Interaction between fixed and vehicular illumination systems. Phase II. Interim report.

Federal Highway Administration, Office of Research, Washington, D.C.

Sensitivity analysis of vehicle design attributes that affect vehicle response in critical accident situations - part 1: user's manual. Final report.

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

DPMAS utilization vehicle parameter identification. Technical report. Final report.

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

Sensitivity analysis of vehicle design attributes that affect vehicle response in critical accident situations - part II: technical report. Final report.

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

Highway-vehicle-object simulation model - 1976. Volume 2: programmers manual. Final report.

Federal Highway Administration, Washington, D.C.

Highway-vehicle-object simulation model - 1976. Volume 3: engineering manual - analysis. Final report.

Federal Highway Administration, Washington, D.C.

Highway-vehicle-object simulation model - 1976. Volume 4: engineering manual - validation. Final report.

Federal Highway Administration, Washington, D.C.

Studies of freight train engineer performance. Final report.

Federal Railroad Administration, Office of Research and Development, Washington, D.C.

Diagnostic motor vehicle inspection demonstration projects, program engineering support. Volume 8 - appendix G: vehicle-in-use standards. Final report.

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

Highway-vehicle-object simulation model - 1976. Volume 1: users manual. Final report.

Federal Highway Administration, Washington, D.C.

Performance audit of the Department of Central Management Services' operation of the state vehicle fleet /

"House Resolution 658 directed the Office of the Auditor General (OAG) to audit the Department of Central Management Services' (CMS) operation of the fleet of passenger cars used by State executive agencies. The Resolution called for the audit to address the total number of cars; number of take-home cars; necessity of take-home vehicles; costs of vehicles in Fiscal Year 2009; and the adequacy of CMS' system to record their use and maintenance and to check for official use, including whether it is possible to implement a system to track vehicles for business only."

Studying the effect of market orientation and organisational culture on a brand’s performance

It is now well accepted that effective implementation of market orientation leads to superior performance. This paper theorises that market orientation and an innovative culture enable organisations to achieve higher brand performance. To test this proposition data were gathered from a sample of firms across a range of industries. The results support the premise that market orientation and innovative cultures improve brand performance and that innovative culture influences market orientation. The results also indicate that innovative culture is the stronger driver of brand performance over market orientation.

Determinants of driver vs. second row occupant posture modelling

Digital human modeling (DHM), as a convenient and cost-effective tool, is increasingly incorporated into product and workplace design. In product design, it is predominantly used for the development of driver-vehicle systems. Most digital human modeling software tools, such as JACK, RAMSIS and DELMIA HUMANBUILDER provide functions to predict posture and positions for drivers with selected anthropometry according to SAE (Society of Automotive Engineers) Recommended Practices and other ergonomics guidelines. However, few studies have presented 2nd row passenger postural information, and digital human modeling of these passenger postures cannot be performed directly using the existing driver posture prediction functions. In this paper, the significant studies related to occupant posture and modeling were reviewed and a framework of determinants of driver vs. 2nd row occupant posture modeling was extracted. The determinants which are regarded as input factors for posture modeling include target population anthropometry, vehicle package geometry and seat design variables as well as task definitions. The differences between determinants of driver and 2nd row occupant posture models are significant, as driver posture modeling is primarily based on the position of the foot on the accelerator pedal (accelerator actuation point AAP, accelerator heel point AHP) and the hands on the steering wheel (steering wheel centre point A-Point). The objectives of this paper are aimed to investigate those differences between driver and passenger posture, and to supplement the existing parametric model for occupant posture prediction. With the guide of the framework, the associated input parameters of occupant digital human models of both driver and second row occupant will be identified. Beyond the existing occupant posture models, for example a driver posture model could be modified to predict second row occupant posture, by adjusting the associated input parameters introduced in this paper. This study combines results from a literature review and the theoretical modeling stage of a second row passenger posture prediction model project.

Bayesian hierarchical analysis on crash prediction models

Traditional crash prediction models, such as generalized linear regression models, are incapable of taking into account the multilevel data structure, which extensively exists in crash data. Disregarding the possible within-group correlations can lead to the production of models giving unreliable and biased estimates of unknowns. This study innovatively proposes a -level hierarchy, viz. (Geographic region level – Traffic site level – Traffic crash level – Driver-vehicle unit level – Vehicle-occupant level) Time level, to establish a general form of multilevel data structure in traffic safety analysis. To properly model the potential cross-group heterogeneity due to the multilevel data structure, a framework of Bayesian hierarchical models that explicitly specify multilevel structure and correctly yield parameter estimates is introduced and recommended. The proposed method is illustrated in an individual-severity analysis of intersection crashes using the Singapore crash records. This study proved the importance of accounting for the within-group correlations and demonstrated the flexibilities and effectiveness of the Bayesian hierarchical method in modeling multilevel structure of traffic crash data.

A comparison of road traffic crashes along mountainous and non-mountainous roads in Sabah, Malaysia

Constrained topography and complex road geometry along rural mountainous roads often represent a demanding driving situation. As a result, traffic crashes along mountainous roads are likely to have different characteristics to crashes on roads in flatter areas; however, there is little research on this topic. The objective of this study is to examine the characteristics of road traffic crashes on rural mountainous roads and to compare these with the characteristics of crashes on non-mountainous roads. This paper explores and compares general crash characteristics including crash type, crash severity, roadway geometric features and environmental factors, and road user/vehicle characteristics. Five years of road traffic crash data (2008-2012) for Sabah were obtained from the Malaysian Institute of Road Safety Research. During this period, a total of 25,439 crashes occurred along federal roads in Sabah, of which 4,875 crashes occurred in mountainous areas. Categorical data analysis techniques were used to examine the differences between mountainous and non-mountainous crashes. Results show that the odds ratio of ‘out-of-control’ crashes and the crash involvement due to speeding are respectively about 4.2 times and 2.8 times higher on mountainous than non-mountainous roads. Other factors and crash characteristics that increase the odds of crashes along mountainous roads compared with non-mountainous roads include horizontal curved sections compared with straight sections, single-vehicle crashes compared with multi-vehicle crashes and weekend crashes compared with weekday crashes. This paper identifies some of the basic characteristics of crashes along rural mountainous roads to aid future research on traffic safety along mountainous roads.