Accelerated Service Life Testing of Automotive Vehicles on a Test Course

The accelerated service life testing of automotive vehicles for durability to road roughness induced dynamic loads is often accomplished in the laboratory using road roughness simulation facilities [1-5]. However, such tests can also be accomplished by a carefully designed field operation on a test course [6], where both the speed of the vehicle and the roughness of die test course become variables that control the degree of the test acceleration. Field tests are generally harder to control than laboratory tests, but offer a greater degree of realism since the vehicle is fully operational during the test exactly as it will be in service. This paper formulates the criteria for accelerated service life tests on a test course, evaluates the assumptions that must be enforced to obtain valid results, and explores the sensitivity of the results to the critical test parameters, namely, the vehicle speed and the road roughness severity of the test course relative to the service environment.     

Relationship between proximity to transit and ridership for journey-to-work trips in Chicago

The use of privately owned vehicles (POVs) contributes significantly to US energy consumption (EC) and greenhouse gas emissions (GHGe). Strategies for reducing POV use include shifting trips to other modes, particularly public transit. Choices to use transit are based on characteristics of travelers, their trips, and the quality of competing transportation services. Here we focus on the proximity of rail stations to trip origins/destinations as a factor affecting mode choice for work trips. Using household travel survey data from Chicago, we evaluate the profile of journey-to-work (JTW) trips, assessing mode share and potential for more travelers to use rail. For work trips having the origin/destination as close as 1 mile from rail transit stations, POVs were still the dominant travel mode, capturing as much as 61%, followed by rail use at 14%. This high degree of POV use coupled with the proportion of JTW trips within close proximity to rail stations indicated that at least some of these trips may be candidates for shifting from POV to rail. For example, shifting all work trips with both the origin/destination within 1 mile of commuter rail stations would potentially reduce the energy associated with all work-related POV driving trips by a maximum of 24%. Based on the analysis of trips having the origin and destination closest to train stations, a complete shift in mode from POV to train could exceed CO₂ reduction goals targeted in the Chicago Climate Action Plan. This could occur with current settlement patterns and the use of existing infrastructure. However, changes in traveler behavior and possibly rail operation would be necessary, making policy to motivate this change essential.     

Economies of scale in bus transit: A review of concepts and evidence

The issue of returns of scale in bus transit continues to be a subject of debate among transportation analysts. From a public policy perspective, returns to scale are relevant to many policy areas such as transit service pricing, cost allocation, productivity and organization of the industry. Empirical studies conducted during the past decade have generated conflicting results. Constant, decreasing and increasing returns to scale have all been reported.This paper identifies the sources of these conflicting results: confusion regarding the concept of scale economies, variable definition, assumptions regarding the shape of the cost function, and certain characteristics of the data base. The paper also discusses the theoretical concept of scale economies, and an interpretation of the concept for bus transit is presented. It is concluded that recent studies which have utilized generalized cost functions more accurately represent the economic structure of bus transit, and provide a stronger basis for transit policy analysis.     

Empirical analysis of transportation investment and economic development at state, county and municipality levels

Numerous studies have found positive correlation between transportation infrastructure investment and economic development. Basically these studies use a conventional production function model augmented by a public capital input, mainly highways, rail and other transportation facilities. While the range of the measured economic growth effects varies widely among studies, the positive elasticity between transportation investment and economic development is now commonly accepted. Still a major puzzling issue is that the magnitude of the measured effect seems to decline significantly as the econometric model is further refined, mainly with regard to space and time lags. That is, the use of national or state data produces elasticity results, which are much larger than when using county or municipality data. Similarly, when we introduce into the econometric model a lag between the times when the transportation investments are made and when the economic benefits transpire, the measured elasticities decline with the size of the lag. Thus, the main objective of this paper is to investigate these issues analytically and empirically and provide a plausible explanation. We do so by using alternative econometric models, applying them to a database, which is composed of longitudinal state, county and municipality observations from 1990 to 2000. The key result is that transportation investments produce strong spillover effects relative to space and time. Unless these factors are properly accounted for many reported empirical results are likely to be overly biased, with important policy implications.     

Journey to work and job search characteristics of the urban poor

Gender differences in work trip and job search patterns have received several analytical attention in recent years. A consistent finding in the literature is that women work closer to home than men because of their lower income, greater household responsibilities, and heavier reliance on public transit. While these findings pervade the literature, there has been little analysis into the extent to which they hold in the exclusive case of the urban poor. Can poor women afford to choose between jobs on the basis of journey to work considerations, any more than poor men? Using a survey data from Edmonton, this study examines the gender differences in commuting and job search patterns of the urban poor. The findings suggest that, even among the low income population, women have shorter work trips and greater preference for part-time jobs than men because of their child care and household responsibilities. More women than men did not have enough time for their job search activities; and fewer women than men were prepared to accept job offers in all parts of the study area due to their household responsibilities. The results suggest that while males' employment problems are tied primarily to the working of the labour market, through inadequate skills and lack of good-paying jobs, females' employment problems are more explicable in terms of their role as mothers and homemakers.     

Integrating geographic information systems into transit ridership forecast models

Researchers have produced sophisticated modal split and transit demand models, including forecasts that are sensitive to the level of service. However, little effort has been made to integrate these models into corridor studies and route alignment analyses since (a) re-routing is itself an extremely complex modeling task, and (b) the results of the demand models are presented in tabular form with no facility to visualize spatial patterns and relationships that, if recognized, would aid in the routing tasks. GIS tools can be used, together with the demand models, to identify both clusters of city blocks that house families with certain socioeconomic characteristics and potential trip destinations conducive to transit use. In other words, GIS tools can be used to better measure some of the factors that are needed by transit demand models. The results of these models can be displayed graphically, enabling analysts to target places needing improved service, evaluate route re-alignment alternatives, and operate more efficient and effective bus lines. This paper examines how a particular class of model used by transit agencies for estimating ridership can be integrated with GIS tools in order to facilitate such analyses. It also explores the effects of visualization of routes, demographics, and employment data on the process of designing route alignments with better targeting of high transit ridership areas. This paper is part of a research project sponsored by the Region One University Transportation Center, at MIT.     

The applicability of non-cooperative game theory in transport analysis

Various models that incorporate concepts from Non-Cooperative Game Theory (NCGT) are described in the transport literature. Game Theory provides powerful tools for analysing transport systems, but these tools have some drawbacks that should be recognised. In the current paper we review games that describe transport problems and discuss them within a uniform context. Although the paper does not introduce new tools, it presents insights concerning the relations between transport models and games. We divide existing games into groups and show that some common features characterise multiple games. We distinguish between games that make a conceptual contribution and games that are suitable for application. Compact or symmetric game structures make remarkable observations but often do not support actual decision-making. Less aesthetic formats, most of which are Stackelberg games between authorities and travellers, are stronger as instruments that assist in determining real-life policies; these formulations can be treated by practitioners as mathematical programs with equilibrium constraints and not as games. Yaron Hollander is currently conducting economic research of bus reliability at the Institute for Transport Studies at the University of Leeds. He previously worked for the Technion—Israel Institute of Technology; for the Israel Institute for Transportation Planning and Research; and for the public transport department at Ayalon Highways Co. Joseph N. Prashker is a professor at the Faculty of Civil and Environmental Engineering at the Technion—Israel Institute of Technology. Till recently he served as head of the Transportation Research Institute at the Technion. His interests are behavioural demand models, network analysis, and Game Theory applications in transportation.     

核废料的处理 分离嬗变可以缩短核废料的毒性期

核能在全欧洲能源供应方面居功甚伟。在欧盟25个成员国中，13个国家共有148座核反应堆，产生的总电力达到125GWh，每年可生产电力850TWh，占欧盟总电力需求的35%.     

Feedback brake distribution control for minimum pitch

The distribution of brake forces between front and rear axles of a vehicle is typically specified such that the same level of brake force coefficient is imposed at both front and rear wheels. This condition is known as ‘ideal’ distribution and it is required to deliver the maximum vehicle deceleration and minimum braking distance. For subcritical braking conditions, the deceleration demand may be delivered by different distributions between front and rear braking forces. In this research we show how to obtain the optimal distribution which minimises the pitch angle of a vehicle and hence enhances driver subjective feel during braking. A vehicle model including suspension geometry features is adopted. The problem of the minimum pitch brake distribution for a varying deceleration level demand is solved by means of a model predictive control (MPC) technique. To address the problem of the undesirable pitch rebound caused by a full-stop of the vehicle, a second controller is designed and implemented independently from the braking distribution in use. An extended Kalman filter is designed for state estimation and implemented in a high fidelity environment together with the MPC strategy. The proposed solution is compared with the reference ‘ideal’ distribution as well as another previous feed-forward solution.     

Wheel slip control with torque blending using linear and nonlinear model predictive control

Modern hybrid electric vehicles employ electric braking to recuperate energy during deceleration. However, currently anti-lock braking system (ABS) functionality is delivered solely by friction brakes. Hence regenerative braking is typically deactivated at a low deceleration threshold in case high slip develops at the wheels and ABS activation is required. If blending of friction and electric braking can be achieved during ABS events, there would be no need to impose conservative thresholds for deactivation of regenerative braking and the recuperation capacity of the vehicle would increase significantly. In addition, electric actuators are typically significantly faster responding and would deliver better control of wheel slip than friction brakes. In this work we present a control strategy for ABS on a fully electric vehicle with each wheel independently driven by an electric machine and friction brake independently applied at each wheel. In particular we develop linear and nonlinear model predictive control strategies for optimal performance and enforcement of critical control and state constraints. The capability for real-time implementation of these controllers is assessed and their performance is validated in high fidelity simulation.