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The aim of this paper is to introduce a new method to assess the safety impact of road treatment that influences long sections of road network, such as alternate road lighting, i.e. switching off every other road light at selected roads. The new method used Spatial Traffic Accident Analysis (STAA) – a network-based GIS hotspot analysis method – to identify and map day-time and night-time road traffic accident (RTA) risk levels before and after the implementation of alternate road lighting along a study road. Using the change after treatment in day-time RTA risk levels as a comparison group, and the change after treatment in night-time RTA risk levels as a treatment group, the difference between the treatment change and the comparison change in RTA risk levels was evaluated and mapped along the study road. The spatial distribution of this difference resulted in three different levels of the safety impact of the alternate light treatment at different locations along the study road: no impact, possible impact and highly possible impact. Night-time RTA after the alternate light treatment at road locations with the last two safety impact levels were identified, and their contributory factors were found most likely related to the reduction in night-time sight distance linked to alternate road lighting, and thus validates the safety impact results from the new method. [ABSTRACT FROM AUTHOR]

Road Traffic Accidents (RTA) are known to be one of the main causes of fatalities worldwide. One usef ul approach to improve road safety is through the identification of RT A hotspots along a road, so they can be prioritised and treated. This paper introduces an approach based on Geographical Information System (GI S) to identify and prioritise RTA hotspots along a road network using historical RTA data. One particular urban road in Brunei with a historically high rate of RT As, Jalan Gadong, was selected as a case study. Five years of historical RTA data were acquired from the relevant authorities and input into a GIS database. GI S analysis was then used to identify the spatial extension of the RT A hotspots. The RT A hotspots were ranked according to three different schemes: frequency, severity and socio-economic impact of RTAs. A composite ranking scheme was also developed to combine these schemes; this enabled the prioritisation and development of intervention and maintenance programmes of the identified RTA hotspots. A visualisation method of the RTA spatial distribution within each identified RTA hotspot was also developed to determine the most risky road stretches within each hotspot, which is important for treatment prioritisation when limited resources are available.

Roads constructed over poor ground conditions that carry high traffic volumes and axle loads may, over time, experience persisting occurrences of pavement distress. Road construction, be it a new or a rehabilitation project, is both costly and time-consuming. An appealing option that improves pavement durability, reduces construction cost and time, accelerates strength development over a short curing period, and decreases pavement thickness is to chemically stabilize local road materials. In contrast to other aggregate materials, there has been a gap in evaluating and quantifying the feasibility of chemical stabilization of sandstone aggregate that possesses marginal quality as a road construction material. Therefore, the aim of this paper is to provide an experimental investigation of relative strength development of sandstone aggregate subbase of marginal quality stabilized with combinations of Portland composite cement (PCC), ordinary Portland cement (OPC), and styrene–butadiene latex copolymer (or polymer). The samples were prepared with different gravel-to-sand (G:S) ratios of 2.1, 1.2, and 0.4 and subsequently stabilized with a polymer-cement (P/C) blend. Samples were compacted and cured under dry and wet conditions before measuring their unconfined compressive strength (UCS), indirect tensile strength (ITS), and California bearing ratio (CBR). At the same curing condition and P/C contents, it was found that the UCS and CBR of P/C-stabilized samples increased with increasing G:S ratios. At the same polymer and cement contents, the P/C-stabilized samples with the highest G:S ratio of 2.1 also demonstrated a significantly higher rate of UCS strength development compared with the samples with lower G:S ratio and unstabilized samples. Soil stabilization with a combination of 0.75% polymer and 5% cement contents yielded the highest UCS that was approximately seven times the UCS of unstabilized samples and an ITS of 0.73 MPa. Stabilization with a combination of 0.75% polymer and 3% cement contents yielded the highest CBR value that significantly exceeded 30% after only 4 days of soaking and was seven times that of unstabilized samples. This paper has thus demonstrated the potential improvement to the strength development of sandstone aggregate subbase stabilized with P/C blend under the optimal curing condition and the importance of identifying and using the optimal proportion of polymer and cement to achieve the target strength development and improvement. [ABSTRACT FROM AUTHOR]

Reducing road traffic accidents (RTA) and their socioeconomic costs is an increasingly important priority in many countries. In recent years, many authors have proposed various approaches to analyse historical RTA data using Geographic Information System (GIS) tools, so that locations with high instances or risk of RTA – i.e., RTA hotspots or blackspots – could be identified and ranked. This could then enable limited road engineering resources to be prioritised for remediating more critical RTA hotspots and therefore reducing RTA rates. This paper presents the development of a new validation method to evaluate the application of four different hotspot analysis methods in ESRI ArcGIS 10.2 to identify and rank RTA hotspots using historical RTA data on a section of a road in Brunei Darussalam as a case study. A road safety audit was undertaken for six locations along the study road section to identify the risk levels at these locations. These risk levels were then compared with risk levels at the same six locations computed by four hotspot analysis methods: Network KDE by SANET, KDE+, Getis-Ord Gi*, and a recently proposed risk-based method – STAA – that accounts for RTA frequency, severity and socioeconomic costs. It was found that SANET-KDE overestimated the risk levels of road sections that are free of RTA. The results from KDE + showed the most deviations compared to the identified risk levels by the road safety audit. Getis-Ord Gi* was not able to identify RTA hotspots along the study road section of Jalan Tutong. However, the STAA method provided the most consistent results in comparison with the identified risk levels by the road safety audit. STAA, by having a better validity compared to other methods, provides a promising way to prioritise RTA hotspots for remediation, and thus reducing the associated socioeconomic costs. In addition, these findings demonstrated that the novel method of validation via risk levels determined by road safety audit was able to provide an independent measure of the validity of the hotspot analysis (HSA) methods. [ABSTRACT FROM AUTHOR]