<p>Different security issues are a top subject around the world, especially since the terror threats seem to intensify. In the same time, the transport industry suffer from problems with smuggling and theft of valuable goods. One way to increase the security might be to have a verification system installed in commercial trucks, in order to assure that the driver is the proper one.</p><p>This thesis has two purposes. One is to find appropriate methods for driver verification and build a prototype of a verification system which can be used for testing and further development. The other is to study how truck drivers perceive such a system and how their conception goes along with the growing demand for higher security. The present work is the result of a cooperation between an engineer and a cognitive scientist. The thesis focuses on the transport industry and was performed for Volvo Technology Corporation (VTEC), Gothenburg, Sweden.</p><p>Eleven available verification methods were studied. To enable a well-based selection of methods to implement in the prototype, inquiries and interviews with truck drivers and haulage contractors were carried out to complement the theoretical study. </p><p>One regular and three biometric verification methods were chosen for the test; fingerprint verification, face recognition, voice recognition and PIN verification. These methods were put together to a prototype system that was implemented in a truck simulator. A graphical user interface was developed in order to make the system user friendly. The prototype system was tested by 18 truck drivers. They were thoroughly interviewed before and after the test in order to retrieve their background, expectations and opinions as well as their perceptions and experiences of the test. </p><p>Most of the test participants were positive to the prototype system. Even though they did not feel a need for it today they believed it to “be the future”. However, some participants felt uncomfortable with the system since they felt controlled by it. It became clear how important it is to have a system that respect the users’ privacy and to assure that the users are well informed about how the system is used. Some of the technology used for the verification system requires more development to fit in the automotive context, but it is considered to be possible to achieve a secure and robust system.</p>

Different security issues are a top subject around the world, especially since the terror threats seem to intensify. In the same time, the transport industry suffer from problems with smuggling and theft of valuable goods. One way to increase the security might be to have a verification system installed in commercial trucks, in order to assure that the driver is the proper one. This thesis has two purposes. One is to find appropriate methods for driver verification and build a prototype of a verification system which can be used for testing and further development. The other is to study how truck drivers perceive such a system and how their conception goes along with the growing demand for higher security. The present work is the result of a cooperation between an engineer and a cognitive scientist. The thesis focuses on the transport industry and was performed for Volvo Technology Corporation (VTEC), Gothenburg, Sweden. Eleven available verification methods were studied. To enable a well-based selection of methods to implement in the prototype, inquiries and interviews with truck drivers and haulage contractors were carried out to complement the theoretical study. One regular and three biometric verification methods were chosen for the test; fingerprint verification, face recognition, voice recognition and PIN verification. These methods were put together to a prototype system that was implemented in a truck simulator. A graphical user interface was developed in order to make the system user friendly. The prototype system was tested by 18 truck drivers. They were thoroughly interviewed before and after the test in order to retrieve their background, expectations and opinions as well as their perceptions and experiences of the test. Most of the test participants were positive to the prototype system. Even though they did not feel a need for it today they believed it to “be the future”. However, some participants felt uncomfortable with the system since they felt controlled by it. It became clear how important it is to have a system that respect the users’ privacy and to assure that the users are well informed about how the system is used. Some of the technology used for the verification system requires more development to fit in the automotive context, but it is considered to be possible to achieve a secure and robust system.

Identity verification systems are an important part of our every day life. A typical example is the Automatic Teller Machine (ATM) which employs a simple identity verification scheme: the user is asked to enter their secret password after inserting their ATM card; if the password matches the one prescribed to the card, the user is allowed access to their bank account. This scheme suffers from a major drawback: only the validity of the combination of a certain possession (the ATM card) and certain knowledge (the password) is verified. The ATM card can be lost or stolen, and the password can be compromised. Thus new verification methods have emerged, where the password has either been replaced by, or used in addition to, biometrics such as the person’s speech, face image or fingerprints. Apart from the ATM example described above, biometrics can be applied to other areas, such as telephone & internet based banking, airline reservations & check-in, as well as forensic work and law enforcement applications. Biometric systems based on face images and/or speech signals have been shown to be quite effective. However, their performance easily degrades in the presence of a mismatch between training and testing conditions. For speech based systems this is usually in the form of channel distortion and/or ambient noise; for face based systems it can be in the form of a change in the illumination direction. A system which uses more than one biometric at the same time is known as a multi-modal verification system; it is often comprised of several modality experts and a decision stage. Since a multi-modal system uses complimentary discriminative information, lower error rates can be achieved; moreover, such a system can also be more robust, since the contribution of the modality affected by environmental conditions can be decreased. This thesis makes several contributions aimed at increasing the robustness of single- and multi-modal verification systems. Some of the major contributions are listed below. The robustness of a speech based system to ambient noise is increased by using Maximum Auto-Correlation Value (MACV) features, which utilize information from the source part of the speech signal. A new facial feature extraction technique is proposed (termed DCT-mod2), which utilizes polynomial coefficients derived from 2D Discrete Cosine Transform (DCT) coefficients of spatially neighbouring blocks. The DCT-mod2 features are shown to be robust to an illumination direction change as well as being over 80 times quicker to compute than 2D Gabor wavelet derived features. The fragility of Principal Component Analysis (PCA) derived features to an illumination direction change is solved by introducing a pre-processing step utilizing the DCT-mod2 feature extraction. We show that the enhanced PCA technique retains all the positive aspects of traditional PCA (that is, robustness to compression artefacts and white Gaussian noise) while also being robust to the illumination direction change. Several new methods, for use in fusion of speech and face information under noisy conditions, are proposed; these include a weight adjustment procedure, which explicitly measures the quality of the speech signal, and a decision stage comprised of a structurally noise resistant piece-wise linear classifier, which attempts to minimize the effects of noisy conditions via structural constraints on the decision boundary.