A multi-commodity Lighthill–Whitham–Richards model of lane-changing traffic flow

Systematic lane changes can seriously deteriorate traffic safety and efficiency inside lane-drop, merge, and other bottleneck areas. In our previous studies (Jin, 2010a, Jin, 2010b), a phenomenological model of lane-changing traffic flow was proposed, calibrated, and analyzed based on a new concept of lane-changing intensity. In this study, we further consider weaving and non-weaving vehicles as two commodities and develop a multi-commodity, behavioral Lighthill–Whitham–Richards (LWR) model of lane-changing traffic flow. Based on a macroscopic model of lane-changing behaviors, we derive a fundamental diagram with parameters determined by car-following and lane-changing characteristics as well as road geometry and traffic composition. We further calibrate and validate fundamental diagrams corresponding to a triangular car-following fundamental diagram with NGSIM data. We introduce an entropy condition for the multi-commodity LWR model and solve the Riemann problem inside a homogeneous lane-changing area. From the Riemann solutions, we derive a flux function in terms of traffic demand and supply. Then we apply the model to study lane-changing traffic dynamics inside a lane-drop area and show that the smoothing effect of HOV lanes is consistent with observations in existing studies. The new theory of lane-changing traffic flow can be readily incorporated into Cell Transmission Model, and this study could lead to better strategies for mitigating bottleneck effects of lane-changing traffic flow.     

Determinants of modal choice in freight transport

In the next few years, exciting developments in the field of freight transport are likely to occur. The Channel Tunnel will be perceived as giving railways much greater distance of operation, compared to the current train ferry to/from Great Britain. The further development of swap-body technology will allow easier modal transfer and the creation, in 1992, of a single market in Europe will transform the pattern of trade. All of these are likely to have significant impacts on modal choice, and hence modal split, in freight transport. Reappraisal by many firms of the modes of transport used is likely but will it result in a net transfer of freight from road to rail and, if so, to what extent? To answer such questions, an accurate and reliable method of predicting modal split is required. Research in the past has concentrated on the development of modal split models based on generalised costs. These fail to explain adequately the prevalence of road freight in the UK. From surveys of freight managers within industry, it is clear that models to date rely too heavily on the economic cost factor and too little on behavioural factors (Jeffs 1985). This paper derives from a recent study of freight transport modal choice from the standpoint of the transport decision-maker within the firm. It attempts to shed light on the actual parameters which should be incorporated into a modal split model. Many variables appear to exert an influence on modal choice decision-making process. However, it is possible to categorise them into six main groups, namely: customer-requirements; product-characteristics; company structure/organisation; government interventions; available transport facilities; and perceptions of the decision-maker him/herself. It is the interactions and inter-relationships between these which ultimately determine freight modal split. This study has shown that the relationship between the outcome of the transport decision process and the values of particular determinants of modal split is not straight-forward, due to the complexity and variety of interactions involved. Perhaps one of the main reasons for researchers' failure hitherto to develop a successful modal-split model has been the preoccupation with techniques that rely on the development of common metric (e.g. generalised cost), which has led to the exclusion of some important explanatory variables along quite different dimensions. Another important issue concerns the appropriate level of aggregation. In order not to reduce the explanatory power of the key variables, it is important to work at a disaggregate level, although this does make substantial demands on data. The use of factor analysis enables both the aggregation of information without loss of behavioural reality and the specification of variables in terms of a common metric. In conclusion, freight transport has usually been examined within too narrow a framework. It must be placed firmly within the context of the total industrial process. The demand for freight transport is directly influenced by the level, composition and geographical distribution of production and consumption activities. Freight flows are complex and so it is highly unlikely that a universal mode-choice model can ever be developed. Future research should, therefore, be directed towards developing partial models in response to specific needs of those involved in decision-taking in the freight sector.     

Tyre-force estimation by Kalman inverse filtering: applications to off-highway mining trucks

Kalman inverse filtering is used to develop a methodology for real-time estimation of forces acting at the interface between tyre and road on large off-highway mining trucks. The system model formulated is capable of estimating the three components of tyre-force at each wheel of the truck using a practical set of measurements and inputs. Good tracking is obtained by the estimated tyre-forces when compared with those simulated by an ADAMS virtual-truck model. A sensitivity analysis determines the susceptibility of the tyre-force estimates to uncertainties in the truck’s parameters.     

Efficient empirical modelling of a high-performance shock absorber for vehicle dynamics studies

This paper develops an intuitive empirical nonlinear dynamic shock absorber model for simulation studies. Unlike other existing dynamic shock absorber models, it does not suffer from the complexity of modelling complex physical behaviour, or the inefficiencies of unstructured black-box modelling. The model consists of an algebraic backbone, which is a function of velocity alone, and a nonlinear low-pass filter, which has been designed based on the observation that the damper can respond more quickly at higher velocities. Due to the simplicity of the model, it can be fitted with data and evaluated quickly. The model was fitted using shock dynamometer test data using a random shock position command. The completed model is then validated using random, sine wave, and bump test data. This analysis shows the strengths and weaknesses of the model and suggests areas for future development.     

Physical processes in wheel–rail contact and its implications on vehicle–track interaction

Friction within the wheel–rail contact highly influences all aspects of vehicle–track interaction. Models describing this frictional behaviour are of high relevance, for example, for reliable predictions on drive train dynamics. It has been shown by experiments, that the friction at a certain position on rail is not describable by only one number for the coefficient of friction. Beside the contact conditions (existence of liquids, solid third bodies, etc.) the vehicle speed, normal loading and contact geometry are further influencing factors. State-of-the-art models are not able to account for this sufficiently. Thus, an Extended-Creep-Force-Model was developed taking into account effects from third body layers. This model is able to describe all considered effects. In this way, a significant improvement of the prediction quality with respect to all aspects of vehicle–track interaction is expected.