Vehicle speed and rural automotive crash injury. Part I: estimated traveling speed and fatalities.

Public Health Service, Bethesda, Md.

Effects of vehicle speed in structural health monitoring from operational conditions of bridges

The effects of vehicle speed for Structural Health Monitoring (SHM) of bridges under operational conditions are studied in this paper. The moving vehicle is modelled as a single degree oscillator traversing a damaged beam at a constant speed. The bridge is modelled as simply supported Euler-Bernoulli beam with a breathing crack. The breathing crack is treated as a nonlinear system with bilinear stiffness characteristics related to the opening and closing of crack. The unevenness of the bridge deck is modelled using road classification according to ISO 8606:1995(E). The stochastic description of the unevenness of the road surface is used as an aid to monitor the health of the structure in its operational condition. Numerical simulations are conducted considering the effects of changing vehicle speed with regards to cumulant based statistical damage detection parameters. The detection and calibration of damage at different levels is based on an algorithm dependent on responses of the damaged beam due to passages of the load. Possibilities of damage detection and calibration under benchmarked and non-benchmarked cases are considered. Sensitivity of calibration values is studied. The findings of this paper are important for establishing the expectations from different vehicle speeds on a bridge for damage detection purposes using bridge-vehicle interaction where the bridge does not need to be closed for monitoring. The identification of bunching of these speed ranges provides guidelines for using the methodology developed in the paper.

The Optimal trigger speed of vehicle activated signs

The thesis aims to elaborate on the optimum trigger speed for Vehicle Activated Signs (VAS) and to study the effectiveness of VAS trigger speed on drivers’ behaviour. Vehicle activated signs (VAS) are speed warning signs that are activated by individual vehicle when the driver exceeds a speed threshold. The threshold, which triggers the VAS, is commonly based on a driver speed, and accordingly, is called a trigger speed. At present, the trigger speed activating the VAS is usually set to a constant value and does not consider the fact that an optimal trigger speed might exist. The optimal trigger speed significantly impacts driver behaviour. In order to be able to fulfil the aims of this thesis, systematic vehicle speed data were collected from field experiments that utilized Doppler radar. Further calibration methods for the radar used in the experiment have been developed and evaluated to provide accurate data for the experiment. The calibration method was bidirectional; consisting of data cleaning and data reconstruction. The data cleaning calibration had a superior performance than the calibration based on the reconstructed data. To study the effectiveness of trigger speed on driver behaviour, the collected data were analysed by both descriptive and inferential statistics. Both descriptive and inferential statistics showed that the change in trigger speed had an effect on vehicle mean speed and on vehicle standard deviation of the mean speed. When the trigger speed was set near the speed limit, the standard deviation was high. Therefore, the choice of trigger speed cannot be based solely on the speed limit at the proposed VAS location. The optimal trigger speeds for VAS were not considered in previous studies. As well, the relationship between the trigger value and its consequences under different conditions were not clearly stated. The finding from this thesis is that the optimal trigger speed should be primarily based on lowering the standard deviation rather than lowering the mean speed of vehicles. Furthermore, the optimal trigger speed should be set near the 85th percentile speed, with the goal of lowering the standard deviation.

Koala mortality on roads in south-east Queensland: the koala speed-zone trial

In 1995, the Queensland Parks and Wildlife Service, the Queensland Department of Main Roads and Redland Shire Council initiated the Koala Speed Zone Trial in the Koala Coast, south-east Queensland. The aim of the trial was to assess the effect of differential speed signs on the number of koalas ( Phascolarctos cinereus) hit by vehicles in the Koala Coast from 1995 to 1999. On the basis of information collected by the Queensland Parks and Wildlife Service 1407 koalas were hit by vehicles in the Koala Coast during the five-year study ( mean 281 koalas per year, range 251 - 315). Monitoring of vehicle speeds by the Queensland Department of Main Roads suggested that there was no significant reduction in vehicle speed during the trial period from August to December. Consequently, there was no evidence to suggest that a reduction in the number of koalas hit by vehicles occurred during the trial. Approximately 70% of koalas were hit on arterial and sub-arterial roads and approximately 83% did not survive. The location of each koala hit was recorded and the signed speed limit of the road was noted. Most koalas that were hit by vehicles were young healthy males. Pooling of data on koala collisions and road speed limits suggested that the proportion of koalas that survived being hit by vehicles was slightly higher on roads with lower speed limits. However, vehicle speed was not the only factor that affected the number of koalas hit by vehicles. It is suggested that habitat destruction, koala density and traffic volume also contribute to road-associated koala mortality in the Koala Coast.

Temporary Speed Hump Impact Evaluation, 2002

The main objective of this research was to evaluate the impact of temporary speed humps and speed tables on vehicle speeds, vehicle speed profiles, and traffic volumes along local and/or collector streets in several rural Iowa cities. A 25 mile per hour (mph) temporary speed hump and a 30 mph temporary speed table, both made of recycled rubber, were purchased to test the impact of temporary devices. Two cities volunteered and the speed hump/table was installed on two test streets in the city of Atlantic (Roosevelt Drive and Redwood Drive) and one test street in the city of Le Claire (Canal Shore Drive). The speed hump was installed first and then converted to a speed table. Each device was installed for a period of at least two weeks at the same location. Speed, volume, and resident opinion data were then collected and evaluated.

Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means

Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.

Optimized HOG for on-road video based vehicle verification

Vision-based object detection from a moving platform becomes particularly challenging in the field of advanced driver assistance systems (ADAS). In this context, onboard vision-based vehicle verification strategies become critical, facing challenges derived from the variability of vehicles appearance, illumination, and vehicle speed. In this paper, an optimized HOG configuration for onboard vehicle verification is proposed which not only considers its spatial and orientation resolution, but descriptor processing strategies and classification. An in-depth analysis of the optimal settings for HOG for onboard vehicle verification is presented, in the context of SVM classification with different kernels. In contrast to many existing approaches, the evaluation is realized in a public and heterogeneous database of vehicle and non-vehicle images in different areas of the road, rendering excellent verification rates that outperform other similar approaches in the literature.

Co-simulation Methodologies for Hybrid and Electric Vehicle Dynamics

In recent decades, full electric and hybrid electric vehicles have emerged as an alternative to conventional cars due to a range of factors, including environmental and economic aspects. These vehicles are the result of considerable efforts to seek ways of reducing the use of fossil fuel for vehicle propulsion. Sophisticated technologies such as hybrid and electric powertrains require careful study and optimization. Mathematical models play a key role at this point. Currently, many advanced mathematical analysis tools, as well as computer applications have been built for vehicle simulation purposes. Given the great interest of hybrid and electric powertrains, along with the increasing importance of reliable computer-based models, the author decided to integrate both aspects in the research purpose of this work. Furthermore, this is one of the first final degree projects held at the ETSII (Higher Technical School of Industrial Engineers) that covers the study of hybrid and electric propulsion systems. The present project is based on MBS3D 2.0, a specialized software for the dynamic simulation of multibody systems developed at the UPM Institute of Automobile Research (INSIA). Automobiles are a clear example of complex multibody systems, which are present in nearly every field of engineering. The work presented here benefits from the availability of MBS3D software. This program has proven to be a very efficient tool, with a highly developed underlying mathematical formulation. On this basis, the focus of this project is the extension of MBS3D features in order to be able to perform dynamic simulations of hybrid and electric vehicle models. This requires the joint simulation of the mechanical model of the vehicle, together with the model of the hybrid or electric powertrain. These sub-models belong to completely different physical domains. In fact the powertrain consists of energy storage systems, electrical machines and power electronics, connected to purely mechanical components (wheels, suspension, transmission, clutch…). The challenge today is to create a global vehicle model that is valid for computer simulation. Therefore, the main goal of this project is to apply co-simulation methodologies to a comprehensive model of an electric vehicle, where sub-models from different areas of engineering are coupled. The created electric vehicle (EV) model consists of a separately excited DC electric motor, a Li-ion battery pack, a DC/DC chopper converter and a multibody vehicle model. Co-simulation techniques allow car designers to simulate complex vehicle architectures and behaviors, which are usually difficult to implement in a real environment due to safety and/or economic reasons. In addition, multi-domain computational models help to detect the effects of different driving patterns and parameters and improve the models in a fast and effective way. Automotive designers can greatly benefit from a multidisciplinary approach of new hybrid and electric vehicles. In this case, the global electric vehicle model includes an electrical subsystem and a mechanical subsystem. The electrical subsystem consists of three basic components: electric motor, battery pack and power converter. A modular representation is used for building the dynamic model of the vehicle drivetrain. This means that every component of the drivetrain (submodule) is modeled separately and has its own general dynamic model, with clearly defined inputs and outputs. Then, all the particular submodules are assembled according to the drivetrain configuration and, in this way, the power flow across the components is completely determined. Dynamic models of electrical components are often based on equivalent circuits, where Kirchhoff’s voltage and current laws are applied to draw the algebraic and differential equations. Here, Randles circuit is used for dynamic modeling of the battery and the electric motor is modeled through the analysis of the equivalent circuit of a separately excited DC motor, where the power converter is included. The mechanical subsystem is defined by MBS3D equations. These equations consider the position, velocity and acceleration of all the bodies comprising the vehicle multibody system. MBS3D 2.0 is entirely written in MATLAB and the structure of the program has been thoroughly studied and understood by the author. MBS3D software is adapted according to the requirements of the applied co-simulation method. Some of the core functions are modified, such as integrator and graphics, and several auxiliary functions are added in order to compute the mathematical model of the electrical components. By coupling and co-simulating both subsystems, it is possible to evaluate the dynamic interaction among all the components of the drivetrain. ‘Tight-coupling’ method is used to cosimulate the sub-models. This approach integrates all subsystems simultaneously and the results of the integration are exchanged by function-call. This means that the integration is done jointly for the mechanical and the electrical subsystem, under a single integrator and then, the speed of integration is determined by the slower subsystem. Simulations are then used to show the performance of the developed EV model. However, this project focuses more on the validation of the computational and mathematical tool for electric and hybrid vehicle simulation. For this purpose, a detailed study and comparison of different integrators within the MATLAB environment is done. Consequently, the main efforts are directed towards the implementation of co-simulation techniques in MBS3D software. In this regard, it is not intended to create an extremely precise EV model in terms of real vehicle performance, although an acceptable level of accuracy is achieved. The gap between the EV model and the real system is filled, in a way, by introducing the gas and brake pedals input, which reflects the actual driver behavior. This input is included directly in the differential equations of the model, and determines the amount of current provided to the electric motor. For a separately excited DC motor, the rotor current is proportional to the traction torque delivered to the car wheels. Therefore, as it occurs in the case of real vehicle models, the propulsion torque in the mathematical model is controlled through acceleration and brake pedal commands. The designed transmission system also includes a reduction gear that adapts the torque coming for the motor drive and transfers it. The main contribution of this project is, therefore, the implementation of a new calculation path for the wheel torques, based on performance characteristics and outputs of the electric powertrain model. Originally, the wheel traction and braking torques were input to MBS3D through a vector directly computed by the user in a MATLAB script. Now, they are calculated as a function of the motor current which, in turn, depends on the current provided by the battery pack across the DC/DC chopper converter. The motor and battery currents and voltages are the solutions of the electrical ODE (Ordinary Differential Equation) system coupled to the multibody system. Simultaneously, the outputs of MBS3D model are the position, velocity and acceleration of the vehicle at all times. The motor shaft speed is computed from the output vehicle speed considering the wheel radius, the gear reduction ratio and the transmission efficiency. This motor shaft speed, somehow available from MBS3D model, is then introduced in the differential equations corresponding to the electrical subsystem. In this way, MBS3D and the electrical powertrain model are interconnected and both subsystems exchange values resulting as expected with tight-coupling approach.When programming mathematical models of complex systems, code optimization is a key step in the process. A way to improve the overall performance of the integration, making use of C/C++ as an alternative programming language, is described and implemented. Although this entails a higher computational burden, it leads to important advantages regarding cosimulation speed and stability. In order to do this, it is necessary to integrate MATLAB with another integrated development environment (IDE), where C/C++ code can be generated and executed. In this project, C/C++ files are programmed in Microsoft Visual Studio and the interface between both IDEs is created by building C/C++ MEX file functions. These programs contain functions or subroutines that can be dynamically linked and executed from MATLAB. This process achieves reductions in simulation time up to two orders of magnitude. The tests performed with different integrators, also reveal the stiff character of the differential equations corresponding to the electrical subsystem, and allow the improvement of the cosimulation process. When varying the parameters of the integration and/or the initial conditions of the problem, the solutions of the system of equations show better dynamic response and stability, depending on the integrator used. Several integrators, with variable and non-variable step-size, and for stiff and non-stiff problems are applied to the coupled ODE system. Then, the results are analyzed, compared and discussed. From all the above, the project can be divided into four main parts: 1. Creation of the equation-based electric vehicle model; 2. Programming, simulation and adjustment of the electric vehicle model; 3. Application of co-simulation methodologies to MBS3D and the electric powertrain subsystem; and 4. Code optimization and study of different integrators. Additionally, in order to deeply understand the context of the project, the first chapters include an introduction to basic vehicle dynamics, current classification of hybrid and electric vehicles and an explanation of the involved technologies such as brake energy regeneration, electric and non-electric propulsion systems for EVs and HEVs (hybrid electric vehicles) and their control strategies. Later, the problem of dynamic modeling of hybrid and electric vehicles is discussed. The integrated development environment and the simulation tool are also briefly described. The core chapters include an explanation of the major co-simulation methodologies and how they have been programmed and applied to the electric powertrain model together with the multibody system dynamic model. Finally, the last chapters summarize the main results and conclusions of the project and propose further research topics. In conclusion, co-simulation methodologies are applicable within the integrated development environments MATLAB and Visual Studio, and the simulation tool MBS3D 2.0, where equation-based models of multidisciplinary subsystems, consisting of mechanical and electrical components, are coupled and integrated in a very efficient way.

Vehicle-induced force on pedestrians

The main object of this study is to contribute to the study of the train-induced force on pedestrians with a theoretical model based on unsteady potential flow. The same method can be applied to other bodies and other kind of moving vehicles. The outcome of this theoretical model is that the force coefficient (referred to the vehicle speed and the pedestrian cross-section diameter) acting on the pedestrian are proportional to a single parameter which involves the pedestrian cross-section diameter, the vehicle cross-section area and the distance between the pedestrian and the vehicle. The results of the present model concerning the change in modulus and orientation experienced by the pedestrian, as the vehicles pass by, has a similar appearance to that considered in the European standards. The results obtained are mainly qualitative because of the simplifying assumptions needed to obtain a simple formulation leading to analytical results, except in the case of a vehicle with streamlined front shapes, where quantitative results can be expected.

Investigation of the Effect of Speed on the Dynamic Impact Factor for Bridges with Different Entrance Conditions, 2016

The dynamic interaction of vehicles and bridges results in live loads being induced into bridges that are greater than the vehicle’s static weight. To limit this dynamic effect, the Iowa Department of Transportation (DOT) currently requires that permitted trucks slow to five miles per hour and span the roadway centerline when crossing bridges. However, this practice has other negative consequences such as the potential for crashes, impracticality for bridges with high traffic volumes, and higher fuel consumption. The main objective of this work was to provide information and guidance on the allowable speeds for permitted vehicles and loads on bridges .A field test program was implemented on five bridges (i.e., two steel girder bridges, two pre-stressed concrete girder bridges, and one concrete slab bridge) to investigate the dynamic response of bridges due to vehicle loadings. The important factors taken into account during the field tests included vehicle speed, entrance conditions, vehicle characteristics (i.e., empty dump truck, full dump truck, and semi-truck), and bridge geometric characteristics (i.e., long span and short span). Three entrance conditions were used: As-is and also Level 1 and Level 2, which simulated rough entrance conditions with a fabricated ramp placed 10 feet from the joint between the bridge end and approach slab and directly next to the joint, respectively. The researchers analyzed and utilized the field data to derive the dynamic impact factors (DIFs) for all gauges installed on each bridge under the different loading scenarios.

Sistema de Variação de Lastro para Controlo de Movimento Vertical de Veículo Subaquático

O principal motivo para a realização deste trabalho consistiu no desenvolvimento de tecnologia robótica, que permitisse o mergulho e ascenção de grandes profundidades de uma forma eficiente. O trabalho realizado contemplou uma fase inicial de análise e estudo dos sistemas robóticos existentes no mercado, bem como métodos utilizados identificando vantagens e desvantagens em relação ao tipo de veículo pretendido. Seguiu-se uma fase de projeto e estudo mecânico, com o intuito de desenvolver um veículo com variação de lastro através do bombeamento de óleo para um reservatório exterior, para variar o volume total do veículo, variando assim a sua flutuabilidade. Para operar a grande profundidade com AUV’s é conveniente poder efetuar o trajeto up/down de forma eficiente e a variação de lastro apresenta vantagens nesse aspeto. No entanto, contrariamente aos gliders o interesse está na possibilidade de subir e descer na vertical. Para controlar a flutuabilidade e ao mesmo tempo analisar a profundidade do veículo em tempo real, foi necessario o uso de um sistema de processamento central que adquirisse a informação do sensor de pressão e comunicasse com o sistema de variação de lastro, de modo a fazer o controlo de posicionamento vertical desejado. Do ponto de vista tecnológico procurou-se desenvolver e avaliar soluções de variação de volume intermédias entre as dos gliders (poucas gramas) e as dos ROV’s workclass (dezenas ou centenas de kilogramas). Posteriormente, foi desenvolvido um simulador em matlab (Simulink) que reflete o comportamento da descida do veículo, permitindo alterar parâmetros do veículo e analisar os seus resultados práticos, de modo a poder ajustar o veículo real. Nos resultados simulados verificamos o cálculo das velocidades limite atingidas pelo veículo com diferentes coeficientes de atrito, bem como o comportamento da variação de lastro do veículo no seu deslocamento vertical. Sistema de Variação de Lastro para Controlo de Movimento Vertical de Veículo Subaquático Por fim, verificou-se ainda a capacidade de controlo do veículo para uma determinada profundiade, e foi feita a comparação entre estas simulações executadas com parâmetros muito próximos do ensaio real e os respetivos ensaios reais.

Mobility and Safety Impacts of Winter Storm Events in a Freeway Environment Final Report, February 2000

Several factors influence a driver’s decision to travel, choice of vehicle speed, and the safety of a particular trip. These factors include, among others, the trip purpose, time of day, traffic volumes, weather and roadway conditions, and the range of vehicle speeds on the roadway. The main goal of the research project summarized in this report was the investigation of winter storm event impacts on the volume, safety, and speed characteristics of interstate traffic flow.

Automated Traffic/Truck Weight Monitoring Equipment (Weigh-in-Motion), HR-282, 1988

This report documents work undertaken in the demonstration of a low-cost Automatic Weight and Classification System (AWACS). An AWACS procurement specification and details of the results of the project are also included. The intent of the project is to support and encourage transferring research knowledge to state and local agencies and manufacturers through field demonstrations. Presently available, Weigh-in-Motion and Classification Systems are typically too expensive to permit the wide deployment necessary to obtain representative vehicle data. Piezo electric technology has been used in the United Kingdom and Europe and is believed to be the basic element in a low-cost AWACS. Low-cost systems have been installed at two sites, one in Portland Cement Concrete (PCC) pavement in Iowa and the other in Asphaltic Cement Concrete (ACC) pavement in Minnesota to provide experience with both types of pavement. The systems provide axle weights, gross vehicle weight, axle spacing, vehicle classification, vehicle speed, vehicle count, and time of arrival. In addition, system self-calibration and a method to predict contact tire pressure is included in the system design. The study has shown that in the PCC pavement, the AWACS is capable of meeting the needs of state and federal highway agencies, producing accuracies comparable to many current commercial WIM devices. This is being achieved at a procurement cost of substantially less than currently available equipment. In the ACC pavement the accuracies were less than those observed in the PCC pavement which is concluded to result from a low pavement rigidity at this site. Further work is needed to assess the AWACS performance at a range of sites in ACC pavements.

Performance Measurement for Highway Winter Maintenance Operations, TR-491, 2009

The goal of this research project was to develop a method to measure the performance of a winter maintenance program with respect to the task of providing safety and mobility to the travelling public. Developing these measures required a number of steps, each of which was accomplished. First, the impact of winter weather on safety (crash rates) and mobility (average vehicle speeds were measured by a combination of literature reviews and analysis of Iowa Department of Transportation traffic and Road Weather Information System data. Second, because not all winter storms are the same in their effects on safety and mobility, a method had to be developed to determine how much the various factors that describe a winter storm actually change safety and mobility. As part of this effort a storm severity index was developed, which ranks each winter storm on a scale between 0 (a very benign storm) and 1 (the worst imaginable storm). Additionally a number of methods of modeling the relationships between weather, winter maintenance actions and road surface conditions were developed and tested. The end result of this study was a performance measure based on average vehicle speed. For a given class of road, a maximum expected average speed reduction has been identified. For a given storm, this maximum expected average speed reduction is modified by the storm severity index to give a target average speed reduction. Thus, if for a given road the maximum expected average speed reduction is 20 mph, and the storm severity for a particular storm is 0.6, then the target average speed reduction for that road in that storm is 0.6 x 20 mph or 12 mph. If the average speed on that road during and after the storm is only 12 mph or less than the average speed on that road in good weather conditions, then the winter maintenance performance goal has been met.