Including heavy vehicles in a car‐following model: modelling,calibrating and validating

Heavy vehicles influence general traffic in many different ways compared with passenger vehicles, and this may result in different levels of traffic instability. Increases in the number and proportion of heavy vehicles in the traffic stream will therefore result in different traffic flow conditions. This research initially outlines the different car‐following behaviour of drivers in congested heterogeneous traffic conditions indicating the necessity for developing a car‐following model, which includes these differences. A psychophysical car‐following model, similar in form to Weideman's car‐following model, was developed. Due to the complexity of the developed model, the calibration of the model was undertaken using a particle swarm optimisation algorithm with the data recorded under congested traffic conditions. This was then incorporated into a traffic microsimulation model. The results showed that the car‐following perceptual thresholds and thus action points of drivers differ based on their vehicle and the lead vehicle types. The inclusion of the heavy vehicles in the model showed significant impacts on the traffic dynamic and interactions amongst different vehicles. Copyright © 2016 John Wiley & Sons, Ltd.     

Optimisation of full-toroidal continuously variable transmission in conjunction with fixed ratio mechanism using particle swarm optimisation

The aim of this research is the optimisation of full-toroidal continuously variable transmission (CVT) in conjunction with the fixed ratio (FR) mechanism, while the optimisation objective is to minimise fuel consumption (FC) of the vehicle in the new European driving cycle. After the dynamic analysis of the power train, a computer model is developed to simulate contact between CVT elements and consequently calculate its efficiency. Then an algorithm is presented to calculate FC of the vehicle in the driving cycle. Then, an optimisation using particle swarm optimisation on the CVT geometry and FR mechanism (which is embedded between CVT and final drive) is carried out to minimise FC. It is found that by utilisation of the optimised CVT; FC will be about 11% and 8% lower, compared with the application of a five-speed manual transmission and conventional CVT, respectively. Finally, effects of the roller tilt angle and oil temperature on the FC are investigated.     

Utilisation of optimisation solutions to control active suspension for decreased braking distance

This work deals with how to utilise active suspension on individual vehicle wheels in order to improve the vehicle performance during straight-line braking. Through numerical optimisation, solutions have been found as regards how active suspension should be controlled and coordinated with friction brakes to shorten the braking distance. The results show that, for the studied vehicle, the braking distance can be shortened by more than 1?m when braking from 100?km/h. The applicability of these results is studied by investigating the approach for different vehicle speeds and actuator stroke limitations. It is shown that substantial improvements in the braking distance can also be found for lower velocities, and that the actuator strokes are an important parameter. To investigate the potential of implementing these findings in a real vehicle, a validated detailed vehicle model equipped with active struts is analysed. Simplified control laws, appropriate for on-board implementation and based on knowledge of the optimised solution, are proposed and evaluated. The results show that substantial improvements of the braking ability, and thus safety, can be made using this simplified approach. Particle model simulations have been made to explain the underlying physical mechanisms and limitations of the approach. These results provide valuable guidance on how active suspension can be used to achieve significant improvements in vehicle performance with reasonable complexity and energy consumption.     

An integrated control strategy for the composite braking system of an electric vehicle with independently driven axles

For an electric vehicle with independently driven axles, an integrated braking control strategy was proposed to coordinate the regenerative braking and the hydraulic braking. The integrated strategy includes three modes, namely the hybrid composite mode, the parallel composite mode and the pure hydraulic mode. For the hybrid composite mode and the parallel composite mode, the coefficients of distributing the braking force between the hydraulic braking and the two motors' regenerative braking were optimised offline, and the response surfaces related to the driving state parameters were established. Meanwhile, the six-sigma method was applied to deal with the uncertainty problems for reliability. Additionally, the pure hydraulic mode is activated to ensure the braking safety and stability when the predictive failure of the response surfaces occurs. Experimental results under given braking conditions showed that the braking requirements could be well met with high braking stability and energy regeneration rate, and the reliability of the braking strategy was guaranteed on general braking conditions.     

Active control strategy on a catenary–pantograph validated model

Dynamic simulation methods have become essential in the design process and control of the catenary–pantograph system, overall since high-speed trains and interoperability criteria are getting very trendy. This paper presents an original hardware-in-the-loop (HIL) strategy aimed at integrating a multicriteria active control within the catenary–pantograph dynamic interaction. The relevance of HIL control systems applied in the frame of the pantograph is undoubtedly increasing due to the recent and more demanding requirements for high-speed railway systems. Since the loss of contact between the catenary and the pantograph leads to arcing and electrical wear, and too high contact forces cause mechanical wear of both the catenary wires and the strips of the pantograph, not only prescribed but also economic and performance criteria ratify such a relevance. Different configurations of the proportional-integral-derivative (PID) controller are proposed and applied to two different plant systems. Since this paper is mainly focused on the control strategy, both plant systems are simulation models though the methodology is suitable for a laboratory bench. The strategy of control involves a multicriteria optimisation of the contact force and the consumption of the energy supplied by the control force, a genetic algorithm has been applied for this purpose. Thus, the PID controller is fitted according to these conflicting objectives and tested within a nonlinear lumped model and a nonlinear finite element model, being the last one validated against the European Standard EN 50318. Finally, certain tests have been accomplished in order to analyse the robustness of the control strategy. Particularly, the relevance or the plant simulation, the running speed and the instrumentation time delay are studied in this paper.     

Hierarchical optimisation of the design parameters of a vehicle suspension system

This paper presents a design methodology for the mechanical systems entitled First Design. It is based on a hierarchical organisation of the design, taking into account the notion of robustness at an early phase of the project. The aim is to improve the quality of the system in order to make it robust, less sensitive to the variability of the external parameters and design parameters. We distinguish two main stages of the design cycle: one concerning functional parameters and another concerning physical parameters. The methodology is based on simplified models, on sensitivity analysis and on robust multi-objective optimisation. As an example, the methodology will be applied to the optimisation of vehicle suspension system design parameters. For each stage of the hierarchical design, adapted simplified models, sensitivity analyses and optimisation processes will be studied and applied to our vehicle suspension system.     

基于多目标遗传算法的高速公路多目标路面养护决策优化

高速公路多目标路面养护决策优化是高速公路路面养护决策优化未来发展的趋势,也是目前研究的热点。针对传统数学规划方法用于高速公路多目标路面养护决策优化的不足,引入了目前在多目标优化领域应用较多的带精英策略的非支配排序遗传算法NSGA-Ⅱ。将NSGA-Ⅱ应用于高速公路多目标路面养护决策优化问题中,仿真结果表明其性能优于传统的数学规划方法,具有广阔的应用前景。     

A systematic review of route optimisation and pre-emption methods for emergency vehicles

ABSTRACT

Reducing the travel time of emergency vehicles (EVs) is an effective way to improve critical services such as ambulance, fire, and police. Route optimisation and pre-emption are powerful techniques used to reduce EV travel time. This paper presents a systematic literature review of optimisation and pre-emption techniques for routing EVs. A detailed classification of existing techniques is presented along with critical analysis and discussion. The study observes the limitations of existing routing systems and lack of real-world applications of the proposed pre-emption systems, leading to several interesting and important knowledge and implementation gaps that require further investigation. These gaps include optimisations using real-time dynamic traffic data, considering time to travel as a critical parameter within dynamic route planning algorithms, considering advanced algorithms, assessing and minimising the effects of EV routing on other traffic, and addressing safety concerns in traffic networks containing multiple EVs at the same time.     

An online speed profile generation approach for efficient airport ground movement

The precise guidance and control of taxiing aircraft based on four-dimensional trajectories (4DTs) has been recognised as a promising means to ensure safe and efficient airport ground movement in the context of ever growing air traffic demand. In this paper, a systematic approach for online speed profile generation is proposed. The aim is to generate fuel-efficient speed profiles respecting the timing constraints imposed by routing and scheduling, which ensures conflict-free movement of aircraft in the planning stage. The problem is first formulated as a nonlinear optimisation model, which uses a more flexible edge-based speed profile definition. A decomposed solution approach (following the framework of matheuristic) is then proposed to generate feasible speed profiles in real time. The decomposed solution approach reduces the nonlinear optimisation model into three tractable constituent problems. The control point arrival time allocation problem is solved using linear programming. The control point speed allocation problem is solved using particle swarm optimisation. And the complete speed profile between control points is determined using enumeration. Finally, improved speed profiles are generated through further optimisation upon the feasible speed profiles. The effectiveness and advantages of the proposed approach are validated using datasets of real-world airports.     

Optimisation of active suspension control inputs for improved vehicle ride performance

A collocation-type control variable optimisation method is used in the paper to analyse to which extent the fully active suspension (FAS) can improve the vehicle ride comfort while preserving the wheel holding ability. The method is first applied for a cosine-shaped bump road disturbance of different heights, and for both quarter-car and full 10 degree-of-freedom vehicle models. A nonlinear anti-wheel hop constraint is considered, and the influence of bump preview time period is analysed. The analysis is then extended to the case of square- or cosine-shaped pothole with different lengths, and the quarter-car model. In this case, the cost function is extended with FAS energy consumption and wheel damage resilience costs. The FAS action is found to be such to provide a wheel hop over the pothole, in order to avoid or minimise the damage at the pothole trailing edge. In the case of long pothole, when the FAS cannot provide the wheel hop, the wheel is travelling over the pothole bottom and then hops over the pothole trailing edge. The numerical optimisation results are accompanied by a simplified algebraic analysis.