基于Adams和Matlab联合的汽车悬架系统仿真分析

伴随着虚拟样机技术的不断发展,虚拟物理模型与控制模型联合仿真技术日趋成熟。文中利用ADAMS软件,建立了二分之一车体四自由度汽车主动悬架的虚拟模型。通过集成车辆主动悬架系统的动力学方程,搭建了基于ADAMS和MATLAB联合的汽车悬架系统仿真平台。在此基础上,比较分析了某轿车汽车车身垂直加速度响应和车身俯仰角加速度响应,该模拟结果与文献[1]数学模型的结果基本吻合,从而验证了系统仿真平台正确性。     

Short-term speed predictions exploiting big data on large urban road networks

Big data from floating cars supply a frequent, ubiquitous sampling of traffic conditions on the road network and provide great opportunities for enhanced short-term traffic predictions based on real-time information on the whole network. Two network-based machine learning models, a Bayesian network and a neural network, are formulated with a double star framework that reflects time and space correlation among traffic variables and because of its modular structure is suitable for an automatic implementation on large road networks. Among different mono-dimensional time-series models, a seasonal autoregressive moving average model (SARMA) is selected for comparison. The time-series model is also used in a hybrid modeling framework to provide the Bayesian network with an a priori estimation of the predicted speed, which is then corrected exploiting the information collected on other links. A large floating car data set on a sub-area of the road network of Rome is used for validation. To account for the variable accuracy of the speed estimated from floating car data, a new error indicator is introduced that relates accuracy of prediction to accuracy of measure. Validation results highlighted that the spatial architecture of the Bayesian network is advantageous in standard conditions, where a priori knowledge is more significant, while mono-dimensional time series revealed to be more valuable in the few cases of non-recurrent congestion conditions observed in the data set. The results obtained suggested introducing a supervisor framework that selects the most suitable prediction depending on the detected traffic regimes.     

The impact of road grade on carbon dioxide (CO2) emission of a passenger vehicle in real-world driving

To accurately estimate real-world vehicle emission at 1 Hz the road grade for each second of data must be quantified. Failure to incorporate road grade can result in over or underestimation of a vehicle’s power output and hence cause inaccuracy in the instantaneous emission estimate. This study proposes a simple LiDAR (Light Detection And Ranging) – GIS (Geographic Information System) road grade estimation methodology, using GIS software to interpolate the elevation for each second of data from a Digital Terrain Map (DTM). On-road carbon dioxide (CO₂) emissions from a passenger car were recorded by Portable Emission Measurement System (PEMS) over 48 test laps through an urban-traffic network. The test lap was divided into 8 sections for micro-scale analysis. The PHEM instantaneous emission model (Hausberger, 2003) was employed to estimate the total CO₂ emission through each lap and section. The addition of the LiDAR-GIS road grade to the PHEM modelling improved the accuracy of the CO₂ emission predictions. The average PHEM estimate (with road grade) of the PEMS measured section total CO₂ emission (n = 288) was 93%, with 90% of the PHEM estimates between 80% and 110% of the PEMS recorded value. The research suggests that instantaneous emission modelling with LiDAR-GIS calculated road grade is a viable method for generating accurate real-world micro-scale CO₂ emission estimates. The sensitivity of the CO₂ emission predictions to road grade was also tested by lessening and exaggerating the gradient profiles, and demonstrates that assuming a flat profile could cause considerable error in real-world CO₂ emission estimation.     

Autonomous cars: The tension between occupant experience and intersection capacity

Systems that enable high levels of vehicle-automation are now beginning to enter the commercial marketplace. Road vehicles capable of operating independently of real-time human control under an increasing set of circumstances will likely become more widely available in the near future. Such vehicles are expected to bring a variety of benefits. Two such anticipated advantages (relative to human-driver vehicle control) are said to be increased road network capacity and the freeing up of the driver-occupant’s time to engage in their choice of leisurely or economically-productive (non-driving) tasks.In this study we investigate the implications for intersection capacity and level-of-service of providing occupants of automated (without real-time human control), autonomously-operating (without vehicle-to-X communication) cars with ride quality that is equivalent (in terms of maximum rates of longitudinal and lateral acceleration) to two types of rail systems: [urban] light rail transit and [inter-urban] high-speed rail. The literature suggests that car passengers start experiencing discomfort at lower rates of acceleration than car drivers; it is therefore plausible that occupants of an autonomously-operating vehicle may wish to instruct their vehicle to maneuver in a way that provides them greater ride comfort than if the vehicle-control algorithm simply mimicked human-driving-operation.On the basis of traffic microsimulation analysis, we found that restricting the dynamics of autonomous cars to the acceleration/deceleration characteristics of both rail systems leads to reductions in a signalized intersection’s vehicle-processing capacity and increases in delay. The impacts were found to be larger when constraining the autonomous cars’ dynamics to the more-restrictive acceleration/deceleration profile of high-speed rail. The scenarios we analyzed must be viewed as boundary conditions, because autonomous cars’ dynamics were by definition never allowed to exceed the acceleration/deceleration constraints of the rail systems. Appropriate evidence regarding motorists’ preferences does not exist at present; establishing these preferences is an important item for the future research agenda.This paper concludes with a brief discussion of research needs to advance this line of inquiry.     

Speed behaviour of car drivers: A statistical analysis of acceptance of changes in speed policies in the Netherlands

Lowering the speed of car drivers will have positive impacts on environmental pollution and the number of road accidents. It is therefore a potentially interesting policy option for governments which want to reduce negative externalities of transport. In this paper, the acceptance of such policies is analysed by means of a survey questionnaire among car drivers and public transport users. First, an analysis is presented on the general speed behaviour, the behaviour on distinct road types, the acceptance of lower limits, and the acceptance and perception of electronic speed limiters. Next, a statistical analysis of subgroups is carried out. It is concluded that the speed of car drivers is, in general, not considered to be a main problematic issue by drivers and non-drivers; therefore, there is little scope for the acceptance of changes in speed policies. When speed policies are changed (lower limits), it seems to be most effective to emphasize safety aspects in order to increase the support of the public. However, psychological factors of speed behaviour may play an important role in this respect.     

Driving Forces behind the Growth of Per‐capita Car Driving Distance in the UK, 1970–2000

Abstract

Although per‐capita car trip distance (measured in passenger‐km) and car driving distance (measured in vehicle‐km) in the UK have kept increasing, their growth rates slowed considerably in the 1990s when compared with the 1970s and 1980s. The paper investigates the main driving forces behind the changes in car trip and car driving distances, and it examines the determining factors for the slow down of growth in the 1990s on the basis of the analysis of data from the National Travel Survey (1975/76, 1989/91, 1992/94, 1995/97 and 1999/2001). In particular, it emphasizes the significance of changes in car ownership levels as a key driving force and attempts to separate this ‘car ownership effect’ from other effects. The log‐mean Divisia index decomposition method is applied to measure the relative contribution of each effect. Separate analyses are undertaken according to trip purpose. Other underlying causes, such as changes in fuel price and road capacity, are also examined.     

Up‐to‐the‐minute information as we drive—how it can help road users and traffic management

Road transport of today has a substantial need for a better information system. The European research programmes PROMETHEUS and DRIVE offer the prospect of new techniques and strategies. The role of information in road transport is analysed from the viewpoint of the individual drivers and from the viewpoint of the traffic manager. All necessary information must be brought together and a complex data‐bank system for road transport should be installed. As examples of advanced information systems the concepts of the ‘Wolfsburg wave’ for in‐car speed recommendation and of the LISB field experiment in route guidance in Berlin are explained.     

Powertrain technologies and their impact on greenhouse gas emissions in key car markets

The role alternative car technologies may play in effectively tackling the problem of climate change is still highly uncertain. This paper aims at investigating possible impacts of car powertrain technologies on future energy demand and its corresponding greenhouse gas emissions until 2030. A system dynamics model covering nine car technologies in China, France, Germany, India, Japan and the United States was applied, with a focus on electric cars. Four main scenarios are constructed and sensitivity analysis undertaken. Greenhouse gas emissions from cars in the six countries are simulated to reach up to 2.6 gigatonnes in 2030 (a 13–32% increase between 2020 and 2030, depending on the scenario). The main conclusion from model-based policy analysis is that electric cars may have a positive contribution to emissions mitigation in the passenger road transport system. However, greenhouse gas emissions from cars arising from the combined effect of car manufacturing and scrappage and electricity generation processes are expected to grow more dramatically. As a result, actions that support both low-emission (re-)manufacturing and clean electricity generation are needed. These results complement accurate but static life cycle assessments and open the discussion for dynamic model assumptions.     

Agent-based simulation framework for mixed traffic of cars,pedestrians and trams

In this paper, we report on the construction of a new framework for simulating mixed traffic consisting of cars, trams, and pedestrians that can be used to support discussions about road management, signal control, and public transit. Specifically, a layered road structure that was designed for car traffic simulations was extended to interact with an existing one-dimensional (1D) car-following model and a two-dimensional (2D) discrete choice model for pedestrians. The car model, pedestrian model, and interaction rules implemented in the proposed framework were verified through simulations involving simple road environments. The resulting simulated values were in near agreement with the empirical data. We then used the proposed framework to assess the impact of a tramway extension plan for a real city. The simulation results showed that the impact of the proposed tramway on existing car traffic would not be serious, and by extension, implied that the proposed framework could help stakeholders decide on expansion scenarios that are satisfactory to both tram users and private car owners.     

Design policies for sight distance at stop-controlled intersections based on gap acceptance

The current AASHTO policy for sight distance at stop-controlled intersections is based on a model of the acceleration performance of a minor-road vehicle turning left or right onto a major road and the deceleration performance of the following major-road vehicle. This paper develops and quantifies an alternative intersection sight distance model based on gap acceptance. The paper describes field studies that were performed to determine the critical gaps appropriate for use in sight distance design. It is recommended that the sight distance along the major road for a passenger car at a stop-controlled intersection be based on a distance equal to 7.5 s of travel time at the design speed of the major road. Longer sight distances are recommended for minor-road approaches that have sufficient truck volumes to warrant consideration of a truck as the design vehicle. ©     

货运车型标准化专项治理管理系统设计与实现

货运车型标准化是国家运输行业结构调整及货运行业提质增效发展的重要工作手段与目标。从货运车型标准化转型治理工作的功能需求出发,以正在开展的常压液体危险货物罐车治理工作为基础,本文设计并实现了基于SSM架构的货运车型标准化专项治理管理系统。危险货物道路运输企业在系统中申报罐车信息,罐车检验机构基于车辆识别代码上传罐检报告,道路运输管理机构通过对罐车信息及关键报告进行审核,给予审核结果及意见。     

Theory of safety surrogates using vehicle trajectories in macroscopic and microscopic settings: Application to dynamic message signs controlled traffic at work zones

This paper presents a new mathematical framework for obtaining quantitative safety measure using macroscopic as well as microscopic traffic data. The safety surrogate obtained from the macroscopic data is in terms of analysis performed on vehicle trajectories obtained from the macroscopic data. This method of obtaining safety measure can be used for many different types of applications. The safety surrogate for the traffic dynamics are developed in terms of a new concept of Negative Speed Differentials (NSD) that involve a convolution of vehicle speed function obtained from vehicle trajectories and then performing the integration of the square of the output for its negative values. The framework is applicable to microscopic traffic dynamics as well where we can use car following models for microscopic dynamics or the LWR model for macroscopic dynamics. This paper then presents the use of this new safety surrogate on the development of a feedback control law for controlling traffic in work zones using Dynamic Message Signs. A hybrid dynamics model is used to represent the switching dynamics due to changing DMS messages. A feedback control design for choosing those messages is presented as well as a simple simulation example to show its application.     

Modeling time-of-day car use behavior: A Bayesian network approach

In this research, a Bayesian network (BN) approach is proposed to model the car use behavior of drivers by time of day and to analyze its relationship with driver and car characteristics. The proposed BN model can be categorized as a tree-augmented naive (TAN) Bayesian network. A latent class variable is included in this model to describe the unobserved heterogeneity of drivers. Both the structure and the parameters are learned from the dataset, which is extracted from GPS data collected in Toyota City, Japan. Based on inferences and evidence sensitivity analysis using the estimated TAN model, the effects of each single observed characteristic on car use measures are tested and found to be significant. The features of each category of the latent class are also analyzed. By testing the effect of each car use measure on every other measure, it is found that the correlations between car use measures are significant and should be considered in modeling car use behavior.     

Car ownership and access to jobs in Spain

The purpose of this paper is to assess the effect of urban structure on household car ownership in a context of rapid job and population decentralization. We capture the effect of urban structure through a measure of job accessibility to employment by public transport. An ordered probit explaining the number of cars per household is estimated as a function of individual, household and spatial variables. The data used in the analysis come from the Spanish Institute of Statistics’ 2001 Micro-census for the areas of Barcelona and Madrid. The results show that spatial variables play a significant role in explaining the probability of car ownership. We provide the car ownership elasticities with respect the job accessibility measure. Additionally, we carried out simulation exercises in which the expected number of vehicles decreases as accessibility improves.     

Transport energy consumption in mountainous roads. A comparative case study for internal combustion engines and electric vehicles in Andorra

This paper analyses transport energy consumption of conventional and electric vehicles in mountainous roads. A standard round trip in Andorra has been modelled in order to characterise vehicle dynamics in hilly regions. Two conventional diesel vehicles and their electric-equivalent models have been simulated and their performances have been compared. Six scenarios have been simulated to study the effects of factors such as orography, traffic congestion and driving style. The European fuel consumption and emissions test and Artemis urban driving cycles, representative of European driving cycles, have also been included in the comparative analysis. The results show that road grade has a major impact on fuel economy, although it affects consumption in different levels depending on the technology analysed. Electric vehicles are less affected by this factor as opposed to conventional vehicles, increasing the potential energy savings in a hypothetical electrification of the car fleet. However, electric vehicle range in mountainous terrains is lower compared to that estimated by manufacturers, a fact that could adversely affect a massive adoption of electric cars in the short term.     

Maximum car ownership under constraints of road capacity and parking space

This paper presents a model for determining the maximum number of cars by zones in view of the capacity of the road network and the number of parking spaces available. In other words, the proposed model is to examine whether existing road network and parking supply is capable of accommodating future zonal car ownership growth (or the reserve capacity in each zone); i.e. the potential maximum zonal car ownership growth that generates the road traffic within the network capacity and parking space constraints. In the proposed model, the vehicular trip production and attraction are dependent on the car ownership, available parking spaces and the accessibility measures by traffic zones. The model is formulated as a bi-level programming problem. The lower-level problem is an equilibrium trip distribution/assignment problem, while the upper-level problem is to maximize the sum of zonal car ownership by considering travellers’ route and destination choice behaviour and satisfying the network capacity and parking space constraints. A sensitivity analysis based heuristic algorithm is developed to solve the proposed bi-level car ownership problem and is illustrated with a numerical example.     

Proposed collision warning system for right-turning vehicles at two-way stop-controlled rural intersections

At two-way stop-controlled (TWSC) rural intersections, a right-turning driver who is departing the minor road may select an improper gap and subsequently may be involved in a rear-end collision with another vehicle approaching on the rightmost lane on the major road. This paper provides perceptual framework and algorithm design of a proposed infrastructure-based collision warning system that has the potential to aid unprotected right-turning drivers at TWSC rural intersections. The proposed system utilizes a radar sensor that measures the location, speed, and acceleration of the approaching vehicle on the major road. Based on these measurements, the system’s algorithm determines if there will be any potential conflict between the approaching and the turning vehicles and warns the driver of the latter vehicle if such a conflict is found. The algorithm is based on realistic acceleration profile of the turning vehicle to estimate its acceleration rates at different times so that the system can accurately estimate the time and distance needed for the departing vehicle to accelerate to the same speed as for the approaching vehicle. That realistic acceleration profile is established using actual experimental data collected by a Global Positioning System (GPS) data logger device that was used to record the positions and instantaneous speeds of different right-turning vehicles at 1-s intervals. The algorithm also gives consideration to the time needed by the driver of the departing vehicle to perceive the message displayed by the system and react to it (to start departure) where it was found that 95% of drivers have a perception–reaction time of 1.89 s or less. A methodology is also illustrated to select the maximum measurement errors suggested for the detectors in measuring the locations of the approaching vehicle on the major road where it was found that the accuracy of the system significantly deteriorates if the errors in measuring the distance and the azimuth angle exceed 0.1 m and 0.2°, respectively. An application example is provided to illustrate the algorithm used by the proposed system.     

A parametric study of the energy demands of car transportation: a case study of two competing commuter routes in the UK

This paper presents a parametric study of the energy demands of car transportation on two competing inter-city commuter routes in the UK for all main categories of automotive vehicles. The commuter routes are between Bristol and Bath: one is fast and flat, the other is relatively hilly and with tighter speed restrictions. Energy demands were found to be closely related to the vehicle mass because almost all external forces on the car are either directly or indirectly influenced by the mass of the vehicle. Exposure to the wind was found to be an important parameter that can significantly affect fuel consumption. Reducing vehicle mass is an important way of improving the performance of the car. However, there are limits to what can be achieved in weight reduction because of safety requirements and the desire of car owners to have many luxury items in modern cars. The official European fuel consumption and emissions test is limited in the extent to which it measures parameters that affect fuel consumption. For example, the test does not measure the frontal area or drag coefficient of the car. The design of the route and traffic operation can have a very significant influence on the efficiency of car transportation and therefore it is necessary to consider route design in whole-life analysis.     

Car availability change in England and Wales 1971–1981

The aggregate dynamics of car ownership have overshadowed the dynamics of car ownership and availability at the personal and household level. These dynamics have only recently been investigated in more depth. This paper contributes to this work by probing a special data source, theLongitudinal Study (LS) produced by the Office of Population Censuses and Surveys, for the changes in household car availability.The paper describes the LS and explains its special format, as a Census-based ~1% sample of the population of England and Wales.The analysis focuses on the car availability dynamics of a number of groups defined by changes in their life cycle position. Special attention is given to those households where the LS member remains a dependent child throughout the study period.The results show that all studied household types increase and decrease their car holdings, but that there are patterns in this process, which vary from group to group. In particular, the size of the previous car fleet has a different influence on the current fleet size from life cycle group to life cycle group.The paper argues in its conclusion to incorporate these differentials into the further work on car ownership and car ownership change.The work reported here was performed, while the author was a staff member of the Centre for Transport Studies, Imperial College, London.     

The asymmetric income effect on household vehicle ownership in Taiwan: A threshold cointegration approach

This paper uses the asymmetric threshold cointegration test to examine the asymmetric relationship between household income and vehicle ownership in Taiwan, presenting estimated asymmetric error correction models. The empirical data include information on household income, car ownership and motorcycle ownership in different regions from 1974 to 2009. The results show that, first, motorcycle ownership is asymmetrically cointegrated with household income in each region, and car ownership is asymmetrically cointegrated with household income in all regions except Taipei city. Second, both car and motorcycle ownership levels increase faster than they decrease in the asymmetric adjustment of their long-run relationship. Third, sensitivity tests for the period 1987-2009 show that the cointegration relationship of the car ownership equations vanished. Finally, we find evidence on the effects of household income on motorcycle ownership, and the effects of income variables on car and motorcycle ownership are dissimilar. This study exhibits different results across regions. These findings may be related to the development of public transit system in each region.