Safety features of stop signs at rail-highway grade crossings. Volume II. Technical report. Final report.

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

An evaluation of stop signs used with flashing traffic signals. Final report.

Turner-Fairbank Highway Research Center, McLean, Va.

Safety features of stop signs at rail-highway grade crossings. Volume I. Executive summary. Final report.

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

Retroreflective requirements for traffic signs - a STOP case study. Final report.

Mode of access: Internet.

Stop, yield, and no control at intersections. Final report.

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

Older drivers' crashes in Queensland, Australia

Background: The growing proportion of older adults in Australia is predicted to comprise 23% of the population by 2030. Accordingly, an increasing number of older drivers and fatal crashes of these drivers could also be expected. While the cognitive and physiological limitations of ageing and their road safety implications have been widely documented, research has generally considered older drivers as a homogeneous group. Knowledge of age-related crash trends within the older driver group itself is currently limited. Objective: The aim of this research was to identify age-related differences in serious road crashes of older drivers. This was achieved by comparing crash characteristics between older and younger drivers and between sub-groups of older drivers. Particular attention was paid to serious crashes (crashes resulting in hospitalisation and fatalities) as they place the greatest burden on the Australian health system. Method: Using Queensland Crash data, a total of 191,709 crashes of all-aged drivers (17–80+) over a 9-year period were analysed. Crash patterns of drivers’ aged 17–24, 25–39, 40–49, 50–59, 60–69, 70–79 and 80+ were compared in terms of crash severity (e.g., fatal), at fault levels, traffic control measures (e.g., stop signs) and road features (e.g., intersections). Crashes of older driver sub-groups (60–69, 70–79, 80+) were also compared to those of middle-aged drivers (40–49 and 50–59 combined, who were identified as the safest driving cohort) with respect to crash-related traffic control features and other factors (e.g., speed). Confounding factors including speed and crash nature (e.g., sideswipe) were controlled for. Results and discussion: Results indicated that patterns of serious crashes, as a function of crash severity, at-fault levels, road conditions and traffic control measures, differed significantly between age groups. As a group, older drivers (60+) represented the greatest proportion of crashes resulting in fatalities and hospitalisation, as well as those involving uncontrolled intersections and failure to give way. The opposite was found for middle-aged drivers, although they had the highest proportion of alcohol and speed-related crashes when compared to older drivers. Among all older drivers, those aged 60–69 were least likely to be involved in or the cause of crashes, but most likely to crash at interchanges and as a result of driving while fatigued or after consuming alcohol. Drivers aged 70–79 represented a mid-range level of crash involvement and culpability, and were most likely to crash at stop and give way signs. Drivers aged 80 years and beyond were most likely to be seriously injured or killed in, and at-fault for, crashes, and had the greatest number of crashes at both conventional and circular intersections. Overall, our findings highlight the heterogeneity of older drivers’ crash patterns and suggest that age-related differences must be considered in measures designed to improve older driver safety.

Effectiveness of motorist warning devices at rail-highway crossings. Final report.

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

Media futures: A review essay on'The Future of Reputation','TV Futures', and'The Future of the Internet and How to Stop It'

In his 1987 book, The Media Lab: Inventing the Future at MIT, Stewart Brand provides an insight into the visions of the future of the media in the 1970s and 1980s. 1 He notes that Nicolas Negroponte made a compelling case for the foundation of a media laboratory at MIT with diagrams detailing the convergence of three sectors of the media—the broadcast and motion picture industry; the print and publishing industry; and the computer industry. Stewart Brand commented: ‘If Negroponte was right and communications technologies really are converging, you would look for signs that technological homogenisation was dissolving old boundaries out of existence, and you would expect an explosion of new media where those boundaries used to be’. Two decades later, technology developers, media analysts and lawyers have become excited about the latest phase of media convergence. In 2006, the faddish Time Magazine heralded the arrival of various Web 2.0 social networking services: You can learn more about how Americans live just by looking at the backgrounds of YouTube videos—those rumpled bedrooms and toy‐strewn basement rec rooms—than you could from 1,000 hours of network television. And we didn’t just watch, we also worked. Like crazy. We made Facebook profiles and Second Life avatars and reviewed books at Amazon and recorded podcasts. We blogged about our candidates losing and wrote songs about getting dumped. We camcordered bombing runs and built open‐source software. America loves its solitary geniuses—its Einsteins, its Edisons, its Jobses—but those lonely dreamers may have to learn to play with others. Car companies are running open design contests. Reuters is carrying blog postings alongside its regular news feed. Microsoft is working overtime to fend off user‐created Linux. We’re looking at an explosion of productivity and innovation, and it’s just getting started, as millions of minds that would otherwise have drowned in obscurity get backhauled into the global intellectual economy. The magazine announced that Time’s Person of the Year was ‘You’, the everyman and everywoman consumer ‘for seizing the reins of the global media, for founding and framing the new digital democracy, for working for nothing and beating the pros at their own game’. This review essay considers three recent books, which have explored the legal dimensions of new media. In contrast to the unbridled exuberance of Time Magazine, this series of legal works displays an anxious trepidation about the legal ramifications associated with the rise of social networking services. In his tour de force, The Future of Reputation: Gossip, Rumor, and Privacy on the Internet, Daniel Solove considers the implications of social networking services, such as Facebook and YouTube, for the legal protection of reputation under privacy law and defamation law. Andrew Kenyon’s edited collection, TV Futures: Digital Television Policy in Australia, explores the intersection between media law and copyright law in the regulation of digital television and Internet videos. In The Future of the Internet and How to Stop It, Jonathan Zittrain explores the impact of ‘generative’ technologies and ‘tethered applications’—considering everything from the Apple Mac and the iPhone to the One Laptop per Child programme.

Unloading or not unloading? Sheep welfare implication of rest stop at control post after a 29h transport

In Europe, maximum journey time for transported sheep is set at 29. h (EC Regulation 1/2005), after which animals must be unloaded, fed and watered in control posts stopping for 24. h, as all other species, before continuing their journey. The industry considers these resting times too general, not taking into account the peculiar differences between species or age classes. Also, loading and unloading have been reported to be detrimental for the animals. Therefore, the industry pushes to reduce the times at control post and avoid unloading the animals from the truck. Since there is little information concerning the effect of resting in a stationary truck after long journeys, the present study aims to evaluate the effect of an 8. h rest stop on the truck for transported ewes compared to being unloaded for resting in a control post for the same amount of time, considering physiological and behavioural measures. Two groups of ewes were transported for 29. h, after which one was unloaded and housed in a pen (P) at the control post while the other was left inside the truck (T). After 8. h stop, a further 6. h travel was headed to the farm of origin. A third group (C) stayed at the farm as control. During the stop, standing, resting, moving and eating behaviour of all groups was recorded. Blood parameters, salivary and faecal cortisol were assessed at different stages. The behaviour of P animals during the resting period was more similar to C than to T ones, where feeding and lying behaviours were restricted by the limited space allowance on the truck. After returning to the farm of origin, both T and P animals showed different parameters' levels as compared to C. P ewes showed a mean loss weight of 2. kg not recorded in group T and showed higher signs of muscular damage compared to C group. It was concluded that, with so short resting times as 8. h, there is no clear advantages in terms of animal welfare for avoiding the unloading and loading of the animals in the control post after long journeys.

Visual driver support system for traffic signs

It has been well documented that traffic accidents that can be avoided occur when the motorists miss or ignore traffic signs. With the attention of drivers getting diverted due to distractions like cell phone conversations, missing traffic signs has become more prevalent. Also, poor weather and other unfriendly driving conditions sometimes makes the motorists not to be alert all the time and see every traffic sign on the road. Besides, most cars do not have any form of traffic assistance. Because of heavy traffic and proliferation of traffic signs on the roads, there is a need for a system that assists the driver not to miss a traffic sign to reduce the probability of an accident. Since visual information is critical for driving, processed video signals from cameras have been chosen to assist drivers. These inexpensive cameras can be easily mounted on the automobile. The objective of the present investigation and the traffic system development is to recognize the traffic signs electronically and alert drivers. For the case study and the system development, five important and critical traffic signs have been selected. They are: STOP, NO ENTER, NO RIGHT TURN, NO LEFT TURN, and YIELD. The system was evaluated processing still pictures taken from the public roads, and the recognition results were presented in an analysis table to indicate the correct identifications and the false ones. The system reached the acceptable recognition rate of 80% for all five traffic signs. The processing rate was about three seconds. The capabilities of MATLAB, VLSI design platforms and coding have been used to generate a visual warning to complement the visual driver support system with a Field Programmable Gate Array (FPGA) on a XUP Virtex-II Pro Development System.

L-R: Bob Kunst and Dr. Alan Rockway as part of the "Stop Anita Bryant Comm[ission] Leaders from Dade County, Florida

General note: Title and date provided by Bettye Lane.

Urban network travel time estimation from stop-line loop detector data and signal controller data

This paper presents a model to estimate travel time using cumulative plots. Three different cases considered are i) case-Det, for only detector data; ii) case-DetSig, for detector data and signal controller data and iii) case-DetSigSFR: for detector data, signal controller data and saturation flow rate. The performance of the model for different detection intervals is evaluated. It is observed that detection interval is not critical if signal timings are available. Comparable accuracy can be obtained from larger detection interval with signal timings or from shorter detection interval without signal timings. The performance for case-DetSig and for case-DetSigSFR is consistent with accuracy generally more than 95% whereas, case-Det is highly sensitive to the signal phases in the detection interval and its performance is uncertain if detection interval is integral multiple of signal cycles.