1,357 research outputs found

    Optimal scheme of ships’ routeing system in the Yangtze Estuary based on analytical hierarchy process

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    Optimisation of speed camera locations using genetic algorithm and pattern search

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    Road traffic accidents continue to be a public health problem and are a global issue due to the huge financial burden they place on families and society as a whole. Speed has been identified as a major contributor to the severity of traffic accidents and there is the need for better speed management if road traffic accidents are to be reduced. Over the years various measures have been implemented to manage vehicle speeds. The use of speed cameras and vehicle activated signs in recent times has contributed to the reduction of vehicle speeds to various extents. Speed cameras use punitive measures whereas vehicle activated signs do not so their use depends on various factors. Engineers, planners and decision makers responsible for determining the best place to mount a speed camera or vehicle activated sign along a road have based their decision on experience, site characteristics and available guidelines (Department for Transport, 2007; Department for Transport, 2006; Department for Transport, 2003). These decisions can be subjective and indications are that a more formal and directed approach aimed at bringing these available guidelines together in a model will be beneficial in making the right decision as to where to place a speed camera or vehicle activated sign is to be made. The use of optimisation techniques have been applied in other areas of research but this has been clearly absent in the Transport Safety sector. This research aims to contribute to speed reduction by developing a model to help decision makers determine the optimum location for a speed control device. In order to achieve this, the first study involved the development of an Empirical Bayes Negative Binomial regression accident prediction model to predict the number of fatal and serious accidents combined and the number of slight accidents. The accident prediction model that was used explored the effect of certain geometric and traffic characteristics on the effect of the severity of road traffic accident numbers on selected A-roads within the Nottinghamshire and Leicestershire regions of United Kingdom. On A-roads some model variables (n=10) were found to be statistically significant for slight accidents and (n=6) for fatal and serious accidents. The next study used the accident prediction model developed in two optimisation techniques to help predict the optimal location for speed cameras or vehicle activated signs. Pattern Search and Genetic Algorithms were the two main types of optimisation techniques utilised in this thesis. The results show that the two methods did produce similar results in some instances but different in others. Optimised results were compared to some existing sites with speed cameras some of the results obtained from the optimisation techniques used were within proximity of about 160m. A validation method was applied to the genetic algorithm and pattern search optimisation methods. The pattern search method was found to be more consistent than the genetic algorithm method. Genetic algorithm results produced slightly different results at validation in comparison with the initial results. T-test results show a significant difference in the function values for the validated genetic algorithm (M= 607649.34, SD= 1055520.75) and the validated pattern search function values (M= 2.06, SD= 1.17) under the condition t (79) = 5.15, p=0.000. There is a role that optimisation techniques can play in helping to determine the optimum location for a speed camera or vehicle activated sign based on a set of objectives and specified constraints. The research findings as a whole show that speed cameras and vehicle activated signs are an effective speed management tool. Their deployment however needs to be carefully considered by engineers, planners and decision makers so as to achieve the required level of effectiveness. The use of optimisation techniques which has been generally absent in the Transport Safety sector has been shown in this thesis to have the potential to contribute to improve speed management. There is however no doubt that this research will stimulate interest in this rather new but high potential area of Transport Safety

    Developing accident-speed relationships using a new modelling approach

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    Changing speed limit leads to proportional changes in average speeds which may affect the number of traffic accident occurrences. It is however critical and challenging to evaluate the impact of a speed limit alteration on the number and severity of accidents due primarily to the unavailability of adequate data and the inherent limitations of existing approaches. Although speed is regarded as one of the main contributory factors in traffic accident occurrences, research findings are inconsistent. Independent of the robustness of their statistical approaches, accident frequency models typically use accident grouping concepts based on spatial criteria (e.g. accident counts by link termed as a link-based approach). In the link-based approach, the variability of accidents is explained by highly aggregated average measures of explanatory variables that may be inappropriate, especially for time-varying variables such as speed and volume. This thesis re-examines accident-speed relationships by developing a new accident data aggregation method that enables improved representation of the road conditions just before accident occurrences in order to evaluate the impact of a potential speed limit increase on the UK motorways (e.g. from 70 mph to 80 mph). In this work, accidents are aggregated according to the similarity of their pre-accident traffic and geometric conditions, forming an alternative accident count dataset termed as the condition-based approach. Accident-speed relationships are separately developed and compared for both approaches (i.e. link-based and condition-based) by employing the reported annual accidents that occurred on the Strategic Road Network of England in 2012 along with traffic and geometric variables. Accident locations were refined using a fuzzy-logic-based algorithm designed for the study area with 98.9% estimated accuracy. The datasets were modelled by injury severity (i.e. fatal and serious or slight) and by number of vehicles involved (i.e. single-vehicle and multiple-vehicle) using the multivariate Poisson lognormal regression, with spatial effects for the link-based model under a full Bayesian inference method. The results of the condition-based models imply that single-vehicle accidents of all severities and multiple-vehicle accidents with fatal or serious injuries increase at higher speed conditions, particularly when these are combined with lower volumes. Multiple-vehicle slight injury accidents were not found to be related with higher speeds, but instead with congested traffic. The outcomes of the link-based model were almost the opposite; suggesting that the speed-accident relationship is negative. The differences between the results reveal that data aggregation may be crucial, yet so far overlooked in the methodological aspect of accident data analyses. By employing the speed elasticity of motorway accidents that was derived from the calibrated condition-based models it has been found that a 10 mph increase in UK motorway speed limit (i.e. from 70 mph to 80 mph) would result in a 6-12% increase in fatal and serious injury accidents and 1-3% increase in slight injury accidents

    Automatic Control and Routing of Marine Vessels

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    Due to the intensive development of the global economy, many problems are constantly emerging connected to the safety of ships’ motion in the context of increasing marine traffic. These problems seem to be especially significant for the further development of marine transportation services, with the need to considerably increase their efficiency and reliability. One of the most commonly used approaches to ensuring safety and efficiency is the wide implementation of various automated systems for guidance and control, including such popular systems as marine autopilots, dynamic positioning systems, speed control systems, automatic routing installations, etc. This Special Issue focuses on various problems related to the analysis, design, modelling, and operation of the aforementioned systems. It covers such actual problems as tracking control, path following control, ship weather routing, course keeping control, control of autonomous underwater vehicles, ship collision avoidance. These problems are investigated using methods such as neural networks, sliding mode control, genetic algorithms, L2-gain approach, optimal damping concept, fuzzy logic and others. This Special Issue is intended to present and discuss significant contemporary problems in the areas of automatic control and the routing of marine vessels

    Fractional Order State Feedback Control for Improved Lateral Stability of Semi-Autonomous Commercial Heavy Vehicles

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    With the growing development of autonomous and semi-autonomous large commercial heavy vehicles, the lateral stability control of articulated vehicles have caught the attention of researchers recently. Active vehicle front steering (AFS) can enhance the handling performance and stability of articulated vehicles for an emergency highway maneuver scenario. However, with large vehicles such tractor-trailers, the system becomes more complex to control and there is an increased occurrence of instabilities. This research investigates a new control scheme based on fractional calculus as a technique that ensures lateral stability of articulated large heavy vehicles during evasive highway maneuvering scenarios. The control method is first implemented to a passenger vehicle model with 2-axles based on the well-known “bicycle model”. The model is then extended and applied onto larger three-axle commercial heavy vehicles in platooning operations. To validate the proposed new control algorithm, the system is linearized and a fractional order PI state feedback control is developed based on the linearized model. Then using Matlab/Simulink, the developed fractional-order linear controller is implemented onto the non-linear tractor-trailer dynamic model. The tractor-trailer system is modeled based on the conventional integer-order techniques and then a non-integer linear controller is developed to control the system. Overall, results confirm that the proposed controller improves the lateral stability of a tractor-trailer response time by 20% as compared to a professional truck driver during an evasive highway maneuvering scenario. In addition, the effects of variable truck cargo loading and longitudinal speed are evaluated to confirm the robustness of the new control method under a variety of potential operating conditions

    DYNAMIC ANALYSIS OF VEHICLE SYSTEMS Development of a driving simulator Analysis and design of an automatic transmission for motor-scooters

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    In this work, two researches in the field of dynamic analysis of vehicle systems are presented. The first part of the thesis deals with the development of a driving simulator. This activity was carried out in the framework of a research project co-funded by the Italian Ministry of Education, Universities and Research (MIUR). It aimed at developing a driving simulator for the analysis of the driving style, in order to identify potentially dangerous conditions coming from a non proper interaction between driver, vehicle and environment, especially those related to low driver’s attention. As core part of the driving simulator, a vehicle simulation model, which reproduces the behaviour of the main vehicle systems, was developed. The simulator is made of a fixed driving platform, a single channel visual system and allows to acquire all driver’s inputs and vehicle motion signals. The system was involved in experimental campaigns which allowed the development of the driving style analysis techniques and demonstrated the reliability and the capability of the system. The second part of the thesis treats the dynamic analysis and design of a high efficiency automatic transmission for motor-scooters and was carried out in the framework of the Italian MUSS project funded by the Italian Ministry of Economic Development. Motor-scooters are currently almost always equipped with CVT transmission with rubber belt. This transmission can be very cheap to manufacture, it has good comfort performance but low mechanical efficiency. An alternative automatic transmission was analysed and different architectures were studied. The system is based on a discrete ratio gear box with mechanical control of the gear shit by means of centrifugal clutches and free wheels. A dynamic model of the transmission was developed and its behaviour was investigated by means of results of simulated manoeuvres, highlighting the positive and negative aspects of the system. Finally, a preliminary design was also carried out with reference to an application of the transmission in a hybrid powertrain
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