terminal arrival, • Idling in the terminal, • Terminal departure, • Average speed in the terminal area, and • Driving times and speeds between terminals and customer locations. 20 Truck Drayage Productivity Guide

Most critically, these systems are the only means of automatically collecting data on terminal queue times. There are a number of commercial providers of such systems, including the following: • Qualcomm—www.qualcomm.com/products_services • Teletrac—www.teletrac.net • FleetMatics—www.fleetmatics.com • Advanced Tracking Technologies, Inc.—www.advantrack.com Although there have been special programs to equip drayage tractors with GPS systems specifi- cally to collect data, utilization of commercial systems already installed by the drayage firm or driver offers multiple advantages, including lower cost. The data are limited in that there is no automatic linkage to confirm what the truck was doing in the marine terminal. As such, the data produce accurate turn times, which may not be matched to the type of turn (i.e., double loaded move or bobtail in/load out) without additional manual effort. GPS Data Acquisition Example A motor carrier that regularly serves the Port of New York and New Jersey made Qualcomm/GPS data available to the NCFRP Project 14 study team. The team used the information to measure the time spent at a marine terminal, both inside the gate and in the queuing area. The first step in the process was to become familiar with the current operating patterns of the motor carrier. A day was spent with the dispatcher and a month of driver time sheets were reviewed and analyzed. The drivers recorded the time they spent at the marine terminals and these data were used as a reasonableness test for the subsequent GPS analysis. This step is essential to ensure validity and accuracy. Next, using the motor carrier’s system, the research team established geofenced areas correspond- ing to the marine terminals and the auxiliary container and chassis yards serving those facilities (Figure 3–1). Qualcomm allows a boundary to be created around any particular geographical fea- ture such as a marine terminal, container yard, customer location, home terminal, etc. The process uses satellite photos and is very similar to that used in Google Earth to establish boundaries. The system matches the polled positions with the geofenced areas and produces a report of history of positions for each vehicle. Drayage Data and Information Sources 21 Figure 3–1. Geofenced area for Global Marine Terminal, NY-NJ. Source: The Tioga Group, Inc./Qualcomm/Google Earth.

The third step in the process was to take test data from the Qualcomm system. This was successful as a proof of concept, but the polling frequency was too long to produce reliable results. The next step was to modify the Qualcomm system to poll the location of the truck fleet every 5 minutes for 4 weeks during January 2010. These individual reports were converted to Excel files, combined, and then analyzed to produce the resulting performance measures. As part of NCFRP Project 14, the Tioga Group analyzed the information for nine trucks from January 1 to January 26 as a pilot. The raw data produced by Qualcomm is simply a list in Excel of every observation. Qualcomm investigated, but did not have a regular turn time report in their standard package. As a result, these lists were reviewed manually to identify the time a truck entered one of the geofenced areas and the time it left. Once the month was complete, the full data set had 1,888 usable marine terminal cycles. These were used to produce various turn time frequency distributions, as well as to provide standard statistics such as mean and mode. The biggest issue with the data was false positives and false negatives. These occur repeatedly because the terminals, regularly used roadways, and the motor carrier’s domicile are in very close proximity. During the manual analysis of the raw data, single, isolated positives or negatives were ignored. Therefore, if a truck was in one marine terminal for 20 minutes, listed in the adjacent ter- minal or outside the terminal for one reading, and then back in the terminal for the next reading, the truck was assumed to be located in the marine terminal for the entire time. Also if a truck was on a dispatch that went past a marine terminal and showed in the terminal for one reading, that observation was also ignored. Remote chassis and container facilities were separately geofenced. Where it was obvious that a truck was dispatched to pick up a chassis and then immediately pick up a load at the main terminal, these cycles were combined to produce a cycle time that reflected the full service provided. The same is true for the case in which a chassis yard cycle immediately followed a main marine terminal cycle. Local and Regional Traffic Data DOTs collect a limited amount of information that may be useful in analyzing dray operations. The records collected by DOTs are used for broad planning purposes and, for this reason, usually are not designed to discern the subtle distinctions that characterize dray operations. Rather, DOT records should be seen as providing context as to the overall level of congestion, from all vehicle types, on corridors that could be impacted by drayage. Typically, each DOT has a network of permanent sites that are regularly used to collect data in an on-going fashion. The data collected are usually annual average daily traffic (AADT) in which trucks are not discerned from passenger vehicles. On a sample of highways, classification counts are made to develop factors that can translate average vehicle counts into autos and trucks. This can be viewed as a calibration exercise to obtain estimates of truck flows. Sites may be located on key ramps or highway segments that serve marine terminals (e.g., California) but, in general, state DOTs leave data collection responsibilities to metropolitan planning organizations (MPOs). For roadways in close proximity to a port terminal, there are cases where almost all traffic is made up of dray vehicles and, in this sense, the total traffic count would approximate the dray impact. For the majority of roadways, however, dray traffic will constitute a small share of total traffic. Therefore, the magnitude of the impact of drayage can be assessed by comparing truck generation from the terminals with total traffic counts on connecting corridors and removing the share of dray trips that terminate in close proximity to the terminal itself and therefore do not significantly inter- fere with passenger vehicle movements. Dray truck volumes on networks are best derived from 22 Truck Drayage Productivity Guide

origin/destination (O/D) samples at the terminal gates with a small number of calibration sites at key highway locations near the port, such as ramps. Surveys Driver and Drayage Company Surveys There are no regularly maintained public databases related to drayage activity or operations. The industry is not subject to economic regulation, and has no operational reporting requirements. Safety, licensing, and insurance information may be available but is not relevant to the objectives of this project. As a result, existing drayage data reside almost exclusively in studies, with data col- lected for the purpose mostly through surveys of drivers and drayage firms. Surveys of drayage firms and drivers can be reliable and useful for three purposes. 1. To document and quantify factors that are not recorded in operating systems or other data col- lection routines. Examples could include the frequency with which importers insist on specific containers (regardless of how long it takes the driver) and the frequency with which drivers whose export loads have been turned away from terminals chose to wait for resolution rather than parking the load. 2. To obtain the perceptions of managers, dispatchers, and drivers regarding bottlenecks and other issues being studied. Although quantifying and documenting these issues is a primary study objective, a gulf between perception and quantified reality may signal a critical measurement or definitional issue. 3. To ensure that the study has not missed significant issues or factors. One useful practice is to always include an open-ended survey question to ensure that respondents can convey other issues of concern. Surveys that ask for quantified estimates of average turn times, gate queue times, or trouble ticket frequency are likely to be met with off-the-cuff guesses. Drivers do not ordinarily have data on turn times, and trucking company executives or dispatchers would have to compile any available data to obtain averages or distributions. Inconsistencies are, unfortunately, common in survey data. Survey responses are not constrained by mathematical rules, and tend to reflect recent experience or on-going complaints rather than actual averages. For this reason, researchers need to be very careful about how surveys are constructed and how their results are used. The research team found that surveys or interviews of drayage company managers and dispatch- ers were more cost-effective—and just as valuable—as driver surveys. Moreover, company person- nel have a broader perspective than do drivers and have access to company records, whereas drivers must rely on memory and impressions. One of the most practical and useful set of opinion surveys designed to measure the satisfaction level of motor carriers with the performance of marine terminals was initiated by the bi-state harbor carriers in New Jersey more than a decade ago. Marine, rail, and container yard (CY) ter- minals are graded monthly by port motor carriers on several service dimensions using A–F “school–type” grades. The methodology had the advantage of being easy, relatively consistent, and sustainable over the long term. The results provide a regular basis for discussion and improvement throughout the port community. During the course of NCFRP Project 14, the results of these sur- veys clearly showed their utility. The system identified a terminal that was having severe operating problems. The terminal’s grades showed both the degree (D and F grades) and duration (several months) of those problems. The motor carriers used the results to enlist the support of others in the port community to pursue resolution of the problems. Drayage Data and Information Sources 23

NCFRP Project 14 Survey Example As a part of this effort, the research team surveyed port drayage drivers and drayage company personnel (managers, dispatchers) seeking information relevant to the study. A draft survey instrument was used in a small number of pilot interviews. The survey instruments were refined and finalized. The survey followed conventional methodology. • The research team identified candidate drayage companies from port workshops, referrals, and personal knowledge. The survey was distributed through the drayage companies, who responded to the company surveys and distributed the driver survey to their drivers. This methodology produced a selection bias toward relatively more conscientious and responsible drivers and firms. • In the NY/NJ area, the research team contacted the Association of Bi-State Motor Carriers and attended their meetings to request cooperation. • Members of the research team contacted LoadMatch.com, a service that assists intermodal truckers (chiefly those who serve rail terminals) to locate matching loads and avoid empty moves. An online Survey Gizmo version of the company survey was created and LoadMatch dis- tributed the link to its subscribers. The results were interesting but inconsistent and of limited value. The most valuable use of the survey was in verifying that the team had indeed addressed the most critical issues. There are a number of problems/limitations associated with motor carrier and driver surveys that were encountered in the project survey. The team received significant resistance from the port com- munity, particularly in Los Angeles/Long Beach and Northern New Jersey, for a number of rea- sons, as follows: • Many of the drivers have been surveyed several times. Change has come slowly to the industry, so response rates are low and results can be unreliable. • There was some resistance on the part of drivers/companies to contribute their productive hours toward intangible results. • The result of these surveys is opinion data, which is less highly regarded and useful than objec- tive data. The team concluded that the opinion survey efforts were the least rewarding of any of the data gathering methods used in this analysis, and that further use of driver/company surveys should be very limited and carefully focused toward specific realistic objectives. Alternate, more precise, methods are increasingly available for determining information available only by opinion survey for most of the past decade. Survey instruments are reproduced in the fol- lowing sections. NCFRP Project 14 Port Drayage Driver Survey Form The survey form given to drayage drivers is reproduced here (response spaces have been deleted). Please complete the following survey and turn it in to your dispatcher. Your name and answers will be combined with the responses from all the other drivers and kept confidential. Turn Times at Marine Terminals 1. In your experience, what are the major causes of congestion at marine container terminals? 2. In the spaces below, please enter the amount of time in minutes you would allow for each type of move with no congestion, with routine congestion, and with peak congestion. 24 Truck Drayage Productivity Guide

Sources of Delay, Extra Trips, and Trouble Tickets at Marine Terminals 3. Please rate overall sources of delay, with 1 as the least serious and 5 as the most serious. ▪ Public roads & highways 1 2 3 4 5 ▪ Marine terminal gates 1 2 3 4 5 ▪ Marine terminal yards 1 2 3 4 5 ▪ Other ______________ 1 2 3 4 5 4. Please rate causes of non-revenue trip legs, with 1 as the least serious and 5 as the most serious. ▪ Gate turnaways 1 2 3 4 5 ▪ Chassis logistics (“Splits”) 1 2 3 4 5 ▪ Dirty or littered empties 1 2 3 4 5 ▪ Import box not ready 1 2 3 4 5 ▪ Export box not accepted 1 2 3 4 5 ▪ Wrong information 1 2 3 4 5 ▪ Other______________ 1 2 3 4 5 5. Please rate causes of trouble tickets, with 1 as the least serious and 5 as the most serious. ▪ Customer information error 1 2 3 4 5 ▪ Terminal information error 1 2 3 4 5 ▪ Equipment problem 1 2 3 4 5 ▪ Driver error 1 2 3 4 5 ▪ Dispatcher/company error 1 2 3 4 5 ▪ Other______________ 1 2 3 4 5 6. When you get a trouble ticket or have to visit the trouble window, how long do you usually wait for resolution before shifting to another container? ________ minutes ▪ What percentage of the time can you shift to another container move? ______% ▪ What percentage of the time does a customer delay a driver by insisting that the driver pick up or deliver a specific container that is causing trouble?_____% Problems at Marine Terminals 7. At marine terminals, what practices cause longer turn times, more frequent trouble tickets, or extra trips? 8. At marine terminals, how often do those practices happen? _____% of trips 9. At marine terminals, what should they do differently? 10. What customer practices cause longer turn times, more frequent trouble tickets, or extra trips? 11. How often do those customer practices happen? _____% of trips Drayage Data and Information Sources 25 Terminal Condition Expected turn time* No Routine Peak in minutes for . . . Congestion Congestion Congestion Bobtail in/Load out Bobtail in/Empty out Load in/Bobtail out Load in/Empty out Load in/Load out Empty in/Bobtail out Empty in/Load out Empty in/Empty out If these times are differ- ent at each terminal, please explain why some are longer or shorter ________ ______________________ ______________________ ______________________ ______________________ ______________________ ______________________ ______________________ ______________________ ______________________ ______________________ ___________ *including time in line and time in the terminal

12. What should customers do differently? 13. What steamship line practices cause longer turn times, more frequent trouble tickets, or extra trips? 14. How often do those steamship line practices happen? _____% of trips 15. What should steamship lines do differently? Thank you very much for your help with this survey. Distributed by: ___________ NCFRP Project 14 Port Drayage Company Survey Form The survey form given to drayage firms is reproduced below (response spaces have been deleted). Please complete the following survey based on your experience in port container drayage. Your name and answers will be combined with the responses from all the other firms and kept confidential. Key Issues 1. Are you a . . . ❑Dispatcher ❑ Company Owner ❑Manager ❑Other ____________________________ 2. In your experience, what are the major causes of congestion at marine container terminals? 3. What are the major impacts of terminal congestion and delays on drayage operations? 4. In the spaces below, please enter the amount of time in minutes you would allow for each type of move with no congestion, with routine congestion, and with peak congestion. 26 Truck Drayage Productivity Guide 5. If these times are different at each terminal, please explain why some are longer or shorter. 6. What has been your experience with terminal appointment systems? 7. What has been your experience with TWIC to date? 8. Please rate overall sources of delay, with 1 as the least serious and 5 as the most serious. ▪ Public roads & highways 1 2 3 4 5 ▪ Marine terminal gates 1 2 3 4 5 ▪ Marine terminal yards 1 2 3 4 5 ▪ Other ______________ 1 2 3 4 5 Terminal Condition Expected turn time* No Routine Peak in minutes for . . . Congestion Congestion Congestion Bobtail in/Load out Bobtail in/Empty out Load in/Bobtail out Load in/Empty out Load in/Load out Empty in/Bobtail out Empty in/Load out Empty in/Empty out *including time in line and time in the terminal

Problems at Marine Terminals 9. Please rate causes of non-revenue trip legs, with 1 as the least serious and 5 as the most serious. ▪ Gate turnaways 1 2 3 4 5 ▪ Chassis logistics (“Splits”) 1 2 3 4 5 ▪ Dirty or littered empties 1 2 3 4 5 ▪ Import box not ready 1 2 3 4 5 ▪ Export box not accepted 1 2 3 4 5 ▪ Wrong information 1 2 3 4 5 ▪ Other______________ 1 2 3 4 5 10. Please rate causes of trouble tickets (or visits to a trouble window), with 1 as the least serious and 5 as the most serious. ▪ Customer information error 1 2 3 4 5 ▪ Terminal information error 1 2 3 4 5 ▪ Equipment problem 1 2 3 4 5 ▪ Driver error 1 2 3 4 5 ▪ Dispatcher/company error 1 2 3 4 5 ▪ Other______________ 1 2 3 4 5 11. When drivers get a trouble ticket or have to visit the trouble window, how long do they usu- ally wait for resolution before shifting to another container? ________ minutes ▪ What percentage of the time can they shift to another container move? ______% ▪ What percentage of the time does a customer delay a driver by insisting on a specific troublesome container? _____% 12. What marine terminal practices cause longer turn times, more frequent trouble tickets, or extra trips? 13. How often do those marine terminal practices happen? _____% of trips 14. What should marine terminals do differently? Steamship Line Practices 15. What steamship line practices cause longer turn times, more frequent trouble tickets, or extra trips? 16. How often do those steamship line practices happen? _____% of trips 17. What should steamship lines do differently? Customer Practices 18. What customer practices cause longer turn times, more trouble tickets, or extra trips? 19. How often do those customer practices happen? _____% of trips 20. What should customers do differently? Rail Intermodal Terminal Practices 21. What rail intermodal terminal practices cause longer turn times, more trouble tickets, or extra trips? 22. How often do those rail intermodal terminal practices happen? _____% of trips 23. What should rail intermodal terminals do differently? Best Practices 24. What marine terminal gate or other changes have you experienced that improved drayage operations? 25. What marine terminal practices have you experienced that you would recommend as “best practices” for other marine terminals? Drayage Data and Information Sources 27

26. What drayage or dispatching practices have you developed or learned from others that help reduce turn times, trouble tickets, or extra trips? 27. What else should we know about? (Add pages if necessary.) Thank you very much for your help with this survey. Distributed by: ___________ Terminal Webcam Data Collection Methodology A number of marine terminals provide live views of their gates via webcams. These gate cameras are set up by the terminal operators to allow drayage firms to monitor the gate conditions. They are intended as a means of managing demand for the marine terminals, assuming that drayage firms will adjust their plans based on the real-time feedback of gate congestion. In this study, gate cameras were used to assess truck queues outside the terminal gates at two busy terminals in two different geographic regions. The placement and viewing angle of the cameras allowed measure- ment of the following: • The gate processing time of each truck; • The time the truck spent waiting outside the gate; • The time lost when a gate closed for lunch; • The level of congestion at a marine gate throughout the week; and • The level of gate activity during off-peak, nighttime, and pre-opening hours. The general method for all of these tasks was to manually capture a series of images and store them in Microsoft Excel for post-processing. That is, researchers copied the camera’s view on a Web browser and then pasted the image into Excel. Thus, the number of images captured is a function of how fast the copy and paste task can be accomplished. Also, it is dependent on the refresh rate of the camera. Some cameras provide a live feed whereas others provide snapshots at a certain interval (e.g., 30 seconds). Table 3–1 provides some key statistics concerning the rate at which images were recorded at the two study terminals. Each recorded image includes a time stamp. To measure the terminal’s processing time, the time at which each truck left the gate area was recorded in the corresponding column in an Excel file. The gate processing time is simply the dif- ference between the departure times of trucks in the same lane. Using this procedure, the study 28 Truck Drayage Productivity Guide Terminal A Date 11/2/2009 11/10/2009 11/4/2009 11/5/2009 11/6/2009 Day Monday Tuesday Wednesday Thursday Friday Observation period (EST) 13:00-14:00 14:00-15:00 10:00-11:00 15:00-16:00 14:00-15:00 Number of images captured in 1 hour 309 533 428 514 540 Average rate (seconds per image) 11.65 6.75 8.41 7.00 6.67 Number of trucks processed 92 111 106 71 115 Terminal B Date 1/20/2010 1/21/2010 1/22/2010 1/25/2010 1/26/2010 Day Wednesday Thursday Friday Monday Tuesday Observation period (EST) 17:35-18:35 17:03-18:03 17:15-18:15 17:46-18:46 17:00-18:00 Number of images captured in 1 hour 116 159 163 166 153 Average rate (seconds per image) 31.03 22.64 22.09 21.69 23.53 Number of trucks processed 36 63 84 65 96 Table 3–1. Image capture rates at marine terminals.

team was able to obtain the truck processing times for nearly all trucks. The exceptions arose when rain made it difficult to distinguish one truck from another. Using the webcam method, one also can observe queuing time. The measurement is the differ- ence between the time the truck joined the queue and the time that it left the gate area. A prob- lem with some terminals is that, depending on the camera’s position and angle, one may not be able to see the entire queue. This method was used to determine time lost due to lunchtime clo- sure of the gate. Finally, the webcam method also enables monitoring of gate congestion levels over an extended period (days/weeks). In this study, to determine how frequently and severely a gate was congested, for an entire week team members took snapshots of a marine terminal gate every hour that the ter- minal was open. The result clearly indicated the peak associated with the initial opening of the gate and higher congestion due to ship schedules. Photos also were taken of various terminals during the night to determine the level of queuing activity when the terminals were closed. Recording the images in Excel facilitated subsequent analysis, which typically involved develop- ment of a frequency distribution of the results, as well as ordinary statistical measures including means and modes for the various data sets that were collected. As illustrated in this work, the webcam method can be used effectively to obtain truck process- ing times, truck inter-arrival times, and truck queuing times, as well as early morning queuing, lunch hour queuing, and truck weekly arrival pattern. This method potentially can be used to per- form more rigorous studies such as the effect of weather on gate operations and the impact of a change in the gate infrastructure (e.g., additional lane) or gate operations (e.g., appointment sys- tem). Additionally, the webcam method provides access to a greater number of terminals that may be practically impossible to study using the traditional field-based method. Finally, although the webcam method offers many advantages, it does have a number of limita- tions. The camera lens could be blocked with water during stormy conditions. There were also cases where the camera was completely off target, possibly due to strong winds. Another reliability issue is that sometimes the camera stops working after normal duty hours. Depending on the camera’s view, one may not be able to observe all lanes at some terminals or the end of a queue. The resolu- tion of the camera is typically low, which can make image analysis difficult. Marine terminals provide webcams for the use of truckers and customers. Publication of actual webcam images raises potential issues of confidentiality, ownership, and legality that should be addressed in advance. Sample Webcam Study Results At one terminal, the NCFRP Project 14 study team sampled gate processing time a different hour per day on five different days of the week (Figure 3–2). The result showed a median wait time of 4.3 minutes and an average wait time of 5.1 minutes. Observations of the full service portion of the gate also were taken hourly for a week. In Fig- ure 3–3, Congestion Level 0 means that the next arriving driver would be serviced immediately. Level 1 equates to a wait of 15 minutes or less. Level 2 equates to a wait of 15–30 minutes. Level 3 equates to an average wait of more than 30 minutes. The times are based on the average wait times determined in the initial stage of the analysis. The graph shows that this terminal always has a substantial number of trucks waiting for the gate to open. For half of the week, gate queues are 15 minutes or less. The heavy pattern at the end of the week is due to the need to process a large number of export loads to meet ship departure schedules. Drayage Data and Information Sources 29

30 Truck Drayage Productivity Guide Figure 3–2. Gate waiting times from webcam study. Average Congestion Level For Each Time Slot (Sorted by Day) 0 0.5 1 1.5 2 2.5 3 6: 00 7: 00 8: 00 9: 00 10 :0 0 11 :0 0 12 :0 0 13 :0 0 14 :0 0 15 :0 0 16 :0 0 6: 00 7: 00 8: 00 9: 00 10 :0 0 11 :0 0 12 :0 0 13 :0 0 14 :0 0 15 :0 0 16 :0 0 6: 00 7: 00 8: 00 9: 00 10 :0 0 11 :0 0 12 :0 0 13 :0 0 14 :0 0 15 :0 0 16 :0 0 6: 00 7: 00 8: 00 9: 00 10 :0 0 11 :0 0 12 :0 0 13 :0 0 14 :0 0 15 :0 0 16 :0 0 6: 00 7: 00 8: 00 9: 00 10 :0 0 11 :0 0 12 :0 0 13 :0 0 14 :0 0 15 :0 0 16 :0 0 MONDAY TUESDAY WEDNESDAY THURSDAY FRIDAY Time Slot (Monday to Friday) CO NG ES TI O N LE VE L Level 0 - an open lane exists, no wait Level 1 - 1 to 3 trucks in line, 0-15 min. wait Level 2 - 4 to 6 trucks in line, 15-30 min. wait Level 3 - end of line not visible, 30+ min. wait Figure 3–3. Webcam data on gate queuing.

Site Visits and Field Data Collection Site visits to marine terminals and drayage firms are extremely valuable in understanding drayage operations and terminal interactions, and imperative for those unfamiliar with the details of local port operations. Considerable care, however, is required to arrange and conduct site visits. Drayage firms are private commercial facilities. Appropriate contacts with drayage company managers will usually result in permission to observe dispatching and other operations. The morn- ings of busy days in peak shipping season can be extremely hectic, and the researcher may want to balance the educational value with the inconvenience to the firm in visiting during such times. Marine container terminals are highly sensitive facilities in several respects, as follows: • Safety—Marine terminals require all personnel to wear appropriate safety equipment and fol- low strict safety rules. Any visitors or observers in the operating areas of the terminals will be subject to the same requirements. • Security—For unescorted access, anyone on a marine terminal must have a TWIC issued by TSA. Most visitors will be escorted at all times, even if they have a TWIC. Truck drivers are not allowed to have passengers in the cab. Anyone observing operations in the gate queuing area or outside the terminal will likely be challenged by security staff. • Labor agreements—Longshore labor agreements govern any collection of data or use of tech- nology in the marine terminals. Attempts to collect data or use equipment without express permission obtained in advance will almost certainly generate union concern. There are three likely applications of field data collection for port drayage, as follows: 1. In-gate terminal queuing. Field observations of gate queuing would require multiple observers over many hours. The use of webcams or GPS/AVL systems are better alternatives for collect- ing gate queuing data. 2. In-terminal operational times such as hooking up a chassis or waiting in line for a lift machine. These fall into the category of classic “time and motion” studies. 3. Undocumented exceptions, such as turnaways or extra trips that are not recorded by terminal operating systems. Collection of data in the field—at marine terminals, drayage firms, or rail terminals—is, however, costly, time-consuming, and subject to wide variability. For those reasons, the collec- tion of data in the field should be focused on those information needs that cannot be met by other methods. Special Studies Of the various parties within the drayage industry, the ports are the only ones likely to under- take or commission special drayage studies or surveys, as shown in the following examples: • Port of Houston Drayage Survey—The Port of Houston Authority sponsored extensive verbal surveys of drayage trucks in July–October 2008, with over 3,800 completed surveys. This effort was supplemented by a written survey taken July 31, 2008, with 183 completed responses. • Port of New York and New Jersey (NY/NJ) Origin-Destination Studies—The Port of New York and New Jersey undertook an extensive drayage study in 2005 focused on understanding origin and destination patterns. This work updated a previous study completed in 1995. The survey used an extensive in-person questionnaire customized as required for individual port terminals. • Ports of Los Angeles and Long Beach (LALB) Truck Trip Surveys—The San Pedro Bay ports have undertaken drayage driver surveys to determine the pattern of drayage trips. With trips Drayage Data and Information Sources 31

allocated to ZIP codes or to representative points within regions, such data can yield a weighted average distance to shipper/consignee locations. • Port of Oakland Drayage Study—The Port of Oakland commissioned a drayage study to sup- port the development of a clean truck plan. The report, prepared by Beacon Economics, was completed in April 2009. The Oakland study included surveys of licensed motor carriers (LMCs), drayage companies, and drayage drivers. Much of the survey scope concerned work- ing conditions, driver demographics, and a comparison of employee drivers versus owner- operators. The study did, however, attempt to address fleet composition, distances traveled, trips per day, and terminal turn time. Special studies, whether sponsored by a port authority or another party, frequently have the advantage of bringing substantial resources to bear on the issues. Such studies may, however, be limited in scope or timing. The container shipping and drayage industries are volatile, and can change significantly in a short time. The results of special studies must therefore be interpreted and applied with appropriate caution. 32 Truck Drayage Productivity Guide

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TRB’s National Cooperative Freight Research Program (NCFRP) Report 11: Truck Drayage Productivity Guide is designed to help improve drayage productivity and capacity while reducing emissions, costs, and port-area congestion at deepwater ports.

The guide includes suggestions designed to help shippers, receivers, draymen, marine terminal operators, ocean carriers, and port authorities address inefficiencies, control costs, and reduce associated environmental impacts of truck drayage.

The guide identifies and quantifies the impacts of bottlenecks, associated gate processes, exceptions (trouble tickets), chassis logistics, congestion, and disruption at marine container terminals. The impacts are described in terms of hours, costs, and emissions that were estimated using the Environmental Protection Agency’s DrayFLEET model.

A CD-ROM, which contains the final report on the development of NCFRP Report 11 and its appendices, is included with the print version of NCFRP Report 11.

The CD-ROM is also available for download from TRB’s website as an ISO image. Links to the ISO image and instructions for burning a CD-ROM from an ISO image are provided below.

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CD-ROM Disclaimer - This software is offered as is, without warranty or promise of support of any kind either expressed or implied. Under no circumstance will the National Academy of Sciences or the Transportation Research Board (collectively “TRB’) be liable for any loss or damage caused by the installation or operations of this product. TRB makes no representation or warranty of any kind, expressed or implied, in fact or in law, including without limitation, the warranty of merchantability or the warranty of fitness for a particular purpose, and shall not in any case be liable for any consequential or special damages.

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