Experimental design for evaluating the safety benefits of railroad advance warning signs. Final report.

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

Feasibility of an automatic truck warning system. Final report.

Federal Highway Administration, Office of Safety and Traffic Operations Research and Development, McLean, Va.

Improvement of the effectiveness of motorist warnings at railroad highway grade crossings. Final report.

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

Emergency Medical Services - highway sign evaluation. Final report.

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

Tabulation showing locations of subways and highway bridges with posted loads and limited vertical and horizontal clearances on marked U.S., interstate and Illinois state routes /

Cover title: Vertical and horizontal clearances of structures.

Tavern anecdotes, and reminiscences of the origin of signs, coffee-houses, &c. : intended as a lounge-book for citizens and their country cousins /

Issued in yellow printed boards; vignette on back cover.

Modelling data and voice traffic over IP networks using continuous-time Markov models

Common approaches to IP-traffic modelling have featured the use of stochastic models, based on the Markov property, which can be classified into black box and white box models based on the approach used for modelling traffic. White box models, are simple to understand, transparent and have a physical meaning attributed to each of the associated parameters. To exploit this key advantage, this thesis explores the use of simple classic continuous-time Markov models based on a white box approach, to model, not only the network traffic statistics but also the source behaviour with respect to the network and application. The thesis is divided into two parts: The first part focuses on the use of simple Markov and Semi-Markov traffic models, starting from the simplest two-state model moving upwards to n-state models with Poisson and non-Poisson statistics. The thesis then introduces the convenient to use, mathematically derived, Gaussian Markov models which are used to model the measured network IP traffic statistics. As one of the most significant contributions, the thesis establishes the significance of the second-order density statistics as it reveals that, in contrast to first-order density, they carry much more unique information on traffic sources and behaviour. The thesis then exploits the use of Gaussian Markov models to model these unique features and finally shows how the use of simple classic Markov models coupled with use of second-order density statistics provides an excellent tool for capturing maximum traffic detail, which in itself is the essence of good traffic modelling. The second part of the thesis, studies the ON-OFF characteristics of VoIP traffic with reference to accurate measurements of the ON and OFF periods, made from a large multi-lingual database of over 100 hours worth of VoIP call recordings. The impact of the language, prosodic structure and speech rate of the speaker on the statistics of the ON-OFF periods is analysed and relevant conclusions are presented. Finally, an ON-OFF VoIP source model with log-normal transitions is contributed as an ideal candidate to model VoIP traffic and the results of this model are compared with those of previously published work.

Fluctuation-induced traffic congestion in heterogeneous networks

In studies of complex heterogeneous networks, particularly of the Internet, significant attention was paid to analyzing network failures caused by hardware faults or overload, where the network reaction was modeled as rerouting of traffic away from failed or congested elements. Here we model another type of the network reaction to congestion - a sharp reduction of the input traffic rate through congested routes which occurs on much shorter time scales. We consider the onset of congestion in the Internet where local mismatch between demand and capacity results in traffic losses and show that it can be described as a phase transition characterized by strong non-Gaussian loss fluctuations at a mesoscopic time scale. The fluctuations, caused by noise in input traffic, are exacerbated by the heterogeneous nature of the network manifested in a scale-free load distribution. They result in the network strongly overreacting to the first signs of congestion by significantly reducing input traffic along the communication paths where congestion is utterly negligible. © Copyright EPLA, 2012.

WLAN / WMAN Integration Architecture and Traffic Control for Voice Transmission

The popular technologies Wi-Fi and WiMAX for realization of WLAN and WMAN respectively are much different, but they could compliment each other providing competitive wireless access for voice traffic. The article develops the idea of WLAN/WMAN (Wi-Fi/WiMAX) integration. WiMAX is offering a backup for the traffic overflowing from Wi-Fi cells located into the WiMAX cell. Overflow process is improved by proposed rearrangement control algorithm applied to the Wi-Fi voice calls. There are also proposed analytical models for system throughput evaluation and verification of the effectiveness using WMAN as a backup for WLAN overflow traffic and the proposed call rearrangement algorithm as well.

South Carolina Traffic Collision Report Form (TR- 310) and Supplement Truck and Bus Report Form Instruction Manual

The instructions in this manual have been prepared to provide guidance for completing the South Carolina Traffic Collision Report Form TR-310 and the Supplemental Bus and Truck Collision Report Form. It lists traffic laws and definitions and gives examples of traffic collision report forms.

Screening for drugs in oral fluid : illicit drug use and drug driving in a sample of urban and regional Queensland motorists

Police services in a number of Australian states and overseas jurisdictions have begun to implement or consider random road-side drug testing of drivers. This paper outlines research conducted to provide an estimate of the extent of drug driving in a sample of Queensland drivers in regional, rural and metropolitan areas. Oral fluid samples were collected from 2657 Queensland motorists and screened for illicit substances including cannabis (delta 9 tetrahydrocannibinol [THC]), amphetamines, ecstasy, and cocaine. Overall, 3.8% of the sample (n = 101) screened positive for at least one illicit substance, although multiple drugs were identified in a sample of 23 respondents. The most common drugs detected in oral fluid were ecstasy (n = 53), and cannabis (n = 46) followed by amphetamines (n = 23). A key finding was that cannabis was confirmed as the most common self-reported drug combined with driving and that individuals who tested positive to any drug through oral fluid analysis were also more likely to report the highest frequency of drug driving. Furthermore, a comparison between drug vs. drink driving detection rates for one region of the study, revealed a higher detection rate for drug driving (3.8%) vs. drink driving (0.8%). This research provides evidence that drug driving is relatively prevalent on Queensland roads, and may in fact be more common than drink driving. This paper will further outline the study findings’ and present possible directions for future drug driving research.

Report : development of a methodology for assessing variation in maintenance and rehabilitation costs

In the previous research CRC CI 2001-010-C “Investment Decision Framework for Infrastructure Asset Management”, a method for assessing variation in cost estimates for road maintenance and rehabilitation was developed. The variability of pavement strength collected from a 92km national highway was used in the analysis to demonstrate the concept. Further analysis was conducted to identify critical input parameters that significantly affect the prediction of road deterioration. In addition to pavement strength, rut depth, annual traffic loading and initial roughness were found to be critical input parameters for road deterioration. This report presents a method developed to incorporate other critical parameters in the analysis, such as unit costs, which are suspected to contribute to a certain degree to cost estimate variation. Thus, the variability of unit costs will be incorporated in this analysis. Bruce Highway located in the tropical east coast of Queensland has been identified to be the network for the analysis. This report presents a step by step methodology for assessing variation in road maintenance and rehabilitation cost estimates.

Development of a particle number and particle mass vehicle emissions inventory for an urban fleet

Motor vehicles are major emitters of gaseous and particulate pollution in urban areas, and exposure to particulate pollution can have serious health effects, ranging from respiratory and cardiovascular disease to mortality. Motor vehicle tailpipe particle emissions span a broad size range from 0.003-10µm, and are measured as different subsets of particle mass concentrations or particle number count. However, no comprehensive inventories currently exist in the international published literature covering this wide size range. This paper presents the first published comprehensive inventory of motor vehicle tailpipe particle emissions covering the full size range of particles emitted. The inventory was developed for urban South-East Queensland by combining two techniques from distinctly different disciplines, from aerosol science and transport modelling. A comprehensive set of particle emission factors were combined with traffic modelling, and tailpipe particle emissions were quantified for particle number (ultrafine particles), PM1, PM2.5 and PM10 for light and heavy duty vehicles and buses. A second aim of the paper involved using the data derived in this inventory for scenario analyses, to model the particle emission implications of different proportions of passengers travelling in light duty vehicles and buses in the study region, and to derive an estimate of fleet particle emissions in 2026. It was found that heavy duty vehicles (HDVs) in the study region were major emitters of particulate matter pollution, and although they contributed only around 6% of total regional vehicle kilometres travelled, they contributed more than 50% of the region’s particle number (ultrafine particles) and PM1 emissions. With the freight task in the region predicted to double over the next 20 years, this suggests that HDVs need to be a major focus of mitigation efforts. HDVs dominated particle number (ultrafine particles) and PM1 emissions; and LDV PM2.5 and PM10 emissions. Buses contributed approximately 1-2% of regional particle emissions.

Learning to drive with cognitive impairment : the experience of young ADHD diagnosed drivers and their parent supervisors

A subset of novice drivers exhibit executive function impairments which may adversely impact on the learn-to-drive period and subsequent driving experience, potentially explaining their overrepresentation in traffic offences and crashes. This paper presents the results of a qualitative analysis of a small series of in-depth semi-structured interviews undertaken individually with affected young drivers (n = 7) and each of their parent supervisors (n = 6). Young drivers were selected on the basis of their ADHD diagnosis, as a sample particularly affected by executive function impairments. Standardised rating scale measures confirmed the currency of the young drivers’ ADHD symptoms and executive function impairment. Results are discussed in terms of common experiences of the young affected drivers and those of their parents as supervising drivers of the learn-to-drive process and subsequent driving behaviour. Key themes included difficulties that were related to core executive function impairments symptomatic of ADHD. Themes also included common emotions that the young drivers associated with driving, with particular types of impact on their driving behaviour. Common strategies that were used by both the young driver and their parent during this learning process and their perceived effectiveness are also discussed. Those that were perceived to be most effective tended to focus on reducing the cognitive load for the young driver when introducing new information and skills.

How do other people influence your driving speed? Exploring the 'who' and the 'how' of social influences on speeding from a qualitative perspective

Using only legal sanctions to manage the speed at which people drive ignores the potential benefits of harnessing social factors such as the influence of others. Social influences on driver speeds were explored in this qualitative examination of 67 Australian drivers. Focus group interviews with 8 driver types (young, mid-age and older males and females, and self-identified Excessive and Rare speeders) were guided by Akers’ social learning theory (Akers, 1998). Findings revealed two types of influential others: people known to the driver (passengers and parents), and unknown other drivers. Passengers were generally described as having a slowing influence on drivers: responsibility for the safety of people in the car and consideration for passenger comfort were key themes. In contrast, all but the Rare speeders reported increasing their speed when driving alone. Parental role modelling was also described. In relation to other drivers, key themes included speeding to keep up with traffic flow and perceived pressure to drive faster. This ‘pressure’ from others to ‘speed up’ was expressed in all groups and reported strategies for managing this varied. Encouragingly, examples of actual or anticipated social rewards for speeding were less common than examples of social punishments. Three main themes relating to social punishments were embarrassment, breaching the trust of others, and presenting an image of a responsible driver. Impression management and self-presentation are discussed in light of these findings. Overall, our findings indicate scope to exploit the use of social sanctions for speeding and social praise for speed limit compliance to enhance speed management strategies.