Analyzing pedestrian head injury to design pedestrian-friendly hoods

Head injuries are a major cause of fatalities in pedestrian-car accidents. The HIC (Head Injury Criterion) value, a measure of the fatality risk of a head injury, is calculated from the acceleration of the head’s center of gravity (henceforth, head center) resulting from a head impact. The pedestrian’s head does not impact the hood at a direction normal to the hood’s surface. The direction of motion of the head center may change extremely rapidly upon impact, and normal acceleration may also significantly contribute to the resultant acceleration of the head center. Therefore, pedestrian head protection studies should consider how normal acceleration contributes to the resultant acceleration of the head center. It is necessary to control the resultant acceleration of the head center to produce an optimal characteristic pulse. This study analyzes the composition and variations of the head’s acceleration in head-to-hood impacts, focusing on exactly how the normal and tangential components of the acceleration contribute to the resultant acceleration of the head center. This study also considers how structural design parameters affect each component of the resultant acceleration. Methods to control the resultant acceleration of the head center to produce an optimal characteristic pulse can be proposed based on the results of this study. The analytical models and the results of this study contribute to efforts to design vehicle hoods and pave the way for developing pedestrian protection technologies.     

Neural-empirical tyre model based on recursive lazy learning under combined longitudinal and lateral slip conditions

The behaviour of the tyre plays an important role in the vehicle handling. An accurate tyre model that estimates these forces and moments it is highly essential for the studies of vehicle behaviour. For the last ten years neural networks have attracted a great deal of attention in vehicle dynamics and control. Neural networks have been effectively applied to model complex systems due to their good learning capability. In this paper a recursive lazy learning method based on neural networks is considered to model the tyre characteristics under combined braking and cornering. The proposed method is validated by comparison with experimental obtained responses. Results show the estimated model correlates very well with the data obtained experimentally. Moreover, the neural model proposed allows to include the asymetric tyre behaviour in the tyre model without difficulty.     

Efficiency improvement for an unthrottled SI engine at part load

Variable valve timing (VVT) and cylinder deactivation (CDA) are promising methods in reducing fuel consumption and emission at part load in SI engines. An SI engine which uses electromagnetic valvetrain (EMV) will eliminate flow restriction from the throttle valve and produce higher indicated mean efficiency pressure (IMEP) due to the disabling of some of the working cylinders at part load. Therefore, pumping loss can be significantly reduced at part-load conditions. In addition, duration and timing of valve events are variably controlled at different operating conditions. This contributes to the improvement of engine efficiency. In this study, a dynamic model of an unthrottled SI engine has been developed to simulate the engine cycle. The model uses an EMV system that allows valvetrain control and cylinder deactivation techniques to be carried out in simulation flexibly. The simulated results find the optimal valve timing for different engine speeds. The optimal timing of intake valve closing depends on engine speed linearly, while the intake valve opening insignificantly influences engine performance. Additionally, this study also shows that cylinder deactivation modes can be successfully applied in improving engine efficiency at different engine loads. Different cylinder deactivation strategies have been applied for the full range of engine loads. It is concluded that the two-cylinder deactivation mode (50% CDA) considerably improves fuel consumption at low engine load. Meanwhile, one-cylinder deactivation (25% CDA) is an optimal fuel economy mode at medium engine load. With proper uses of VVT and CDA strategies, the efficiency of an SI engine can be increased more than 30% at low engine load and 11.7 % at medium engine load.     

Bees-algorithm-based optimization of component size and control strategy parameters for parallel hybrid electric vehicles

This paper presents the optimization of key component sizes and control strategy for parallel hybrid electric vehicles (parallel HEVs) using the bees algorithm (BA). The BA is an intelligent optimization tool that mimics the food foraging behavior of honey bees. Parallel HEV configuration and electric assist control strategy were used to conduct the research. The values of the key component size and the control strategy parameters were adjusted according to the BA to minimize the weighted sum of fuel consumption (FC) and emissions, while the vehicle performance satisfies the PNGV constraints. In this research, the software ADVISOR was used as the simulation tool, and the driving cycles FTP, ECE-EUDC and UDDS were employed to evaluate FC, emission and dynamic performance. The results demonstrate that the BA is a powerful tool in parallel HEV optimization to determine the optimal parameters of component sizes and control strategy, resulting in the improvement of FC and emissions without sacrificing vehicle performance. In addition, the BA is able to define a global solution with a high rate of convergence.     

Electro-hydraulic braking system for autonomous vehicles

Reducing the number of traffic accidents is a declared target of most governments. Since dependence on driver reaction is the main cause of road accidents, it would be advisable to replace the human factor in some driving-related tasks with automated solutions. To automate a vehicle, it is necessary to control the actuators of a car, i.e., the steering wheel, accelerator, and brake. This paper presents the design and implementation of an electro-hydraulic braking system consisting of a pump and various valves, allowing the control computer to stop the car. It is assembled in conjunction with the original circuit for the sake of robustness and to permit the two systems to halt the car independently. This system was developed for installation in a commercial Citroën C3 Pluriel of the AUTOPIA program. Various tests were carried out to verify its correct operation, and an experiment showing the integration of the system into the longitudinal control of the car is described.     

Torsional stiffness and weight optimization of a real bus structure

In this paper, the structural optimization of a real bus structure is proposed. The proposed optimization has been accomplished by means of genetic algorithms. The structural behavior of the bus structure when subjected to weight and torsion was also analyzed using the finite element method (FEM). The results demonstrate that improved weight and torsional stiffness are achieved with the optimized structure.     

Macroscopic relations of urban traffic variables: Bifurcations, multivaluedness and instability

Recent experimental work has shown that the average flow and average density within certain urban networks are related by a unique, reproducible curve known as the Macroscopic Fundamental Diagram (MFD). For networks consisting of a single route this MFD can be predicted analytically; but when the networks consist of multiple overlapping routes experience shows that the flows observed in congestion for a given density are less than those one would predict if the routes were homogeneously congested and did not overlap. These types of networks also tend to jam at densities that are only a fraction of their routes’ average jam density.This paper provides an explanation for these phenomena. It shows that, even for perfectly homogeneous networks with spatially uniform travel patterns, symmetric equilibrium patterns with equal flows and densities across all links are unstable if the average network density is sufficiently high. Instead, the stable equilibrium patterns are asymmetric. For this reason the networks jam at lower densities and exhibit lower flows than one would predict if traffic was evenly distributed.Analysis of small idealized networks that can be treated as simple dynamical systems shows that these networks undergo a bifurcation at a network-specific critical density such that for lower densities the MFDs have predictably high flows and are univalued, and for higher densities the order breaks down. Microsimulations show that this bifurcation also manifests itself in large symmetric networks. In this case though, the bifurcation is more pernicious: once the network density exceeds the critical value, the stable state is one of complete gridlock with zero flow. It is therefore important to ensure in real-world applications that a network’s density never be allowed to approach this critical value.Fortunately, analysis shows that the bifurcation’s critical density increases considerably if some of the drivers choose their routes adaptively in response to traffic conditions. So far, for networks with adaptive drivers, bifurcations have only been observed in simulations, but not (yet) in real life. This could be because real drivers are more adaptive than simulated drivers and/or because the observed real networks were not sufficiently congested.     

Probabilistic Fatigue Failure Analysis of a Railroad Freight Car

The critical components of railroad fraight cars are subjected to fluctuating stresses and, therefore, vulnerable to fatigue damage. These fluctuating stresses result from different motions of the car when it travels along a track and is subjected to various track irregularities. Both the track irregularities and corresponding motions are highly random. Therefore, the fatigue damage can only be determined by means of a percentage probability level. This paper describes a probability-based method for evaluating fatigue damage in a freight car. The effect of uncertain boundary conditions for the car in the calculations of fatigue damage is also discussed. The applications of the method to carbody design and assessment of fatigue life are also explained     

Testbed for evaluation of vehicular detection systems

Reliable and robust detection systems are the cornerstone in the efficient and proper functioning of vehicle infrastructure integration. This paper presents the design and implementation of a testbed for evaluating vehicular detection systems. The development of the testbed involved design of the hardware setup required for real‐time monitoring of the sensors, programming the devices for data capture, and development of algorithms to automate the analysis of the recorded data. The methodology used to calibrate and validate the algorithms to automate the analysis of the data is presented as well. Although the testbed is presented in the context of evaluation of video detection systems at signalized intersections, it can be used for evaluating any vehicular detection systems. Copyright © 2010 John Wiley & Sons, Ltd.