青藏铁路机械设备合理配置与施工

介绍了青藏铁路隧道、桥梁桩基成孔、路基机械设备配置的原则、配套方案以及机械化施工在“地球第三极”显示出的巨大威力。     

Physically Realisable Feedback Controls for a Fully Active Preview Suspension Applied to a Half-Car Model

An optimal preview type active suspension with feedback control based on easily measured relative displacements, velocities and accelerations is proposed. Measurements relative to the road, except by the preview sensor, are not required and the front and rear spring rates are quite arbitrary. Also, state estimators or observers are unnecessary and as a practical alternative the body accelerometers may be replaced by load cells. The effects of preview on the performance, for a theoretical step type road input and an analogous random road input, are described. The definition of the optimum preview function, and its consequent effects on performance, receives attention and an example is given.     

A Driver Model Based on the Cerebellar Model Articulation Controller

A model of driver behavior is described which is based on a current theory of neurophysiological processes occurring in the cerebellum. The model learns to control the vehicle through experience, provides discontinuous ramp steer inputs to the vehicle, accepts discontinuous input data, and is applicable to all control situations.

The model is implemented on a simple simulation model of a car and learning is accomplished by the use of an explicit driver model which drives the vehicle along a specified trajectory.     

An Active Suspension with Optimal Linear State Feedback

In this paper modern optimal control theory is applied to the design of an active suspension system for a motor vehicle. The road profile is assumed to be continuous and random with a power spectral density (P.S.D.) which varies inversely with the square of the frequency. The quadratic integral type performance index employed is a weighted sum of the integral squares of body acceleration, dynamic tyre deflection and relative body-to-axle displacement. A solution is obtained for the infinite time case which is both computationally and physically realizable as an active suspension in which the only continuous measurements required are the body absolute velocity and the body displacement relative to the road. The performance is compared with that of a conventional type passive suspension and found to be significantly better in practically all respects.     

Evaluation of transit operations: data applications of Tri-Met's automated Bus Dispatching System

In this paper, archived Automatic Vehicle Location and Automatic Passenger Counter data are used to evaluate actual bus running time variation in relation to scheduled service for Tri-Met, the transit provider for the Portland, Oregon metropolitan area. Given observed variation in running times, scheduled recovery times are found to be generally (though not universally) excessive. This results in an under-investment of resources in revenue service relative to non-revenue service. Analysis of trip level data reveals that bus operators are an important source of running time variation after controlling for such factors as route design, time of day and direction of service, and passenger activity.     

Influence of peak spreading and departure time choice on evaluation of its measures

Intelligent transport systems provide various means to improve capacity and travel time in road networks. Evaluation of the benefits of these improvements requires consideration of travellers' response to them. We consider a continuous‐time equilibrium model of departure time choice and identify a formula for the dynamic equilibrium departure rate profile. We develop the analysis to consider the effect on the cost incurred by travellers of ITS measures through their effects on each of the travel time in the absence of congestion, and the capacity for travel. This shows the importance in choice of departure time of travellers' values of time at each of the origin and destination of their journeys. We show the importance of these values of time in evaluation, and that if travellers value their time at both the origin and destination of their journeys, their responses will lead them to achieve a greater reduction in costs than would be achieved under free‐flow conditions.     

Motion cueing in high-performance vehicle simulators

The majority of motion cueing algorithms have been developed for passenger car applications, with correspondingly less research dedicated to race-car and high-performance vehicle simulators. In the high-performance context, the focus is on cueing the vehicle's behavioural and handling characteristics, particularly when driving near the limits of performance. In race-car simulators the cueing requirements are therefore quite different, with the problem made all the more challenging by the presence of large accelerations. To understand the drivers' cueing needs, the vehicle's stability and handling response characteristics must be examined near the performance boundary. Frozen-time eigenvalue analyses are used to determine stability and response characteristics across all vehicle operating conditions, including accelerating and braking under cornering, with the results used to determine motion cueing algorithm requirements. Lateral acceleration and yaw cueing filters are designed in order to retain information critical to understanding the vehicle's behaviour on its performance boundary. Cueing filters are then tested, with the help of a professional race-car driver, and are found to provide the cues necessary for the driver to control the vehicle on the limit of performance.     

Novel stability control strategy for distributed drive electric vehicle based on driver operation intention

In this paper, a novel direct yaw control method based on driver operation intention for stability control of a distributed drive electric vehicle is proposed. It was discovered that the vehicle loses its stability easily under an emergency steering alignment (EA) problem. An emergent control algorithm is proposed to improve vehicle stability under such a condition. A driver operation intention recognition module is developed to identify the driving conditions. When the vehicle enters into an EA condition, the module can quickly identify it and transfer the control method from normal direct yaw control to emergency control. Two control algorithms are designed. The emergency control algorithm is applied to an EA condition while the adaptive control algorithm is applied to other conditions except the EA condition. Both simulation results and real vehicle results show that: The driver module can accurately identify driving conditions based on driver operation intention. When the vehicle enters into EA condition, the emergent control algorithm can intervene quickly, and it has proven to outperform normal direct yaw control for better stabilization of vehicles.