Crash tests of single post sign installations using subcompact automobiles. Interim report.

Federal Highway Administration, Implementation Division, Washington, D.C.

An analysis of the automobile market: modeling of the long-run determinants of the demand for automobiles. Volume II: simulation analysis using the Wharton E.F.A. Automobile Demand Model. Final report.

Transportation Department, Washington, D.C.

Side impact crashworthiness of full-size hardtop automobiles. Final report. Phase I.

National Highway Traffic Safety Administration, Washington, D.C.

An analysis of the automobile market: modeling of the long-run determinants of the demand for automobiles. Volume I: the Wharton E.F.A. Automobile Demand Model. Final report.

Transportation Department, Washington, D.C.

Selective survey of the capability of representative automobile repair facilities to diagnose and repair automobiles. Final report.

Transportation Department, Office of the Secretary of Transportation, Washington, D.C.

Cyclopedia of mechanical engineering : a general reference work on machine shop practice, tool making, forging, pattern making, foundry, work, metallurgy, steam boilers and engines, gas producers, gas engines, automobiles, elevators, refrigeration, sheet metal work, mechanical drawing, machine design, etc;

Mode of access: Internet.

Crash tests of single post sign installations using subcompact automobiles /

Mode of access: Internet.

U.S. industrial competitiveness : a comparison of steel, electronics, and automobiles.

Mode of access: Internet.

Report upon cost of roads required for heavy motor vehicles compared with cost of roads adequate for passenger automobiles and light trucks, made to the Associated Railroads of Pennsylvania.

Cover title.

Horseless vehicles, automobiles, motor cycles operated by steam, hydro-carbon, electric and pneumatic motors; a practical treatise for ... everyone interested in the development, use and care of the automobile, including a special chapter on how to build an electric cab, with detail drawings.

Mode of access: Internet.

A study in the reduction of efficiency of nitrogen oxide removal catalysts for automobiles

Automotive catalysts are the most effective short-term answer to air pollution from automobiles. Since strict control of exhaust emissions is, or will be,covered by legislation in most developed countries in the world, catalytic devices will be increasingly fitted to cars. There is consequently an urgent need for the development of catalysts that will not compete for scarce precious metal resources. A number of problems have already been identified in connection with base metal catalysts but quantitative investigations are lacking. The base metal reduction catalysts developed by Imperial Chemical Industries Limited, catalysts and Chemical Group, in collaboration with the Air Pollution Control Laboratory, B L Cars Limited for automotive emission control, are susceptible to de-activation by three major mechanisms. These are: physical loss of the wash-coat (a high surface area coating which supports the active species), aggregation of the active species and poisoning by fuel and engine oil additives. This thesis is especially concerned with the first two of these and attempts to indicate the relative magnitude .of their effect on the activity of. the catalysts. Aggregation of the active species or sintering, as it is loosely called, was studied by using impregnated granules to overcome effects due to the loss of the wash-coat. Samples were aged in a synthetic exhaust gas, free from poisons, and metal crystallite sizes were measured by scanning-electron microscopy. The increase in particle size was correlated with the loss in catalytic activity. In order to maintain a link with the real conditions of service a number of monolithic catalysts were tested in an engine-dynamometer and several previously tested endurance catalysts were examined. A mechanism is proposed for the break-up and subsequent 10s.5 of the wash-coat and suggestions for improved resistance to loss of the' coating and active species are proposed.

An assessment system for evaluation of driving competencies

Automobiles have deeply impacted the way in which we travel but they have also contributed to many deaths and injury due to crashes. A number of reasons for these crashes have been pointed out by researchers. Inexperience has been identified as a contributing factor to road crashes. Driver’s driving abilities also play a vital role in judging the road environment and reacting in-time to avoid any possible collision. Therefore driver’s perceptual and motor skills remain the key factors impacting on road safety. Our failure to understand what is really important for learners, in terms of competent driving, is one of the many challenges for building better training programs. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. A multidisciplinary approach is necessary to explain how driving abilities evolves with on-road driving experience. To our knowledge, driver assistance systems have never been comprehensively used in a driver training context to assess the safety aspect of driving. The aim and novelty of this thesis is to develop and evaluate an Intelligent Driver Training System (IDTS) as an automated assessment tool that will help drivers and their trainers to comprehensively view complex driving manoeuvres and potentially provide effective feedback by post processing the data recorded during driving. This system is designed to help driver trainers to accurately evaluate driver performance and has the potential to provide valuable feedback to the drivers. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the driving tasks. Therefore, the proposed IDTS utilizes fuzzy set theory for the assessment of driver performance. The proposed research program focuses on integrating the multi-sensory information acquired from the vehicle, driver and environment to assess driving competencies. After information acquisition, the current research focuses on automated segmentation of the selected manoeuvres from the driving scenario. This leads to the creation of a model that determines a “competency” criterion through the driving performance protocol used by driver trainers (i.e. expert knowledge) to assess drivers. This is achieved by comprehensively evaluating and assessing the data stream acquired from multiple in-vehicle sensors using fuzzy rules and classifying the driving manoeuvres (i.e. overtake, lane change, T-crossing and turn) between low and high competency. The fuzzy rules use parameters such as following distance, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvres to assess competency. These rules that identify driving competency were initially designed with the help of expert’s knowledge (i.e. driver trainers). In-order to fine tune these rules and the parameters that define these rules, a driving experiment was conducted to identify the empirical differences between novice and experienced drivers. The results from the driving experiment indicated that significant differences existed between novice and experienced driver, in terms of their gaze pattern and duration, speed, stop time at the T-crossing, lane keeping and the time spent in lanes while performing the selected manoeuvres. These differences were used to refine the fuzzy membership functions and rules that govern the assessments of the driving tasks. Next, this research focused on providing an integrated visual assessment interface to both driver trainers and their trainees. By providing a rich set of interactive graphical interfaces, displaying information about the driving tasks, Intelligent Driver Training System (IDTS) visualisation module has the potential to give empirical feedback to its users. Lastly, the validation of the IDTS system’s assessment was conducted by comparing IDTS objective assessments, for the driving experiment, with the subjective assessments of the driver trainers for particular manoeuvres. Results show that not only IDTS was able to match the subjective assessments made by driver trainers during the driving experiment but also identified some additional driving manoeuvres performed in low competency that were not identified by the driver trainers due to increased mental workload of trainers when assessing multiple variables that constitute driving. The validation of IDTS emphasized the need for an automated assessment tool that can segment the manoeuvres from the driving scenario, further investigate the variables within that manoeuvre to determine the manoeuvre’s competency and provide integrated visualisation regarding the manoeuvre to its users (i.e. trainers and trainees). Through analysis and validation it was shown that IDTS is a useful assistance tool for driver trainers to empirically assess and potentially provide feedback regarding the manoeuvres undertaken by the drivers.

Evaluating effects of eco-driving at traffic intersections based on traffic micro-simulation

Eco-driving is an initiative driving behavior which aims to reduce fuel consumption and emissions from automobiles. Recently, it has attracted increasing interests and has been adopted by many drivers in Australia. Although many of the studies have revealed considerable benefits in terms of fuel consumption and emissions after utilising eco-driving, most of the literature investigated eco-driving effects on individual driver but not traffic flow. The driving behavior of eco-drivers will potentially affect other drivers and thereby affects the entire traffic flow. To comprehensively assess and understand how effectively eco-driving can perform, therefore, measurement on traffic flow is necessary. In this paper, we proposed and demonstrated an evaluation method based on a microscopic traffic simulator (Aimsun). We focus on one particular eco-driving style which involves moderate and smooth acceleration. We evaluated both traffic performance (travel time) and environmental performance (fuel consumption and CO2 emission) at traffic intersection level in a simple simulation model. The before-and-after comparisons indicated potentially negative impacts when using eco-driving, which highlighted the necessity to carefully evaluate and improve eco-driving before wide promotion and implementation.

To bound or not to bound: preliminary Theory of Time Bounds Specification in strategic alliances

This article augments Resource Dependence Theory with Real Options reasoning in order to explain time bounds specification in strategic alliances. Whereas prior work has found about a 50/50 split between alliances that are time bound and those that are open-ended, their substantive differences and antecedents are ill understood. To address this, we suggest that the two alliance modes present different real options trade-offs in adaptation to environmental uncertainty: ceteris paribus, time-bound alliances are likely to provide abandonment options over open-ended alliances, but require additional investments to extend the alliance when this turns out to be desirable after formation. Open-ended alliances are likely to provide growth options over open-ended alliances, but they demand additional effort to abandon the alliance if post-formation circumstances so desire. Therefore, we expect time bounds specification to be a function of environmental uncertainty: organizations in more uncertain environments will be relatively more likely to place time bounds on their strategic alliances. Longitudinal archival and survey data collected amongst 39 industry clusters provides empirical support for our claims, which contribute to the recent renaissance of resource dependence theory by specifying the conditions under which organizations choose different time windows in strategic partnering.