Baggage Screening Research Articles

Metacognitive Judgments in a Simulated Luggage Screening Task

A pair of experiments examined the accuracy and potential role of predictive metacognitive judgments in a simulated baggage screening task. Procedure was modeled after the ease-of-learning task (Underwood, 1966). Subjects searched for knives hidden in x-ray images of passenger bags. Before performing the search task, subjects viewed each stimulus without the embedded target and rated the likelihood of finding the target if it was hidden in that image. Experiment 1 used a 2IFC search task. Experiment 2 used a speeded yes-no search procedure. Results suggest that predictive metacognitive judgments are only modestly accurate, but that the information on which such judgments are based is nonetheless used to regulate search behavior

Effects of Automation Failure in a Luggage Screening Task: A Comparison between Direct and Indirect Cueing

The present study investigated the use of two automated aids of different reliabilities in a luggage screening task. A Direct Cue consisting of a green circle around a potential target directs attention to a specific part of the luggage image, while an Indirect Cue, consisting of a green border around an image determined to have a target, does not. Direct Cues offer an advantage in visual inspection tasks because they guide attention to specific areas of the visual image but this can also cause attentional tunneling. Furthermore, the reliance on automation may negatively impact manual performance after the aid is removed or is no longer available. Thus, two issues were investigated in the current study: (1) how do failures in Direct and Indirect Cues affect reliance and (2) how does a complete failure affect performance after operators had the use of an automated aid? Results suggest that reliance patterns were more optimal with the Direct Cue than with the Indirect Cue and performance with a more reliable Indirect Cue was not much better than a less reliable one. The results also suggest that manual performance, when the aid was removed, was better for participants who had used the automated aids compared to control participants who did not have any use of the aid previously. The advantage of previously aided performance on subsequent manual performance was greatest for those who had used the more reliable Direct Cue. Explanations and implications are discussed.

Weapons Detection System for Airport Baggage Screening

Weapons Detection System for Airport Baggage Screening

Watching Single Cells Pay Attention

Visual search is a task that each of us rapidly and efficiently performs a thousand times a day, from searching for a coffee cup to looking for a face in a crowd. As a society, we have created many artificial and imperfect but critically important search tasks, such as airport baggage screening and routine mammography. In his Perspective, [Wolfe][1] discusses new work ([ Bichot et al .][2]) that provides insights into how the primate brain performs complex visual search tasks, which might shed light on ways to improve the imperfect artificial search tasks on which we all depend. [1]: http://www.sciencemag.org/cgi/content/full/308/5721/503 [2]: http://www.sciencemag.org/cgi/content/short/308/5721/529

The Impact of Post 9/11 Airport Security Measures on the Demand for Air Travel

We examine the impact of post-9/11 airport security measures on air travel in the U.S. Using five years of data on passenger volume, we evaluate the effects of the implementation of baggage screening and the federalization of passenger screening on the demand for air travel. These two congressionally mandated measures are the most visible changes in airport security following the 9/11 attacks. Exploiting the phased introduction of security measures across airports, we find that baggage screening reduced passenger volume by about five percent on all flights, and by about eight percent on flights departing from the nations fifty busiest airports. In contrast, federalizing passenger screening had little effect on passenger volume. We provide evidence that the reduction in demand was an unintended consequence of baggage screening and not the result of contemporaneous price changes, airport-specific shocks, or other factors. Moreover, this decline in air travel has substantial welfare implications. Back-of-the-envelope calculations indicate that the airline industry lost about $1.1 billion, a tenth of the projected revenue lost because of 9/11 itself. Similar calculations show that the substitution of driving for flying by those seeking to avoid security inconvenience likely lead to over 100 road fatalities.

Assessing the impact of deterrence on aviation checked baggage screening strategies

This paper analyses checked baggage screening strategies that incorporate the effects of deterrence on explosive detection systems (EDSs) deployed at airports. Cost models for these strategies are presented that incorporate the cost of purchasing, operating, and maintaining an EDS, the number of checked bags available to be screened, and the numbers of selectees and non-selectees checked bags actually screened over a one-year period. The model also includes the effect of deterrence on the level of threat at an airport. The cost models provide a quantitative tool to assess the strategy of 100% screening of all checked bags, as set forth by the USA Aviation and Transportation Security Act. Comparing the expected direct cost per expected prevented attack to the expected cost of an aviation terrorist incident provides an indication of the cost effectiveness of 100% checked bag screening.

Modeling and analyzing multiple station baggage screening security system performance

AbstractIn the aftermath of the tragic events of 11 September 2001, numerous changes have been made to aviation security policy and operations throughout the nation's airports. The allocation and utilization of checked baggage screening devices is a critical component in aviation security systems. This paper formulates problems that model multiple sets of flights originating from multiple stations (e.g., airports, terminals), where the objective is to optimize a baggage screening performance measure subject to a finite amount of resources. These measures include uncovered flight segments (UFS) and uncovered passenger segments (UPS). Three types of multiple station security problems are identified and their computational complexity is established. The problems are illustrated on two examples that use data extracted from the Official Airline Guide. The examples indicate that the problems can provide widely varying solutions based on the type of performance measure used and the restrictions imposed by the security device allocations. Moreover, the examples suggest that the allocations based on the UFS measure also provide reasonable solutions with respect to the UPS measure; however, the reverse may not be the case. This suggests that the UFS measure may provide more robust screening device allocations. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2005.

The key design parameters of checked baggage security screening systems in airports

In an effort to meet the checked baggage screening explosive detection deadline established by the Aviation and Transportation Security Act, the Transportation Security Administration placed hundreds of explosives detection system machines and thousands of explosives trace detection machines in airport check-in areas across the country as short-term solutions. To effectively integrate explosives detection system machines into the air transportation operations, numerous objectives must be balanced, including equipment cost, passenger and baggage demand, screening capacity, and security effectiveness. As a result, the Transportation Security Administration and its industry partners will need to increasingly rely on computer models, which offer the opportunity to examine the various complexities of the airport environment in a non-intrusive way, and to estimate the operational impact of new security equipment, policies, and procedures. While Transportation Security Administration, along with the airport community, is stimulating research in this area, it remains relatively undeveloped. Thus, the purpose of the research is to identify and evaluate the key design parameters of checked baggage screening, and to develop an analytical model that will determine the optimal number of explosives detection system equipment based on passenger demand levels and security protocols.

High “Back Injury” Rate Among Airport Baggage Screeners

High “Back Injury” Rate Among Airport Baggage Screeners

Effects of Age on Utilization and Perceived Reliability of an Automated Decision-Making aid for Luggage Screening

An experiment examined the effects of age on utilization and perceived reliability of an imperfectly reliable decision-making aid in a luggage x-ray screening task. Forty-five young adults and 45 elderly adults performed a simulated luggage screening task. Some subjects were provided the assistance of an automated decision aid with a hit rate of .90 and a false alarm rate of .25. Others performed the task with no aid. Signal-detection analysis revealed that automation improved sensitivity only for younger participants, suggesting a tendency for older participants to underutilize the aid's recommendations. Data also revealed unique patterns of individual differences in cue reliance among older and younger participants. Perceived reliability of the aid did not differ between age groups. Order of information presentation (with the aid's recommendation coming before or after the raw data) had little effect for either age group.

Analyzing the cost of screening selectee and non-selectee baggage.

Determining how to effectively operate security devices is as important to overall system performance as developing more sensitive security devices. In light of recent federal mandates for 100% screening of all checked baggage, this research studies the trade-offs between screening only selectee checked baggage and screening both selectee and non-selectee checked baggage for a single baggage screening security device deployed at an airport. This trade-off is represented using a cost model that incorporates the cost of the baggage screening security device, the volume of checked baggage processed through the device, and the outcomes that occur when the device is used. The cost model captures the cost of deploying, maintaining, and operating a single baggage screening security device over a one-year period. The study concludes that as excess baggage screening capacity is used to screen non-selectee checked bags, the expected annual cost increases, the expected annual cost per checked bag screened decreases, and the expected annual cost per expected number of threats detected in the checked bags screened increases. These results indicate that the marginal increase in security per dollar spent is significantly lower when non-selectee checked bags are screened than when only selectee checked bags are screened.

Designing optimal aviation baggage screening strategies using simulated annealing

Terrorist activities are a critical threat to domestic aviation security. Current aviation security models created to address this threat are descriptive rather than prescriptive; they evaluate a given baggage screening strategy rather than identify optimal baggage screening strategies. Moreover, these models only incorporate costs associated with purchasing and operating baggage screening security devices. This research introduces a comprehensive cost function that not only includes direct costs associated with the purchase and operation of baggage screening security devices, but also includes indirect costs associated with device errors. A methodology is presented to determine the best selection of baggage screening security devices that minimizes the expected annual total cost of a baggage screening strategy. Computational experiments with this methodology are presented. Scope and purpose This research presents an optimization-based tool for designing effective aviation security systems. The tool uses a broader cost model than previous tools. It also uses a simulated annealing heuristic to identify lower cost system configurations. This study evaluates the tool's performance for a set of input parameter values in order to recommend appropriate settings for practical use of the tool.

Modeling aviation baggage screening security systems: a case study

Aviation security protects vital national interests, as well as passengers and aircraft. Key components of an aviation security system include baggage and passenger screening devices and operations. Determining how and where to assign (deploy) such devices can be quite challenging. Moreover, even after such systems are in place, it can be difficult to measure their effectiveness. This paper describes how discrete optimization models can be used to address these questions, based on three performance measures that quantify the effectiveness of airport baggage screening security device systems. These models are used to solve for optimal airport baggage screening security device deployments considering the number of passengers on a set of flights who have not been cleared using a security risk assessment system in use by the Federal Aviation Administration (i.e., passengers whose baggage is subjected to screening), the number of flights in this set, and the size of the aircraft for such flights. Several examples are provided to illustrate these results, including an example that uses data available from the Official Airline Guide.

Using Cognitive Theory to Enhance Aviation Security X-Ray Screening

A fundamental part of the aviation security process is ‘baggage screening’. Aviation security screeners are required to search for threat items within an X-ray image. The task is complex, demanding, involves perceptual and cognitive components and is vital to ensure the safety of the travelling public. QinetiQ CHS has undertaken a research programme, sponsored by Transport Security Division of the UK Department for Transport, to investigate the nature of screener expertise and to develop technologies that will support this expertise. This paper outlines recent findings and discusses support technologies that have been produced as a consequence of this research.

Taking on terrorism

The 11th day of September 2001 began with a tragedy beyond comprehension. It ended in a cacophony of outrage, blame, and urgent questions. How could so few terrorists create death and destruction on so massive a scale? How could US intelligence services have been caught so off guard? Can technology help prevent such attacks in the future, or at least respond to them more effectively if they do occur? A year after the strikes, answers to these questions are finally starting to take shape. The focus here is on the use of technology as a pillar of future counter-terrorism-from the advanced screening equipment now being installed at airports around the world to the robust emergency communications systems that will link workers and officials after any future calamities. Although the attacks prompted a broad array of technology initiatives, some of the most significant have been in intelligence, airport baggage screening, postal monitoring, biometric identification, radio and television broadcasting, hardened emergency communications, and personal security.

Delayed arrival for US baggage screening?

The US Department of Transportation (DOT) calculates that 2200 explosives-detecting luggage scanners will be needed to equip all 429 civilian airports in the United States by 31 December 2002, as required by the Aviation and Transportation Security Act passed in the wake of 11 September. But earlier in 2002, when the act's new baggage security rules took effect, only 161 of the machines needed to automatically scan checked baggage had been installed. That means airports have less, than a year to install the other 2039, to be built by just two manufacturers approved by the US Federal Aviation Administration (FAA): InVision Technologies (Newark, Calif.) and L-3 Communications Corp. (New York City). An EDS machine takes a series of X-ray cross-sections of a bag traveling through it on a conveyor belt. As the X-ray machine rotates around the bag, the machine integrates the sections into a near-three-dimensional composite picture, and highlights suspicious objects to be checked manually. This article briefly discusses how the authorities are hedging over the year-end dead-line and how the manufacturers are scrambling to meet the same deadline. Other concerns discusses in the article include finding space for the machines at airports and procedures for getting baggage in and out of the machines.

Outgoing selectee rates at hub airports

Abstract The selectee rate at an airport, or the fraction of originating passengers at an airport that have not been cleared by the computer-aided passenger prescreening system, may be useful in determining where to deploy certain baggage screening security devices. At hub airports, this rate alone does not capture the selectee rate of outgoing passengers, which consists of both originating passengers and transferring passengers. The impact of transferring passengers on the outgoing selectee rate is needed to optimally deploy baggage screening security devices at airports. This paper introduces a methodology for computing the outgoing selectee rates for a set of (hub and non-hub) airports and to quantify the impact of transferring selectees at airports. Different types of selectee rates are defined and relationships between selectee rates for a set of airports and within an airport are discussed. Based on these relationships, two approaches for computing the outgoing selectee rates are presented. The resulting formulations, the exact formulation and the approximate formulation, are illustrated and compared using several examples, including a real-world example with data from the official airline guide. The methodology introduced in this paper can be used to determine which individual airports pose the greatest threat from selectee passengers to the entire system of airports, hence can be used to aid in the deployment of baggage screening security devices at airports.

Learning symbolic descriptions of shape for object recognition in X-ray images

In this paper we describe a method for learning shape descriptions of objects in X-ray images. The descriptions are induced from shape examples using the AQ15c inductive learning system. The method has been experimentally compared to k-nearest neighbor, a statistical pattern recognition technique, the C4.5 decision tree learning program, and a multilayer feed-forward neural network. Experimental results demonstrate strong advantages of the AQ methodology over the other methods. Specifically, the method has higher predictive accuracy and faster learning and recognition rates. AQ's representation language, VL 1, was better suited for this problem, which can be seen by examining the empirical results and the learned rules. The method was applied to the problem of detecting blasting caps in X-ray images of luggage. An intelligent system performing this detection task can be used to assist airport security personnel with luggage screening.