National Academies Press: OpenBook

Airport Landside Data: Collection and Application (2023)

Chapter: Appendix B - Summary of Interviews with Case Example Airports

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Suggested Citation:"Appendix B - Summary of Interviews with Case Example Airports." National Academies of Sciences, Engineering, and Medicine. 2023. Airport Landside Data: Collection and Application. Washington, DC: The National Academies Press. doi: 10.17226/27403.
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Suggested Citation:"Appendix B - Summary of Interviews with Case Example Airports." National Academies of Sciences, Engineering, and Medicine. 2023. Airport Landside Data: Collection and Application. Washington, DC: The National Academies Press. doi: 10.17226/27403.
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Suggested Citation:"Appendix B - Summary of Interviews with Case Example Airports." National Academies of Sciences, Engineering, and Medicine. 2023. Airport Landside Data: Collection and Application. Washington, DC: The National Academies Press. doi: 10.17226/27403.
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Suggested Citation:"Appendix B - Summary of Interviews with Case Example Airports." National Academies of Sciences, Engineering, and Medicine. 2023. Airport Landside Data: Collection and Application. Washington, DC: The National Academies Press. doi: 10.17226/27403.
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Suggested Citation:"Appendix B - Summary of Interviews with Case Example Airports." National Academies of Sciences, Engineering, and Medicine. 2023. Airport Landside Data: Collection and Application. Washington, DC: The National Academies Press. doi: 10.17226/27403.
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Suggested Citation:"Appendix B - Summary of Interviews with Case Example Airports." National Academies of Sciences, Engineering, and Medicine. 2023. Airport Landside Data: Collection and Application. Washington, DC: The National Academies Press. doi: 10.17226/27403.
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Suggested Citation:"Appendix B - Summary of Interviews with Case Example Airports." National Academies of Sciences, Engineering, and Medicine. 2023. Airport Landside Data: Collection and Application. Washington, DC: The National Academies Press. doi: 10.17226/27403.
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Suggested Citation:"Appendix B - Summary of Interviews with Case Example Airports." National Academies of Sciences, Engineering, and Medicine. 2023. Airport Landside Data: Collection and Application. Washington, DC: The National Academies Press. doi: 10.17226/27403.
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Suggested Citation:"Appendix B - Summary of Interviews with Case Example Airports." National Academies of Sciences, Engineering, and Medicine. 2023. Airport Landside Data: Collection and Application. Washington, DC: The National Academies Press. doi: 10.17226/27403.
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Suggested Citation:"Appendix B - Summary of Interviews with Case Example Airports." National Academies of Sciences, Engineering, and Medicine. 2023. Airport Landside Data: Collection and Application. Washington, DC: The National Academies Press. doi: 10.17226/27403.
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55   Interview Questions During the follow-up interview with relevant staff, the following questions were asked: 1. How data are collected, what systems/technologies are used (e.g., Passenger intercept survey? Bluetooth? Wi-Fi access page?) 2. How data are analyzed (e.g., Excel? Other business intelligence software? Contractor?) 3. Why data are collected. 4. How data inform decision-making? The data that airports consider to be important in informing decision-making. 5. Information on the costs and any legal issues with data collection and storage. 6. The availability of data from contractors or other third-party sources (airlines or other stakeholders)? 7. What kind of data would you like to have that you currently do not collect or receive? 8. Challenges encountered during data collection, storage, or application to decision-making. 9. An example of how your airport fixed a problem using data. Case Examples The airport staff that responded to the online survey indicated their willingness to serve as case examples. Based on survey responses and airport characteristics, the team identified nine airports to serve as case examples. Selected airports indicated a range of data collection efforts across landside facilities and provided diversity in airport activity levels. This section provides a summary of the case example interviews. Chicago O’Hare International Airport The City of Chicago, the operator of Chicago O’Hare International Airport (ORD), indicated that total vehicular volume data are collected as needed via camera systems that require manual review, and vehicular volume data by mode are collected via several different systems. The airport’s ground transportation management system uses license plate recognition (LPR) equipment at the airport’s commercial vehicle hold lot and commercial vehicle lane at Terminal 1. Combined with TNC self-reported data (provided through the Chicago Department of Business Affairs and Consumer Protection’s PowerBI platform), this information is used for vehicle classification. Mode share data are collected as needed by planning consultants. Wait times for transportation services are collected on an as-needed basis. ORD staff indicated that passenger wait times for taxis are collected manually by taxi stand staff. Curbside dwell times are collected manually by watching footage from cameras typically used for other purposes. Ridership of airport-owned A P P E N D I X B Summary of Interviews with Case Example Airports

56 Airport Landside Data: Collection and Application shuttles is typically estimated using remote parking exit counts. The Chicago Transit Authority collects ridership data of public transit through transit passes that can be requested by the airport when needed. ORD staff also indicated that public transit ridership data have, in the past, been manually captured by in-person surveys. Ticket counter queue length and times are collected on an as-needed basis through the use of camera footage or the use of a survey team. Security checkpoint queue length and times are collected by TSA and through camera footage. Customs and immigration queue lengths and times are collected by United States Customs and Border Protection (CBP) and through camera-based technology. Passenger movement through the terminal before security and post-security can be manually reviewed through cameras. Con- cessionaires report their transactions and revenues to the airport. Employee parking and permit data are collected in the standard parking permit process and placed into an online database. ORD staff indicated that data analysis varies depending on the data type. Some data are received through third-party PDFs and often analyzed using Excel. ORD staff reported that data are collected for a range of reasons, but primarily to support business analytics to understand the airport’s performance, adjust staffing, understand demand at terminals, and plan ahead by understanding current utilization and estimating changes for the future. ORD staff indicated that data on courtesy buses (operated by off-airport hotels and parking operators) are lacking, and they would like more real-time data. ORD staff stated that no legal issues have been encountered with data collection, and data must be stored for 5 years. ORD staff also reported that data from contractors and third-party sources are easily accessible and available. However, staff also reported a challenge with the timeliness of data and lack of holistic data for ground access. Additionally, mobilization to gather data (especially passenger intercept surveys) often requires extra time, delaying the request for data. ORD staff indicated that the need for interagency coordination and cooperation contributes to the ease of access to data and timeliness. To address a roadway congestion issue at Terminal 5, the airport collected traffic volume data, turning movement counts, and signal timing data. A consultant was engaged to analyze the data and model the congestion in a microsimulation model (VISSIM). The VISSIM model was used to test and evaluate the efficacy of potential solutions. Chicago Midway International Airport The City of Chicago, the operator of Chicago Midway International Airport (MDW), indi- cated that total vehicular volume data is collected as needed via camera systems that require manual review. Vehicular volume data by mode and vehicle classification can be collected via surveys as necessary, but these are not done frequently. Wait times for transportation services are collected as needed through cameras and manual review. Curbside dwell times are collected as needed for private vehicles and TNCs and are done quarterly or during busy months. Taxicabs and limousine dwell times are tracked through a ticketing process that identifies when vehicles approach the curbside and when they leave. Ridership of airport-owned shuttles is typically tracked through video counts and reviewed per the shuttle operator’s contractual requirements. The Chicago Transit Authority collects ridership data of public transit, which the airport can request when needed. Ticket counter queue length and times are collected on an as-needed basis through the use of camera footage or the use of a survey team. Security checkpoint queue length and times are collected by TSA and through camera-based technology.

Summary of Interviews with Case Example Airports 57   Customs and immigration queue length and times are collected by CBP and through camera- based technology. Concessionaires report the transactions and revenues to the airport. Employee parking and permit data are collected during the standard parking permit process. MDW staff indicated that data analysis varies depending on the data type. Some data are received through third parties and are often analyzed using Excel. MDW staff reported that data are collected to develop forecasting, ensure that key performance indicators are met, understand capacity, inform capital plan updates, support decisions that affect airlines, ensure that revenue is maximized and captured, and ensure customer service goals and standards are met. MDW staff expressed the desire for data collection to be more automated but understood the amount of capital investment required and the business case necessary to implement an automated data collection system. MDW staff stated that no legal issues have been encountered, and the city’s legal team has addressed any legal issues well. MDW staff also reported that data from contractors and third-party sources are easily accessible and available. Staff also reported the challenge of a non-centralized database of information and the need to reach out to mul- tiple agencies or sources to receive information. Additionally, while data are readily available, staff must understand the availability of all data types to determine what relevant data can be provided. MDW used ground transportation wait times for TNCs to validate customer complaints received regarding the poor level of service provided by TNCs. As part of the evaluation, staff also evaluated the location of the hold lot and the route the vehicle travels to the terminal to have a holistic understanding of the issue. MDW staff then modified TNC operations to meet customer service goals better. Denver International Airport The City and County of Denver, the operator of Denver International Airport (DEN), indi- cated that total bi-directional vehicular volume data are collected using 20 continuous traffic loop detector counters along Pena Blvd, the main access route to the airport. Vehicular volume data, by mode and vehicle classification, can be collected via surveys, typically bi-annual or annually, using Wavetronix camera and radar technology. Additionally, Gatekeeper software processes data on TNCs. Wait times for transportation services are collected as needed through NextGen, the parking access and revenue control system (PARCS), or through Gatekeeper. Curbside dwell times are collected as needed by NextGen. Ridership of airport-owned shuttles is collected annually through the rental car companies and the DEN parking team. The Denver Regional Transportation District provides ridership data for public transit more than once a year. The DEN parking team collects staging/hold lot wait times annually. Ticket counter queue length and times are collected as needed through manual surveys con- ducted by the DEN planning team. TSA collects security checkpoint queue length and times through Livereach Media camera-based technology. Before this technology, data were collected using beacons and Wi-Fi data. Concessionaires report their transactions and revenues to the airport monthly. Employee parking and permit data are collected in the standard parking permit process. DEN staff indicated that data are typically stored in a business intelligence warehouse on a server, extracted using Microsoft tools, and then analyzed using business intelligence tools such as Tableau and PowerBI. After analysis, data are summarized into dashboards. Additional soft- ware DEN staff use includes ESRI for GIS mapping and visual analysis. DEN staff reported that data are collected to ultimately make better decisions overall and empower management to make

58 Airport Landside Data: Collection and Application informed decisions. Staff indicated that all data are important in informing decision-making; however, data are used differently depending on the airport department. DEN staff desire passenger movement and real-time revenue data from concessionaires and retail. Additionally, staff said they want accurate and easy-to-export traffic data, more data on vehicle crashes, and real-time traffic safety information. DEN staff stated that no legal issues have been encountered and data must be stored for 7 years. DEN staff also reported that data from contractor and third-party sources are generally accessible and available. However, staff also reported that they had some challenges in receiving flight schedule data from specific airlines and that GIS data are occasionally delayed or in an incorrect format. While data are typically readily available, staff must access data through an SQL server and parse through data using Excel, which requires a detailed understanding of the data. DEN recently used interterminal train wait time data to inform the decision on train headway times to ensure adequate capacity during peak times. DEN used cameras to count the number of passengers boarding and alighting during peak times. All data were aggregated to inform the operations team monthly to meet customer experience and operational goals. Fort Lauderdale-Hollywood International Airport The County of Broward, the operator of Fort Lauderdale-Hollywood International Airport (FLL), indicated that vehicular volume data are collected by consultants using tube counters. In contrast, specific vehicle classification counts are collected using AVI data, a Gatekeeper system, and self-reported TNC data. Mode choice data can be collected via passenger surveys as needed. Wait times for transportation services are only collected for buses (through GPS) and TNCs, which self-report the wait times between ride requests and the vehicle’s arrival at the pickup location. Curbside dwell times are collected as needed; staff indicated that policy limits TNC dwell times on the curbside to one minute. Ridership of airport-owned shuttles is collected continuously through automated counters and manually supplemented as needed. Ridership data of public transit are provided by Broward County Transit more than once a year. Staging/ hold lot wait times are continuously collected by the airport using an entry and exit automated counter for taxis. Ticket counter queue length and time-in-queue are manually collected as needed by FLL staff. TSA collects security checkpoint queue length and times. Data on passenger movement through the terminal are collected as needed using consultants. However, staff is investigating a new system using camera tracking with AI analytics. Customs and immigration data on wait times and queue lengths are collected continuously by CBP. Concessionaires report the transac- tions, revenues, foot traffic, and customer wait times to the airport monthly. Employee parking and permit data are collected in the standard parking permit process. FLL staff indicated that all employees who work at the airport are badged regardless of work location on the airport. FLL staff indicated that data analysis methods vary depending on the data type. Generally, Tableau is used for daily tracking, while Excel is used for analysis. Staff reported using flight tracking software services such as FlightAware and FlightRadar24 to supplement airline data. FLL staff reported that data are collected for operational decision-making. Specifically, FLL used data to inform staffing level decisions for maintenance, operations, and concessions staff. FLL staff wanted curbside dwell time data to understand passenger behavior better. FLL staff stated that no legal issues have been encountered, and data must be stored for 7 years. FLL staff indicated that the greatest challenge with data collection is the multiple available data sources and collection methods, which can result in inconsistencies. FLL staff also reported that data from contractor and third-party sources are generally accessible and available.

Summary of Interviews with Case Example Airports 59   FLL utilized expected airline load factor data and traffic volume information during the 2022 holiday season to direct drivers to alternative pickup areas on the departure level during high arrival periods and to alternative drop-off areas on the arrivals level during high departure periods. The data were also used to determine staffing levels in the terminal building for pre- dictive and preventive maintenance. Indianapolis International Airport The Indianapolis Airport Authority, Indianapolis International Airport’s (IND) operator, indicated that specific vehicle volume and classification counts are collected using AVI data as commercial vehicles enter the ground transportation center (GTC). Wait times for transpor- tation services are collected as needed. IND utilizes NextBus, or UMO IQ, to determine the airport shuttle wait times and headways. Curbside dwell times are collected as needed. TSA collects security checkpoint queue length and times using automated people counters. Concessions report the monthly transactions, revenues, and customer wait times provided to the airport. Employee parking and permit data are collected in the standard parking permit process. This information is also used to estimate employee mode choice options. IND staff indicated that data analysis varies depending on the data type. Generally, Excel is used for data storage and analysis. Additionally, staff uses vendor-provided software (e.g., ClickView, which is integrated with the parking and revenue control system) to analyze parking data. IND staff reported that data are collected for adherence to records retention laws and for analysis to improve operations management. IND staff indicated their challenge is related to the sample size limitations of passenger surveys. As categories get more specific, sample sizes drop significantly and may not be statistically relevant. Staff indicated that the most important data are those that inform better operational decisions— specifically staffing decisions—based on volume and demand data. IND staff stated that no legal issues have been encountered. IND staff also reported that data from contractor and third-party sources are generally accessible and available. Some third parties are occasionally less willing to share data, requiring staff to follow up. IND recently used traffic volume data and curbside dwell times for TNCs to inform the con- struction of a new TNC dedicated roadway to ensure adequate capacity and meet customer service goals. Another example is using the Airport Service Quality survey results to adjust concessions operation times. Jackson Hole Airport The Jackson Hole Airport Board, the operator of Jackson Hole Airport (JAC), indicated that mode share data are collected using an airport Wi-Fi intercept survey. Vehicle classification data are collected continuously through self-reporting by TNCs and commercial vehicle registration data. Curbside dwell time observational data are collected as needed by JAC staff. Ticket counter queue length and times are collected by JAC staff as needed by manual obser- vation. TSA collects security checkpoint queue length and times. Concessionaires report the transactions and revenues provided to the airport monthly. Employee parking and permit data are collected in the standard parking permit process. JAC staff indicated that the data analysis varies depending on the data type. Generally, Excel is used for data storage and analysis. Staff reported that data are collected to help support the justification for decision-making.

60 Airport Landside Data: Collection and Application JAC staff expressed the desire to gather data on ground transportation services with greater detail, specifically for tracking taxicabs and courtesy shuttles using an LPR system. JAC staff stated that no legal issues have been encountered, and data storage costs are minimal. JAC staff also reported that data from contractors and third-party sources are generally accessible and avail- able. The greatest challenge for JAC is staffing limitations for data analysis. JAC recently used customer survey feedback to encourage the public transit agency to begin service to the airport. JAC staff also recently used parking capacity and transaction data to inform parking rate changes and justify changes to the Airport Board. JAC staff used observational data from ticketing and security queue times and lengths to organically and situationally prioritize passengers. John Wayne Airport The County of Orange, California, the operator of John Wayne Airport (JWA), indicated that specific vehicle volume and classification counts are collected using their AVI system (which consists of TransCore and Gatekeeper). Mode choice data are collected by the public affairs team through a passenger survey every 2 years. TSA collects security checkpoint queue length and times. Customs and immigration data on wait times and queue lengths are collected continuously by CBP. Concessionaires report the transactions, revenues, and customer wait times to the airport monthly. Additionally, JWA staff indicated that through JBT (the airport contractor who maintains the bag belt system), the air- port receives inbound baggage information. Employee parking and permit data are collected in the standard parking permit process. Employee mode choice data are collected annually for Orange County employees using surveys, but the data do not include airline or other airport tenants. JWA staff indicated that the analysis of data varies depending on the type of data collected and who collects the data. Generally, Excel is used for data storage and analysis. JWA staff stated that data are mainly collected for revenue management and generation. Data are typically used to manage roadway operations, commercial vehicle operations, passenger/guest experience, and overall passenger understanding. JWA staff expressed the desire for additional data to be used for understanding customer behavior. Staff indicated that data are collected and used to inform messaging to stakeholders and for operational decisions for tenants, concessionaires, staff, and passenger experience. JWA staff stated that no legal issues have been encountered. JWA staff also reported that data from contractor and third-party sources are generally accessible and available. One of the challenges that JWA encounters is that staff may not be sufficiently familiar with the various data to know how to act on the information. JWA staff recently used data to improve guest experience and craft relevant messaging based on passenger intercept survey data. Phoenix Sky Harbor International Airport The City of Phoenix, the Phoenix Sky Harbor International Airport (PHX) operator, indicated that total vehicular volume data are collected as needed on a project basis. This information was last collected 5 years ago as part of an airport roadway evaluation study. Access mode choice data are collected via holdroom passenger intercept surveys monthly and quarterly. Vehicle classifica- tion data are collected using an AVI system but the system only counts and classifies commercial vehicles registered with the airport. Wait times for TNCs are provided by each operating com- pany, while for other modes of transportation, information is usually anecdotal. PHX collects ridership data for PHX’s SkyTrain. Ridership data of public transit are collected by Valley Metro

Summary of Interviews with Case Example Airports 61   but are typically not requested by the airport. Staging and hold lot wait times are tracked by TNCs, and PHX’s taxicab management contractor is contractually required to track wait times for taxicabs in the hold lots. Airline partners collect ticket counter queue length and times. Security checkpoint queue length and times are collected by TSA and through a sensor-based technology installed in 2016 utilizing Bluetooth and laser/infrared technology. CBP collects customs and immigration queue length and times. Concessionaires report the gross revenues to the airport, but new concession contracts will require that concessionaires provide PHX with transaction-level data in real time using airport-provided standard AVI. Employee parking and permit data are collected in the standard parking permit process. As part of a City of Phoenix sustainability initiative, a yearly survey of PHX’s city staff collects various data about employees, including mode choice data. PHX staff indicated that tools for data analysis vary, and staff often use Excel and Busi- ness Intelligence software. PHX staff reported collecting data to understand the environment, improve the customer journey, inform data-driven decision-making at all levels, and plan daily operations. PHX’s main goal is to be known as America’s friendliest airport by reducing customer stress and improving predictability. The airport is focused on understanding customer prefer- ences and behaviors to improve the customer experience and make it as seamless and hassle-free as possible. By better understanding what is happening in the environment, the airport can plan accordingly and tailor the experience to meet customer needs. PHX has access to a large amount of data, with every line of business utilizing different data sets for decision-making. To establish a data-driven culture, PHX staff indicated that it is neces- sary to collect and analyze customer data to understand general customer perceptions and utilize data for operational improvements, such as staffing and predictive operations. Using granular data to identify passenger volumes and locations can aid in staff utilization and enable proactive decision-making. The data are utilized at the senior level for business decisions and by technical staff for operational improvements. PHX is currently investigating governance related to the use of customer data. While the airport currently uses non-personally identifiable information (PII), the staff are assessing new ways to connect with customers to understand their needs better and provide tailored experi- ences and services. Staff indicated that as the concerns increase with PII data, the airport is taking steps to ensure the proper use and safeguarding of the data. PHX staff indicated that one full-time employee is dedicated to data analytics. PHX staff also reported that data from contractors and third-party sources are generally accessible and avail- able. However, staff have encountered bottlenecks in requesting data from concessionaires that are not a part of the current contract or lease agreements. PHX staff indicated that data are provided in varying formats and transmitted using various methods. Combining those disparate sources is labor-intensive and inefficient; thus, automation is needed to address the challenge of assembly and processing. The knowledge gap in processing data is another challenge that needs to be addressed; for many data sources, specific expertise is required to understand and recognize the data quality. Staff believe that with the current demand from all lines of business, each line of business could benefit from having its own data manage- ment expertise, allowing each to manage the data effectively. In 2022, PHX completed the development of a passenger flow optimization model based on 57 different data sources, including automated and manual sources and airline booking data. PHX uses the flow model to prepare for upcoming passenger activity, including staffing accordingly and planning maintenance and other activities to minimize potential impacts to passengers.

62 Airport Landside Data: Collection and Application The study also resulted in a pilot program initially conducted with one in-terminal concessions operator. PHX provided the concessionaire with model results regarding forecast passenger volumes in each concourse. The forecast allowed the concessionaire to adjust staffing levels and plan for supplies in each location. Now, many stakeholders receive these data to improve their ability to allocate resources and be better prepared to provide the needed level of service in response to projected demand. San Diego International Airport The San Diego Regional Airport Authority, the San Diego International Airport (SAN) operator, indicated that vehicular volume data are collected continuously, and traffic surveys are conducted every 3 to 4 years using tube counters or cameras. Mode share data are collected using a passenger intercept survey every 4 years. Vehicle classification data are provided for commercial vehicles equipped with AVI tags. Wait times for transportation services are collected as needed and can be requested from various contracted third parties. SAN staff indicated that curbside dwell times are collected more than once a year and collection is done manually. Ridership of airport-owned shuttles is contractually provided by the shuttle operators and collected using an automated system. Ridership data of public transit are collected by the airport when needed through surveys typically conducted by interns. These surveys are typically capable of distinguishing between employees and passengers. TSA collects security checkpoint queue length and times, supplemented by the airport’s camera- based technology. Customs and immigration queue lengths and times are collected by CBP and through the airport’s camera-based technology. Concessionaires report the transactions and rev- enues to the airport. Passenger accumulation data are collected using beacons and Wi-Fi pings. This system is currently limited to specific locations within the terminal. Staff have indicated that this system will expand to monitor and collect data from the entire terminal. Employee parking and permit data are collected in the standard parking permit process and placed into an online database. Employee mode choice data are collected annually through a survey distributed to employees. SAN staff indicated that data analysis varies depending on the data type. Tableau is used for dashboard summaries, and Excel is typically used for data analysis. SAN staff reported that data are collected for decision-making, focusing on business cases. SAN has three to four full-time staff dedicated to data analytics. SAN staff indicated that data on public transit to the airport are limited and would ideally be used to provide a business case for improved public transit. SAN staff stated that no legal issues have been encountered. SAN staff also reported that data from contractor and third-party sources are easily accessible and available. SAN used traffic volume data for TNCs and taxicabs to inform the capacity needed for the hold lot and locating the facility.

Abbreviations and acronyms used without de nitions in TRB publications: A4A Airlines for America AAAE American Association of Airport Executives AASHO American Association of State Highway Officials AASHTO American Association of State Highway and Transportation Officials ACI–NA Airports Council International–North America ACRP Airport Cooperative Research Program ADA Americans with Disabilities Act APTA American Public Transportation Association ASCE American Society of Civil Engineers ASME American Society of Mechanical Engineers ASTM American Society for Testing and Materials ATA American Trucking Associations CTAA Community Transportation Association of America CTBSSP Commercial Truck and Bus Safety Synthesis Program DHS Department of Homeland Security DOE Department of Energy EPA Environmental Protection Agency FAA Federal Aviation Administration FAST Fixing America’s Surface Transportation Act (2015) FHWA Federal Highway Administration FMCSA Federal Motor Carrier Safety Administration FRA Federal Railroad Administration FTA Federal Transit Administration GHSA Governors Highway Safety Association HMCRP Hazardous Materials Cooperative Research Program IEEE Institute of Electrical and Electronics Engineers ISTEA Intermodal Surface Transportation Efficiency Act of 1991 ITE Institute of Transportation Engineers MAP-21 Moving Ahead for Progress in the 21st Century Act (2012) NASA National Aeronautics and Space Administration NASAO National Association of State Aviation Officials NCFRP National Cooperative Freight Research Program NCHRP National Cooperative Highway Research Program NHTSA National Highway Traffic Safety Administration NTSB National Transportation Safety Board PHMSA Pipeline and Hazardous Materials Safety Administration RITA Research and Innovative Technology Administration SAE Society of Automotive Engineers SAFETEA-LU Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users (2005) TCRP Transit Cooperative Research Program TEA-21 Transportation Equity Act for the 21st Century (1998) TRB Transportation Research Board TSA Transportation Security Administration U.S. DOT United States Department of Transportation

Transportation Research Board 500 Fifth Street, NW Washington, DC 20001 ADDRESS SERVICE REQUESTED ISBN 978-0-309-70924-8 9 7 8 0 3 0 9 7 0 9 2 4 8 9 0 0 0 0

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Airports collect data to help understand the customer journey from the entrance or access points of the airport to the boarding gates. Processes may change in order to improve the customer experience when the collected data are analyzed.

ACRP Synthesis 132: Airport Landside Data: Collection and Application, from TRB's Airport Cooperative Research Program, documents landside data, collection methods, analysis, and interpretation and discusses how that information affects airport decision-making.

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