Australasian horror special issue editorial : putting Australian and New Zealand horror movies on the map of cinema studies

This Australasian horror special issue is an important step forward in putting Australian and New Zealand horror movies on the map of film and cinema studies as a subject worthy of intellectual debate. The journal issue is the first devoted solely to the academic discussion of Australasian horror movies. While an Australian horror movie tradition has produced numerous titles since the 1970s achieving commercial success and cult popularity worldwide, the horror genre is largely missing from Australian film history. While there have been occasional essays on standout titles such as Wolf Creek (Mclean, 2005), an increasing number of articles on ‘Ozploitation’ movies, and irregular discussion about Australian Gothic, overall the nature of Australian horror as a genre remains poorly understood. In terms of New Zealand, debate has tended to revolve around ‘Kiwi Gothic’ and of course Peter Jackon’s early splatter films, rather than Kiwi horror as a specific filmmaking tradition.

Idealistic quantum psychopathology : a way forward?

Quantum psychopathology holds the so called “quantum mind” hypothesis, which is controversial. In addition, this hypothesis focuses attention onto quantum processes in the brain, and how this may relate to psychopathological issues. This is very “low level”. As a consequence, it is challenging to form bridges to “higher level” problems related to psychopathology. By adopting the stance used in the quantum interaction community or researchers, this reply puts forward the idea that an idealistic approach may circumvent the controversy and opens the way for addressing challenges at higher levels of psychopathology.

A critical analysis of sperm donation practices : the personal and social effects of disrupting the unity of biological and social relatedness for the offspring

This thesis critically analyses sperm donation practices from a child-centred perspective. It examines the effects, both personal and social, of disrupting the unity of biological and social relatedness in families affected by donor conception. It examines how disruption is facilitated by a process of mediation which is detailed using a model provided by Sunderland (2002). This model identifies mediating movements - alienation, translation, re-contextualisation and absorption - which help to explain the powerful and dominating material, and social and political processes which occur in biotechnology, or in reproductive technology in this case. The understanding of such movements and mediation of meanings is inspired by the complementary work of Silverstone (1999) and Sunderland. This model allows for a more critical appreciation of the movement of meaning from previously inalienable aspects of life to alienable products through biotechnology (Sunderland, 2002). Once this mediation in donor conception is subjected to critical examination here, it is then approached from different angles of investigation. The thesis posits that two conflicting notions of the self are being applied to fertility-frustrated adults and the offspring of reproductive interventions. Adults using reproductive interventions receive support to maximise their genetic continuity, but in so doing they create and dismiss the corresponding genetic discontinuity produced for the offspring. The offspring’s kinship and identity are then framed through an experimental postmodernist notion, presenting them as social rather than innate constructs. The adults using the reproductive intervention, on the other hand, have their identity and kinship continuity framed and supported as normative, innate, and based on genetic connection. This use of shifting frameworks is presented as unjust and harmful, creating double standards and a corrosion of kinship values, connection and intelligibility between generations; indeed, it is put forward as adult-centric. The analysis of other forms of human kinship dislocation provided by this thesis explores an under-utilised resource which is used to counter the commonly held opinion that any disruption of social and genetic relatedness for donor offspring is insignificant. The experiences of adoption and the stolen generations are used to inform understanding of the personal and social effects of such kinship disruption and potential reunion for donor offspring. These examples, along with laws governing international human rights, further strengthen the appeal here for normative principles and protections based on collective knowledge and standards to be applied to children of reproductive technology. The thesis presents the argument that the framing and regulation of reproductive technology is excessively influenced by industry providers and users. The interests of these parties collide with and corrode any accurate assessments and protections afforded to the children of reproductive technology. The thesis seeks to counter such encroachments and concludes by presenting these protections, frameworks, and human experiences as resources which can help to address the problems created for the offspring of such reproductive interventions, thereby illustrating why these reproductive interventions should be discontinued.

Driver behaviour and decision making at railway level crossings : An exploratory on-road case study

Crashes at rail level crossings represent a significant problem, both in Australia and worldwide. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles, now provide researchers with the opportunity to further understand driver behaviour at rail level crossings in ways not previously possible. This paper gives an overview of a recent on-road pilot study of driver behaviour at rail level crossings in which 25 participants drove a pre-determined route, incorporating 4 rail level crossings, using MUARC's instrumented On-Road Test Vehicle (ORTeV). Drivers provided verbal commentary whilst driving the route, and a range of other data were collected, including eye fixations, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. Extracts from the wider analyses are used to examine in depth driver behaviour at one of the rail level crossings encountered during the study. The analysis presented, along with the overall analysis undertaken, gives insight into the driver and wider systems factors that shape behaviour at rail level crossings, and highlights the utility of using a multi-method, instrumented vehicle approach for gathering data regarding driver behaviour in different contexts.

Kava and St. John's wort : current evidence for use in mood and anxiety disorders

Background: Mood and anxiety disorders pose significant health burdens on the community. Kava and St John’s wort (SJW) are the most commonly used herbal medicines in the treatment of anxiety and depressive disorders, respectively. Objectives: To conduct a comprehensive review of kava and SJW, to review any evidence of efficacy, mode of action, pharmacokinetics, safety and use in Major Depressive Disorder (MDD), Bipolar Disorder (BP), Seasonal Affective Disorder (SAD), Generalized Anxiety Disorder (GAD), Social Phobia (SP), Panic Disorder (PD), Obsessive-Compulsive Disorder (OCD), and Post Traumatic Stress Disorder (PTSD). Methods: A systematic review was conducted using the electronic databases MEDLINE, CINAHL, and The Cochrane Library during late 2008. The search criteria involved mood and anxiety disorder search terms in combination with kava, Piper methysticum, kavalactones, St John’s wort, Hypericum perforatum, hypericin and hyperforin. Additional search criteria for safety, pharmacodynamics , and pharmacokinetics was employed. A subsequent forward search was conducted of the papers using Web of Science cited reference search. Results: Current evidence supports the use of SJW in treating mild-moderate depression, and for kava in treatment of generalized anxiety. In respect to the other disorders, only weak preliminary evidence exists for use of SJW in SAD. Currently there is no published human trial on use of kava in affective disorders, or in OCD, PTSD, PD or SP. These disorders constitute potential applications that warrant exploration. Conclusions: Current evidence for herbal medicines in the treatment of depression and anxiety only supports the use of Hypericum perforatum for depression, and Piper methysticum for generalized anxiety.

Development of rapid and highly resolving combinatorial genotyping schemes for Campylobacter jejuni and Campylobacter coli

Campylobacter jejuni followed by Campylobacter coli contribute substantially to the economic and public health burden attributed to food-borne infections in Australia. Genotypic characterisation of isolates has provided new insights into the epidemiology and pathogenesis of C. jejuni and C. coli. However, currently available methods are not conducive to large scale epidemiological investigations that are necessary to elucidate the global epidemiology of these common food-borne pathogens. This research aims to develop high resolution C. jejuni and C. coli genotyping schemes that are convenient for high throughput applications. Real-time PCR and High Resolution Melt (HRM) analysis are fundamental to the genotyping schemes developed in this study and enable rapid, cost effective, interrogation of a range of different polymorphic sites within the Campylobacter genome. While the sources and routes of transmission of campylobacters are unclear, handling and consumption of poultry meat is frequently associated with human campylobacteriosis in Australia. Therefore, chicken derived C. jejuni and C. coli isolates were used to develop and verify the methods described in this study. The first aim of this study describes the application of MLST-SNP (Multi Locus Sequence Typing Single Nucleotide Polymorphisms) + binary typing to 87 chicken C. jejuni isolates using real-time PCR analysis. These typing schemes were developed previously by our research group using isolates from campylobacteriosis patients. This present study showed that SNP + binary typing alone or in combination are effective at detecting epidemiological linkage between chicken derived Campylobacter isolates and enable data comparisons with other MLST based investigations. SNP + binary types obtained from chicken isolates in this study were compared with a previously SNP + binary and MLST typed set of human isolates. Common genotypes between the two collections of isolates were identified and ST-524 represented a clone that could be worth monitoring in the chicken meat industry. In contrast, ST-48, mainly associated with bovine hosts, was abundant in the human isolates. This genotype was, however, absent in the chicken isolates, indicating the role of non-poultry sources in causing human Campylobacter infections. This demonstrates the potential application of SNP + binary typing for epidemiological investigations and source tracing. While MLST SNPs and binary genes comprise the more stable backbone of the Campylobacter genome and are indicative of long term epidemiological linkage of the isolates, the development of a High Resolution Melt (HRM) based curve analysis method to interrogate the hypervariable Campylobacter flagellin encoding gene (flaA) is described in Aim 2 of this study. The flaA gene product appears to be an important pathogenicity determinant of campylobacters and is therefore a popular target for genotyping, especially for short term epidemiological studies such as outbreak investigations. HRM curve analysis based flaA interrogation is a single-step closed-tube method that provides portable data that can be easily shared and accessed. Critical to the development of flaA HRM was the use of flaA specific primers that did not amplify the flaB gene. HRM curve analysis flaA interrogation was successful at discriminating the 47 sequence variants identified within the 87 C. jejuni and 15 C. coli isolates and correlated to the epidemiological background of the isolates. In the combinatorial format, the resolving power of flaA was additive to that of SNP + binary typing and CRISPR (Clustered regularly spaced short Palindromic repeats) HRM and fits the PHRANA (Progressive hierarchical resolving assays using nucleic acids) approach for genotyping. The use of statistical methods to analyse the HRM data enhanced sophistication of the method. Therefore, flaA HRM is a rapid and cost effective alternative to gel- or sequence-based flaA typing schemes. Aim 3 of this study describes the development of a novel bioinformatics driven method to interrogate Campylobacter MLST gene fragments using HRM, and is called ‘SNP Nucleated Minim MLST’ or ‘Minim typing’. The method involves HRM interrogation of MLST fragments that encompass highly informative “Nucleating SNPS” to ensure high resolution. Selection of fragments potentially suited to HRM analysis was conducted in silico using i) “Minimum SNPs” and ii) the new ’HRMtype’ software packages. Species specific sets of six “Nucleating SNPs” and six HRM fragments were identified for both C. jejuni and C. coli to ensure high typeability and resolution relevant to the MLST database. ‘Minim typing’ was tested empirically by typing 15 C. jejuni and five C. coli isolates. The association of clonal complexes (CC) to each isolate by ‘Minim typing’ and SNP + binary typing were used to compare the two MLST interrogation schemes. The CCs linked with each C. jejuni isolate were consistent for both methods. Thus, ‘Minim typing’ is an efficient and cost effective method to interrogate MLST genes. However, it is not expected to be independent, or meet the resolution of, sequence based MLST gene interrogation. ‘Minim typing’ in combination with flaA HRM is envisaged to comprise a highly resolving combinatorial typing scheme developed around the HRM platform and is amenable to automation and multiplexing. The genotyping techniques described in this thesis involve the combinatorial interrogation of differentially evolving genetic markers on the unified real-time PCR and HRM platform. They provide high resolution and are simple, cost effective and ideally suited to rapid and high throughput genotyping for these common food-borne pathogens.

Water sensitive urban design in landscape projects in Shijiazhuang and Yueyang in China [水敏性城市设计 (WSUD) 策略及景观项目中的应用 (中国石家莊和中國岳陽)]

With the rapid urbanization progress, water resources protection and water pollution control have become key problems of human environment construction and social sustainable development. Many countries, especially Australia, have mature experiences. Water Sensitive Urban Design (WSUD) is one of the successful strategies that is put forward under this global situation and helps releasing heavy environmental pressure from urbanization. The paper discussed main principles of WSUD and then took Shijiazhuang, Heibei and Yueng, Hunan for examples trying to apply WSUD in river landscape projects in China's new urban area, thus doing contributions to more sustainable water management in new urban areas in China.

Combined optic-flow and stereo-based navigation of urban canyons for a UAV

We present a novel vision-based technique for navigating an Unmanned Aerial Vehicle (UAV) through urban canyons. Our technique relies on both optic flow and stereo vision information. We show that the combination of stereo and optic-flow (stereo-flow) is more effective at navigating urban canyons than either technique alone. Optic flow from a pair of sideways-looking cameras is used to stay centered in a canyon and initiate turns at junctions, while stereo vision from a forward-facing stereo head is used to avoid obstacles to the front. The technique was tested in full on an autonomous tractor at CSIRO and in part on the USC autonomous helicopter. Experimental results are presented from these two robotic platforms operating in outdoor environments. We show that the autonomous tractor can navigate urban canyons using stereoflow, and that the autonomous helicopter can turn away from obstacles to the side using optic flow. In addition, preliminary results show that a single pair of forward-facing fisheye cameras can be used for both stereo and optic flow. The center portions of the fisheye images are used for stereo, while flow is measured in the periphery of the images.

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

Spectral coding methods for speech compression and speaker identification

This thesis investigates aspects of encoding the speech spectrum at low bit rates, with extensions to the effect of such coding on automatic speaker identification. Vector quantization (VQ) is a technique for jointly quantizing a block of samples at once, in order to reduce the bit rate of a coding system. The major drawback in using VQ is the complexity of the encoder. Recent research has indicated the potential applicability of the VQ method to speech when product code vector quantization (PCVQ) techniques are utilized. The focus of this research is the efficient representation, calculation and utilization of the speech model as stored in the PCVQ codebook. In this thesis, several VQ approaches are evaluated, and the efficacy of two training algorithms is compared experimentally. It is then shown that these productcode vector quantization algorithms may be augmented with lossless compression algorithms, thus yielding an improved overall compression rate. An approach using a statistical model for the vector codebook indices for subsequent lossless compression is introduced. This coupling of lossy compression and lossless compression enables further compression gain. It is demonstrated that this approach is able to reduce the bit rate requirement from the current 24 bits per 20 millisecond frame to below 20, using a standard spectral distortion metric for comparison. Several fast-search VQ methods for use in speech spectrum coding have been evaluated. The usefulness of fast-search algorithms is highly dependent upon the source characteristics and, although previous research has been undertaken for coding of images using VQ codebooks trained with the source samples directly, the product-code structured codebooks for speech spectrum quantization place new constraints on the search methodology. The second major focus of the research is an investigation of the effect of lowrate spectral compression methods on the task of automatic speaker identification. The motivation for this aspect of the research arose from a need to simultaneously preserve the speech quality and intelligibility and to provide for machine-based automatic speaker recognition using the compressed speech. This is important because there are several emerging applications of speaker identification where compressed speech is involved. Examples include mobile communications where the speech has been highly compressed, or where a database of speech material has been assembled and stored in compressed form. Although these two application areas have the same objective - that of maximizing the identification rate - the starting points are quite different. On the one hand, the speech material used for training the identification algorithm may or may not be available in compressed form. On the other hand, the new test material on which identification is to be based may only be available in compressed form. Using the spectral parameters which have been stored in compressed form, two main classes of speaker identification algorithm are examined. Some studies have been conducted in the past on bandwidth-limited speaker identification, but the use of short-term spectral compression deserves separate investigation. Combining the major aspects of the research, some important design guidelines for the construction of an identification model when based on the use of compressed speech are put forward.

Human preadipocyte proliferation and differentiation

Obesity represents a major health, social and economic burden to many developing and Westernized communities, with the prevalence increasing at a rate exceeding almost all other medical conditions. Despite major recent advances in our understanding of adipose tissue metabolism and dynamics, we still have limited insight into the regulation of adipose tissue mass in humans. Any significant increase in adipose tissue mass requires proliferation and differentiation of precursor cells (preadipocytes) present in the stromo-vascular compartment of adipose tissue. These processes are very complex and an increasing number of growth factors and hormones have been shown to modulate the expression of genes involved in preadipocyte proliferation and differentiation. A number of transcription factors, including the C/EBP family and PP ARy, have been identified as integral to adipose tissue development and preadipocyte differentiation. Together PP ARy and C/EBPa regulate important events in the activation and maintenance of the terminally differentiated phenotype. The ability of PP ARy to increase transcription through its DNA recognition site is dependent on the binding of ligands. This suggests that an endogenous PP ARy ligand may be an important regulator of adipogenesis. Adipose tissue functions as both the major site of energy storage in the body and as an endocrine organ synthesizing and secreting a number of important molecules involved in regulation of energy balance. For optimum functioning therefore, adipose tissue requires extensive vascularization and previous studies have shown that growth of adipose tissue is preceded by development of a microvascular network. This suggests that paracrine interactions between constituent cells in adipose tissue may be involved in both new capillary formation and fat cell growth. To address this hypothesis the work in this project was aimed at (a) further development of a method for inducing preadipocyte differentiation in subcultured human cells; (b) establishing a method for simultaneous isolation and separate culture of both preadipocytes and microvascular endothelial cells from the same adipose tissue biopsies; (c) to determine, using conditioned medium and co-culture techniques, if endothelial cell-derived factors influence the proliferation and/or differentiation of human preadipocytes; and (d) commence characterization of factors that may be responsible for any observed paracrine effects on aspects of human adipogenesis. Major findings of these studies were as follows: (A) Inclusion of either linoleic acid (a long-chain fatty acid reported to be a naturally occurring ligand for PP ARy) or Rosiglitazone (a member of the thiazolidinedione class of insulin-sensitizing drugs and a synthetic PPARy ligand) in differentiation medium had markedly different effects on preadipocyte differentiation. These studies showed that human preadipocytes have the potential to accumulate triacylglycerol irrespective of their stage of biochemical differentiation, and that thiazolidinediones and fatty acids may exert their adipogenic and lipogenic effects via different biochemical pathways. It was concluded that Rosiglitazone is a more potent inducer of human preadipocyte differentiation than linoleic acid. (B) A method for isolation and culture of both endothelial cells and preadipocytes from the same adipose tissue biopsy was developed. Adipose-derived microvascular endothelial cells were found to produce factor/s, which enhance both proliferation and differentiation of human preadipocytes. (C) The adipogenic effects of microvascular endothelial cells can be mimicked by exposure of preadipocytes to members of the Fibroblast Growth Factor family, specifically ~-ECGF and FGF-1. (D) Co-culture of human preadipocytes with endothelial cells or exposure of preadipocytes to either ~-ECGF or FGF-1 were found to 'prime' human preadipocytes, during their proliferative phase of growth, for thiazolidinedione-induced differentiation. (E) FGF -1 was not found to be acting as a ligand for PP ARy in this system. Findings from this project represent a significant step forward in our understanding of factors involved in growth of human adipose tissue and may lead to the development of therapeutic strategies aimed at modifying the process. Such strategies would have potential clinical utility in the treatment of obesity and obesity related disorders such as Type II Diabetes.

Automatic spoken language identification utilizing acoustic and phonetic speech information

Automatic spoken Language Identi¯cation (LID) is the process of identifying the language spoken within an utterance. The challenge that this task presents is that no prior information is available indicating the content of the utterance or the identity of the speaker. The trend of globalization and the pervasive popularity of the Internet will amplify the need for the capabilities spoken language identi¯ca- tion systems provide. A prominent application arises in call centers dealing with speakers speaking di®erent languages. Another important application is to index or search huge speech data archives and corpora that contain multiple languages. The aim of this research is to develop techniques targeted at producing a fast and more accurate automatic spoken LID system compared to the previous National Institute of Standards and Technology (NIST) Language Recognition Evaluation. Acoustic and phonetic speech information are targeted as the most suitable fea- tures for representing the characteristics of a language. To model the acoustic speech features a Gaussian Mixture Model based approach is employed. Pho- netic speech information is extracted using existing speech recognition technol- ogy. Various techniques to improve LID accuracy are also studied. One approach examined is the employment of Vocal Tract Length Normalization to reduce the speech variation caused by di®erent speakers. A linear data fusion technique is adopted to combine the various aspects of information extracted from speech. As a result of this research, a LID system was implemented and presented for evaluation in the 2003 Language Recognition Evaluation conducted by the NIST.

Tactical driver lane change model using forward search

This paper describes the development and evaluation of a tactical lane change model using the forward search algorithm, for use in a traffic simulator. The tactical lane change model constructs a set of possible choices of near-term maneuver sequences available to the driver and selects the lane change action at the present time to realize the best maneuver plan. Including near term maneuver planning in the driver behavior model can allow a better representation of the complex interactions in situations such as a weaving section and high-occupancy vehicle (HOV) lane systems where drivers must weave across several lanes in order to access the HOV lanes. To support the investigation, a longitudinal control model and a basic lane change model were also analyzed. The basic lane change model is similar to those used by today's commonly-used traffic simulators. Parameters in all models were best-fit estimated for selected vehicles from a real-world freeway vehicle trajectory data set. The best-fit estimation procedure minimizes the discrepancy between the model vehicle and real vehicle's trajectories. With the best fit parameters, the proposed tactical lane change model gave a better overall performance for a greater number of cases than the basic lane change model.