This research utilises data from instrumented vehicles and road side remote sensing in an urban environment to explore the relationships between exhaust tail pipe emissions, vehicle technology, and driver behaviour. An investigation is carried out into the nature of variability that exists in the driving behaviour of a sample of drivers, and the influence of such variability on fuel consumption and the emission rates of exhaust pollutants. Analysis of data from remote sensing reveals that emissions from petrol cars (CO, HC, NO, PM) are all observed to display a statistically significant reduction with the introduction of each successive Euro emissions standard from Euro 1 onwards. However, Euro 2 diesel cars are observed to emit statistically higher rates of NO than either Euro 1 or Euro 3 standard diesel cars. When the New European Driving Cycle is synthesised from remote sensing data and compared with type approval data published by the UK Vehicle Certification Agency, mean CO emissions from petrol cars ≤3 years old measured using remote sensing are found to be 1.3 times higher than published original type approval test values; this factor increases to 2.2 for cars 4 – 8 years old, and 6.4 for cars 9 – 12 years old. The corresponding factors for diesel cars are 1.1, 1.4, and 1.2 respectively. This thesis has made an original contribution to the field in two main areas; firstly by quantifying the ‘real-world’ emission rates for a sample of the UK vehicle fleet in an urban area, and demonstrating the statistically significant differences in emission rates between groups of vehicles; and secondly, by proposing a feasible method to move towards reconciling essentially instantaneous road side measurements of exhaust emissions obtained from remote sensing, with laboratory based measurements taken over a legislated driving cycle as part of the new vehicle type approval process.

Nowadays, occupant safety becomes one of the most important research area and the automotive industry increased their efforts for enhancing the safety of the vehicles. The aim of this research is to investigate the effect of vehicle dynamics control systems (VDCS) on both the collision of the vehicle body and the kinematics behaviour of the vehicle's occupant. In this work, a novel vehicle dynamics/crash mathematical model is proposed and developed to co-simulate the crash event with the VDCS. This model is achieved using the novel approach of integrating front-end structure and vehicle dynamics mathematical models. The proposed mathematical model integrates both anti-lock braking systems (ASS) and active suspension control (ASC) systems alongside with crash structure modelling. This model is developed by generating its equations of motion and solving them numerically, this approach is used due to its quick and accurate analysis. In addition, a new multi-body occupant mathematical model is developed to capture the occupant kinematics before and during the collision. Validations of the proposed mathematical models are achieved to ensure their accuracy by comparing the simulated results with other real crash test data and former models results. The validation analysis of the vehicle and occupant models shows that the comparison results are well matched and the models are valid and can be used for different crash scenarios. The numerical simulation results are divided into two parts for vehicle and occupant models, respectively. Related to the vehicle model, it is shown that the mathematical model is flexible and useful for optimization studies. The results show that the deformation of the front-end structure is reduced, the vehicle body pitching and yawing angles are notably reduced, and the vehicle pitching acceleration is greatly reduced. Related to the occupant model, it is shown that the VDCS does have a significant effect on the rotations of the occupant's chest and head owing to its effect on the vehicle pitching. In addition, the occupant's deceleration is also slightly decreased and the occupant safety is improved.

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Traffic assignment, the process by which vehicle flows are loaded on to paths traversing a road network for the purpose of spatial demand forecasting, has been traditionally approached as a mathematical optimisation problem. However, this assumes typical highway network conditions, yielding ‘average day’ traffic forecasts only. Such approaches fail to account for time-dependent variability caused by infrequent events such as traffic accidents, vehicle breakdowns or road works which result in sub-optimal network performance. On any day, especially when incidents cause abnormal congestion patterns, drivers can only choose routes and diversion strategies according to the best of their own subjective knowledge and experience which is unique to each traveller. Ensuring that knowledge, both within-day and between days, is represented adequately and with realistic assumptions within models is key to forecasting traffic flows in all situations and their resulting network phenomena accurately. This thesis explores how drivers react under these irregular conditions, termed ‘states’, with a goal of understanding route choice and consequently advancing demand forecasting techniques. To this end, a simulator based survey is used in order to gain further knowledge of driver learning and diversion behaviour, then an agent based simulation modelling approach is developed using this insight to explore the network and traffic flow effects of drivers reacting to uncertain network conditions by altering their route choices. This work argues that representing driver knowledge and choices from a disaggregate agent based perspective, rather than a traditional aggregate approach, is more appropriate for modelling the impact of variable travel conditions. Results demonstrate that the possibility of incidents occurring and the potential for diverting can have a significant effect on network characteristics and the decisions of drivers, even on incident-free ‘clear’ days. Importantly, results show that drivers diverting can temporarily alleviate congestion but ultimately cause more delays and suboptimal network performance. These results have significant implications for demand forecasting practitioners and policy makers who try to minimise disruption through traffic management systems or effective network design.

different methods of in-vehicle information presentation to encourage fuel efficient driving behaviours, and to explore the theoretical justifications for the use of in-vehicle haptic stimuli (related to the sense of touch), presented at the site of control (i.e., the accelerator pedal). A review of the literature concerning design, behaviour, and energy use led on to an exploration of Ecological Interface Design, and the Skills, Rules, and Knowledge (SRK) taxonomy of human behaviour, particularly with regard to haptic information presented through the accelerator pedal. Survey and on-road studies served to shed light on the practice of eco-driving more generally, in terms of attitudes, knowledge, behaviour, and cognition. Then followed an analysis of expert eco-drivers’ decision-making processes. This made use of the decision ladder, an analysis tool rooted in the SRK framework. Results of the analysis went on to inform the design of an in-vehicle information system that aimed to support optimum use of the accelerator pedal, both for efficient accelerations, and for maximisation of the coasting phase of the vehicle when approaching deceleration events. A simulator-based experiment served to assess the effects of presenting stimuli in different sensory modes (visual, auditory, vibrotactile), resulting in the conclusion that vibrotactile feedback, being both effective and well received by participants, is indeed suitable for the support of eco-driving. In a second simulator-based study, coasting support provided the sole focus; acceleration behaviours were not investigated. Results suggested that there is a minimum distance away from an event below which stimuli encouraging removal of the foot from the accelerator pedal (in order to coast down to the desired speed)have neither a beneficial effect on driving performance, nor attract positive acceptance ratings from users. Moreover, stimuli presented farther from the event supported greater benefits in terms of efficiency. Overall findings are discussed with regard to the practical aspect of how best to support eco-driving in the private road vehicle, and in relation to the theoretical justifications for accelerator-based haptic feedback in the vehicle.

This research investigated the perception of self-motion in driving simulation, focussing on the dynamic cues produced by a motion platform. The study was undertaken in three stages, evaluating various motion cueing techniques based on both subjective ratings of realism and objective measures of driver performance. Using a Just Noticeable Difference methodology, Stage 1 determined the maximum perceptible motion scaling for platform movement in both translation and tilt. Motion cues scaled by 90% or more could not be perceptibly differentiated from unscaled motion. This result was used in Stage 2‟s examination of the most appropriate point in space at which the platform translations and rotations should be centred (Motion Reference Point, MRP). Participants undertook two tracking tasks requiring both longitudinal (braking) and lateral (steering) vehicle control. Whilst drivers appeared unable to perceive a change in MRP from head level to a point 1.1m lower, the higher position (closer to the vestibular organs) did result in marginally smoother braking, corresponding to the given requirements of the longitudinal driving task. Stage 3 explored the perceptual trade-off between the specific force error and tilt rate error generated by the platform. Three independent experimental factors were manipulated: motion scale-factor, platform tilt rate and additional platform displacement afforded by a XY-table. For the longitudinal task, slow tilt that remained sub-threshold was perceived as the most realistic, especially when supplemented by the extra surge of the XY-table. However, braking task performance was superior when a more rapid tilt was experienced. For the lateral task, perceived realism was enhanced when motion cues were scaled by 50%, particularly with added XY-sway. This preference was also supported by improvements in task accuracy. Participants ratings were unmoved by changing tilt rate, although rapid tilt did result in more precise lane control. Several interactions were also observed, most notably between platform tilt rate and XY-table availability. When the XY-table was operational, driving task performance varied little between sub-threshold and more rapid tilt. However, while the XY-table was inactive, both driving tasks were better achieved in conditions of high tilt rate. An interpretation of these results suggests that without the benefit of significant extra translational capability, priority should be given to the minimisation of specific force error through motion cues presented at a perceptibly high tilt rate. However, XY-table availability affords the simulator engineer the luxury of attaining a slower tilt that provides both accurate driving task performance and accomplishes maximum perceived realism.

The objectives of this thesis was to provide researchers with a scientitically-based guide for interpreting driver behaviour results obtained on a fixed-base driving simulator and to provide guidance on how the Leeds Advanced Driving Simulator (LADS) could be modified to overcome any deficiencies that were detected. However. objectives of any simulator validation study are directly related to the specitic driving task under investigation. our ability to perform a similar task in the field (for the comparison of the results between the two environments) and the existing configuration capabilities of the simulator. To achieve the objectives of this study, driver behaviour was investigated at the control level under different road geometry and oncoming traffic conditions using the LADS. Speed and lateral displacement in terms of mean and standard deviation were chosen to represent driver behaviour. They were measured under free-flowing conditions on a rural A road. The objectives of the study were fulfilled by comparing observational uncontrolled real road data with experimental simulator data and by evaluating the differences between the two environments using the absolute and relative validity criteria. It was found that LADS is relatively valid in terms of speed and lateral position. It was also found that higher speeds are developed in the simulator where speed in not confined by the road geometry and simulator subjects drive significantly closer to the edge of the road compared to their real road counterparts irrespective of the road geometry and the oncoming traffic conditions. The face validity of the simulator was examined using subjective data obtained from questionnaires relative to the realism and ease of controlling the simulator. Subjects commented that the least realistic features of the simulator were the braking and steering systems. Subjects were classiffied to "good" and "poor" according to their responses regarding the simulator face validity. It was found that "good" subjects behave slightly better compared to "poor" subjects when driving the simulator.

The tuning of production road car suspension parameters in the development stage of a vehicle can be a lengthy and expensive procedure and commonly relies on the subjective judgements of test drivers to assess various aspects of ride and handling. The work in this thesis aims to create a testing and tuning technique using four-post rig testing and vehicle simulation to significantly reduce the amount of physical and subjective testing required within the development stage. A four-post rig testing technique is developed using modal sine sweep inputs to acquire the response of the vehicle in the heave, pitch, roll and warp modes of excitation. An analysis and parameter estimation method is developed based on four-post data and a 7 degree-of-freedom model, with four-post test data used to validate the parameter estimation and vehicle model simultaneously, obtaining satisfactory results in all but the roll mode of excitation. The BS 6841 [1] discomfort acceleration weightings are applied to the modal responses, with road input PSDs representative of standardised roads and driving cycles used to produce a comfort index value for a tested vehicle or setup. A novel performance index is created to estimate grip loss due to static and dynamic tyre properties for each axle, which allows the prediction of road input effects on the total grip and balance of the vehicle, as well as a driver requirement of steering input. MATLAB code is constructed for the parameter estimation procedure and for three general user interfaces to assist with the testing, tuning and benchmarking procedure. An objective-subjective validation exercise is carried out using a single vehicle with four different component setups which are tested on the four-post rig to determine comfort and performance index values, as well as recording the subjective assessments of three test drivers on two drive routes in the UK and Germany. The results show fair to good correlation for comfort measures but generally poor correlation to the performance index, mostly because of large variations between the drivers’ subjective assessment criteria.

In-vehicle navigation has been identified as a key activity for maintaining the mobility and hence the independence and quality of life of older adults. However, few studies have directly investigated and tested route guidance requirements specifically for older drivers. This thesis addresses the knowledge gap using a range of quantitative and qualitative methodologies across three investigations. A focus group investigation was undertaken first. Thirty older adults were recruited and themes of driving and navigation behaviour discussed. This research stage found older adults have difficulty planning and then navigating journeys, landmarks are used to navigate the road network and in-vehicle navigation systems (IVNS) are not deemed to be useable. In the second investigation, current design IVNS were loaned to 22 older adults for a two-week period. During this period the participants detailed their experiences and attitudes of the loaned IVNS. In addition, in-depth interviews were undertaken. This investigation found that IVNS have usability issues for older drivers that need to be considered for the next generation of IVNS. In the next stage, a driving simulator investigation with 30 older drivers was carried out. This phase of the research examined the navigational benefits of providing landmark-based route guidance information as compared to the traditional method of paper maps. The study concluded that older drivers have difficulties with navigation through decline in memory and vision. The driving simulator investigation suggests that landmarks are effective at supporting older drivers with the navigation task; in particular, older female drivers. In addition, landmark-based route guidance information should be delivered through a combination of audio instructions and an icon-based visual display. Finally, the thesis outlines recommendations for the next generation IVNS for older drivers.

Noise, vibration and Harshness (NVH) of automotive disc brakes have been an active research topic for several decades. The environmental concerns, on one hand, and the rising customer expectations of their car quality, on the other hand, have made NVH of brakes an important issue for car manufacturers. Of different types of noise and vibration that a brake system may generate, squeal is the main focus of the current study. Brake squeal is an irritating high-frequency noise causing a significant warranty cost to car manufacturers. There are a number of reasons leading to squeal noise either at the end of production or during usage and services. Of these reasons, it is believed that manufacturing variability, several sources of uncertainty (such as friction and contact) and diverse loading cases have the most contribution in this problem. Car manufacturers are then recently encouraged to look into the uncertainty analysis of the brake systems in order to cover the influence of these variations on brake designs. The biggest hurdle in the uncertainty analysis of brakes is the computational time, cost and data storage. In general, stochastic studies are done on the premise of deterministic analyses of a system. As the deterministic analyses of brake squeal instability essentially involve a great deal of computational workload, their stochastic (non-deterministic) analyses will be consequently very expensive. To overcome this issue, the method of surrogate modelling is proposed in this study. Briefly speaking, surrogate modelling replaces an expensive simulation code with a cheap-to-evaluate mathematical predictor. As a result, instead of using the actual finite element model of a brake for statistical analyses, its replacement model will be used alternatively. There are three main advantages in surrogate modelling of brakes. First of all, it paves the way of structural modification of brakes, which are conventionally done for reducing squeal propensity. Secondly, structural uncertainties of a brake design can cost-effectively be propagated onto the results of the stability analysis. Thereafter, instead of making a single design point stable, a scatter of points should meet the stability criteria. Finally, the reliability and robustness of a brake design can be quantified efficiently. These two measures indicate the probability of unstable vibration leading to squeal noise for a brake design. Accordingly, car manufacturers will be able to estimate the cost of warranty claims which may be filed due to this particular issue. If the probability of failure which is calculated for squeal propensity is significant, surrogate modelling helps come up with a solution during the design stage, before cars go into production. In brief, two major steps must be taken toward constructing a surrogate model: making a uniform sampling plan and fitting a mathematical predictor to the observed data. Of different sampling techniques, Latin hypercube sampling (LHS) is used in this study in order to reduce the amount of computational workload. It is worth mentioning that the original LHS does not enforce the uniformity condition when making samples. However, some modifications can be applied to LHS in order to improve the uniformity of samples. Note that the uniformity of samples plays a crucial role in the accuracy of a surrogate model. A surrogate model, in fact, is built on the premise of the observations which are made over a design space. Depending on the nonlinearity of the outputs versus the input variables and also depending on the dimensions of a design space, different mathematical functions may be used for a surrogate predictor. The results of this study show that Kriging function brings about a very accurate surrogate model for the brake squeal instability. In order to validate the accuracy of surrogate models, a number of methods are reviewed and implemented in the current study. Finally, the validated surrogate models are used in place of the actual FE model for uncertainty quantification of squeal instability. Apart from surrogate modeling, a stochastic study is conducted on friction-induced vibration. Statistics of complex eigenvalues of a simplified brake models are studied under the influence of variability and uncertainty. For this purpose, the 2nd order perturbation method is extended to be applicable on an asymmetric system with non-proportional damping. The main advantage of this approach is that the statistics of complex eigenvalues can be calculated in just one run, which is massively more efficient than the conventional techniques of uncertainty propagation that use a large number of simulations to determine the results.