Safe speed limits for a safe system: The relationship between speed limit and fatal crash rate for different crash types

Objective: The objective of this article is to provide empirical evidence for safe speed limits that will meet the objectives of the Safe System by examining the relationship between speed limit and injury severity for different crash types, using police-reported crash data.

Method: Police-reported crashes from 2 Australian jurisdictions were used to calculate a fatal crash rate by speed limit and crash type. Example safe speed limits were defined using threshold risk levels.

Results: A positive exponential relationship between speed limit and fatality rate was found. For an example fatality rate threshold of 1 in 100 crashes it was found that safe speed limits are 40 km/h for pedestrian crashes; 50 km/h for head-on crashes; 60 km/h for hit fixed object crashes; 80 km/h for right angle, right turn, and left road/rollover crashes; and 110 km/h or more for rear-end crashes.

Conclusions: The positive exponential relationship between speed limit and fatal crash rate is consistent with prior research into speed and crash risk. The results indicate that speed zones of 100 km/h or more only meet the objectives of the Safe System, with regard to fatal crashes, where all crash types except rear-end crashes are exceedingly rare, such as on a high standard restricted access highway with a safe roadside design.     

Analytical mapping of research on disaster management,types and role of ICT during 2011–2018

Catastrophic disasters like earthquake and flood cause widespread destruction and financial devastation. This has brought disaster management into limelight making it a burgeoning academic research field. The remarkable rise of ICT (Information and Communication Technology) has instigated the scientific world to incorporate these technologies in disaster management. This study presents scientometric analysis to identify the status quo of research on the management of various disasters and role of ICT in it. This paper uses bibliographic data retrieved from Scopus for the observation period from 2011 to 2018. We provide extensive insights into growth of publications, citation pattern and their connectedness with other subject disciplines. Furthermore, we identify most productive and influential countries, institutes and journals. Our study analyses co-occurrence of keywords using Visualization of Similarities (VOS) Viewer. This structured overview will enhance the understanding of this field leading to more focussed and purposeful research.     

Transition zone in otoliths of orange roughy (Hoplostethus atlanticus) and its relationship to the onset of maturity

A transition zone in the otoliths of orange roughy (Hoplostethus atlanticus) is described where annulus width decreases markedly. For fish sampled at spawning time, the relationship between gonad stage and the presence or absence of a transition zone is consistent with the hypothesis that this zone marks the onset of maturity, if allowance is made for some error in gonad staging and identification of the zone. Another data set from a non-spawning area after the spawning season is not consistent with the hypothesis. However, these latter data are considered less reliable because of the small size of the fish in the sample and difficulties in determining, outside the spawning season, whether a fish has been reproductively active. This hypothesis was used to provide estimates of the median age (30 yr) and length (31 cm) at the onset of maturity for the Chatham Rise, New Zealand population. These estimates are unaffected by the biases associated with the usual ogive method of estimation. Received: 27 June 1997 / Accepted: 1 July 1997     

The Spatiotemporal Pattern of Fires in Northern Taiga Larch Forests of Central Siberia

The periodicity of fires in larch forests of Evenkia and their relationship with landscape elements have been studied. Cross-sections with “burns” in them caused by past fires have been analyzed in 72 test plots; the fire chronology encompassed the period from the 15th to the 20th century. The between-fire intervals (BFIs) have been calculated by two methods: (I) on the basis of burns alone and (II) on the basis of burns and the start of growth of the new generation of larch after the earliest fire. The BFI depends on local orographic features; it is 86 ± 11 (105 ± 12), 61 ± 8 (73 ± 8), 139 ± 17 (138 ± 18), and 68 ± 14 (70 ± 13) years for northeastern slopes, southwestern slopes, bogs, and flatlands, respectively. The mean BFIs calculated by methods I and II are 82 ± 7 and 95 ± 7 years, respectively. The permafrost horizon rises at a mean rate of 0.3 cm per year after a forest fire. It has been shown that the number of fires regularly peaks at periods of 36 and 82 years. There is also a temporal trend in fire frequency: the mean BFI was approximately 100 years in the 19th century and 65 years in the 20th century.     

Estimating waste transfer station delays using GPS

This paper examines the use of on-board global positioning system (GPS) data recorders as a method to collect field data on the movements of solid waste collection vehicles at transfer stations. The movements of five waste collection vehicles using four different transfer facilities were compared over a period of 1 year. The spatial data were analyzed using geofences to determine the amount of time each truck spent on each of four activities: queuing for access to the weigh scale, sitting on the weigh scale, queuing for access to the tipping floor, and unloading waste. The study found that queuing delays can be identified and measured using GPS data. The average time at a facility for all trucks was 16.4min per visit, with a standard deviation of 14.3min. Time at the facility ranged between 2 and 111min per visit and the distribution of time at the facility was positively skewed. Multi-compartment vehicles (co-collection and recycling trucks) spent significantly more time at unloading facilities. There were also significant differences in the length and the location of the queues at different facilities. At one facility, the longest delays were encountered while waiting for the weigh scale, at two facilities trucks experienced delays in obtaining access to the tipping floor, while at the fourth facility no significant delays developed.