A data mining driven crash risk profiling method for road asset management

This thesis takes a new data mining approach for analyzing road/crash data by developing models for the whole road network and generating a crash risk profile. Roads with an elevated crash risk due to road surface friction deficit are identified. The regression tree model, predicting road segment crash rate, is applied in a novel deployment coined regression tree extrapolation that produces a skid resistance/crash rate curve. Using extrapolation allows the method to be applied across the network and cope with the high proportion of missing road surface friction values. This risk profiling method can be applied in other domains.

A data mining driven risk profiling method for road asset management

Road surface skid resistance has been shown to have a strong relationship to road crash risk, however, applying the current method of using investigatory levels to identify crash prone roads is problematic as they may fail in identifying risky roads outside of the norm. The proposed method analyses a complex and formerly impenetrable volume of data from roads and crashes using data mining. This method rapidly identifies roads with elevated crash-rate, potentially due to skid resistance deficit, for investigation. A hypothetical skid resistance/crash risk curve is developed for each road segment, driven by the model deployed in a novel regression tree extrapolation method. The method potentially solves the problem of missing skid resistance values which occurs during network-wide crash analysis, and allows risk assessment of the major proportion of roads without skid resistance values.

Mathematical relationships for metal build-up on urban road surfaces based on traffic and land use characteristics

The study investigated the influence of traffic and land use parameters on metal build-up on urban road surfaces. Mathematical relationships were developed to predict metals originating from fuel combustion and vehicle wear. The analysis undertaken found that nickel and chromium originate from exhaust emissions, lead, copper and zinc from vehicle wear, cadmium from both exhaust and wear and manganese from geogenic sources. Land use does not demonstrate a clear pattern in relation to the metal build-up process, though its inherent characteristics such as traffic activities exert influence. The equation derived for fuel related metal load has high cross-validated coefficient of determination (Q2) and low Standard Error of Cross-Validation (SECV) values indicates that the model is reliable, while the equation derived for wear-related metal load has low Q2 and high SECV values suggesting its use only in preliminary investigations. Relative Prediction Error values for both equations are considered to be well within the error limits for a complex system such as an urban road surface. These equations will be beneficial for developing reliable stormwater treatment strategies in urban areas which specifically focus on mitigation of metal pollution.

Characteristics of road factors in multi and single vehicle motorcycle crashes in Queensland

Motorcyclists were involved in 6.4% of all police-reported crashes and 12.5% of all fatal crashes in Queensland during 2004-2011. Of these crashes, 43% were single-vehicle (SV) and 57% were multi-vehicle (MV). The overall reduction in motorcycle crashes in this period masked different trends: single-vehicle crashes increased while MV motorcycle crashes decreased. However, little research has been undertaken to understand the similarities and differences between SV and MV motorcycle crashes in Queensland and the factors underlying these diverging trends. The descriptive analyses and regression model developed here confirm international research findings regarding the greater role of road infrastructure factors in SV crashes. In particular, road geometric factors such as horizontal and vertical alignment and road surface factors such as sealed/unsealed and wet/dry were more important in SV than MV crashes.

Road Dust from Pavement Wear and Traction Sanding

Vehicles affect the concentrations of ambient airborne particles through exhaust emissions, but particles are also formed in the mechanical processes in the tire-road interface, brakes, and engine. Particles deposited on or in the vicinity of the road may be re-entrained, or resuspended, into air through vehicle-induced turbulence and shearing stress of the tires. A commonly used term for these particles is road dust . The processes affecting road dust emissions are complex and currently not well known. Road dust has been acknowledged as a dominant source of PM10 especially during spring in the sub-arctic urban areas, e.g. in Scandinavia, Finland, North America and Japan. The high proportion of road dust in sub-arctic regions of the world has been linked to the snowy winter conditions that make it necessary to use traction control methods. Traction control methods include dispersion of traction sand, melting of ice with brine solutions, and equipping the tires with either metal studs (studded winter tires), snow chains, or special tire design (friction tires). Several of these methods enhance the formation of mineral particles from pavement wear and/or from traction sand that accumulate in the road environment during winter. When snow and ice melt and surfaces dry out, traffic-induced turbulence makes some of the particles airborne. A general aim of this study was to study processes and factors underlying and affecting the formation and emissions of road dust from paved road surfaces. Special emphasis was placed on studying particle formation and sources during tire road interaction, especially when different applications of traction control, namely traction sanding and/or winter tires were in use. Respirable particles with aerodynamic diameter below 10 micrometers (PM10) have been the main concern, but other size ranges and particle size distributions were also studied. The following specific research questions were addressed: i) How do traction sanding and physical properties of the traction sand aggregate affect formation of road dust? ii) How do studded tires affect the formation of road dust when compared with friction tires? iii) What are the composition and sources of airborne road dust in a road simulator and during a springtime road dust episode in Finland? iv) What is the size distribution of abrasion particles from tire-road interaction? The studies were conducted both in a road simulator and in field conditions. The test results from the road simulator showed that traction sanding increased road dust emissions, and that the effect became more dominant with increasing sand load. A high percentage of fine-grained anti-skid aggregate of overall grading increased the PM10 concentrations. Anti-skid aggregate with poor resistance to fragmentation resulted in higher PM levels compared with the other aggregates, and the effect became more significant with higher aggregate loads. Glaciofluvial aggregates tended to cause higher particle concentrations than crushed rocks with good fragmentation resistance. Comparison of tire types showed that studded tires result in higher formation of PM emissions compared with friction tires. The same trend between the tires was present in the tests with and without anti-skid aggregate. This finding applies to test conditions of the road simulator with negligible resuspension. Source and composition analysis showed that the particles in the road simulator were mainly minerals and originated from both traction sand and pavement aggregates. A clear contribution of particles from anti-skid aggregate to ambient PM and dust deposition was also observed in urban conditions. The road simulator results showed that the interaction between tires, anti-skid aggregate and road surface is important in dust production and the relative contributions of these sources depend on their properties. Traction sand grains are fragmented into smaller particles under the tires, but they also wear the pavement aggregate. Therefore particles from both aggregates are observed. The mass size distribution of traction sand and pavement wear particles was mainly coarse, but fine and submicron particles were also present.

Taxonomy of factors which influence heavy metal build-up on urban road surfaces

Heavy metals build-up on urban road surfaces is a complex process and influenced by a diverse range of factors. Although numerous research studies have been conducted in the area of heavy metals build-up, limited research has been undertaken to rank these factors in terms of their influence on the build-up process. This results in limitations in the identification of the most critical factor/s for accurately estimating heavy metal loads and for designing effective stormwater treatment measures. The research study undertook an in-depth analysis of the factors which influence heavy metals build-up based on data generated from a number of different geographical locations around the world. Traffic volume was found to be the highest ranked factor in terms of influencing heavy metals build-up while land use was ranked the second. Proximity to arterial roads, antecedent dry days and road surface roughness has a relatively lower ranking. Furthermore, the study outcomes advances the conceptual understanding of heavy metals build-up based on the finding that with increasing traffic volume, total heavy metal build-up load increases while the variability decreases. The outcomes from this research study are expected to contribute to more accurate estimation of heavy metals build-up loads leading to more effective stormwater treatment design.

THEORETICAL ROAD DAMAGE DUE TO DYNAMIC TYRE FORCES OF HEAVY VEHICLES. PART 2: SIMULATED DAMAGE CAUSED BY A TANDEM-AXLE VEHICLE.

The literature relating to road surface failure and design is briefly reviewed and the conventional methods for assessing the road damaging effects of dynamic tire forces are examined. A new time domain technique for analyzing dynamic tire forces and four associated road damage criteria are presented. The force criteria are used to examine the road damaging characteristics of a simple tandem-axle vehicle model for a range of speed and road roughness conditions. It is concluded that for the proposed criteria, the theoretical service life of road surfaces that are prone to fatigue failure may be reduced significantly by the dynamic component of wheel forces. The damage done to approximately five per cent of the road surface area during the passage of a theoretical model vehicle at typical highway speeds may be increased by as much as four times.

Characterisation and simulation of asphalt road surfaces

Accurate simulation of rolling-tyre vibrations, and the associated noise, requires knowledge of road-surface topology. Full scans of the surface types in common use are, however, not widely available, and are likely to remain so. Ways of producing simulated surfaces from incomplete starting information are thus needed. In this paper, a simulation methodology based solely on line measurements is developed, and validated against a full two-dimensional height map of a real asphalt surface. First the tribological characteristics-asperity height, curvature and nearest-neighbour distributions-of the real surface are analysed. It is then shown that a standard simulation technique, which matches the (isotropic) spectrum and the probability distribution of the height measurements, is unable to reproduce these characteristics satisfactorily. A modification, whereby the inherent granularity of the surface is enforced at the initialisation stage, is introduced, and found to produce simulations whose tribological characteristics are in excellent agreement with the measurements. This method will thus make high-fidelity tyre-vibration calculations feasible for researchers with access to line-scan data only. In addition, the approach to surface tribological characterisation set out here provides a template for efficient cataloguing of road textures, as long as the resulting information can subsequently be used to produce sample realisations. A third simulation algorithm, which successfully addresses this requirement, is therefore also presented. © 2011 Elsevier B.V.

An integrated model of rolling tyre vibrations on a smooth road

We describe new results on the vibrations of rolling tyres, aimed at noise prediction for tyres of given design on a smooth road surface. This new approach incorporates our existing models, of smooth road-tyre interaction and belt vibration but includes additional features that are required for real tyre patterns. To this end, the model allows variable tread block size and grooves along the belt circumference; the density and angle of these grooves may also vary laterally. The key innovation is to treat the tyre belt as a laterally stacked series of rings, each of which is equipped with a set of viscoelastic springs around its circumference. It is shown how to use this construction to mimic the details of actual tyre patterns and, in conjunction with existing models, predict belt vibrations. The construction is applied to develop a ring discretisation for a real tyre that shows strong lateral variations. It is shown that the vibration amplitude is concentrated on a set of parallel lines in frequency-wavenumber space and that the tread pattern dictates the occurrence and spacing of these lines. Linkage to a boundary element calculation then allows quantification of the influence of tread parameters on radiated noise. Keywords: Vibration, tread pattern, tyre noise. Copyright © (2011) by the Institute of Noise Control Engineering.

Dynamic Axle Force and Road Profile Identification Using a Moving Vehicle

In the interaction between vehicles, pavements and bridges, it is essential to aim towards a reduction of vehicle axle forces to promote longer pavement life spans and to prevent bridges loads becoming too high. Moreover, as the road surface roughness affects the vehicle dynamic forces, an efficient monitoring of pavement condition is also necessary to achieve this aim. This paper uses a novel algorithm to identify the dynamic interaction forces and pavement roughness from vehicle accelerations in both theoretical simulations and a laboratory experiment; moving force identification theory is applied to a vehicle model for this purpose. Theoretical simulations are employed to evaluate the ability of the algorithm to predict forces over a range of bridge spans and to evaluate the influence of road roughness level on the accuracy of the results. Finally, in addressing the challenge for the real-world problem, the effects of vehicle configuration and speed on the predicted road roughness are also investigated in a laboratory experiment.

Dynamic axle force and road profile identification using a moving vehicle

The axle forces applied by a vehicle through its wheels are a critical part of the interaction between vehicles, pavements and bridges. Therefore, the minimisation of these forces is important in order to promote long pavement life spans and ensure that bridge loads are small. Moreover, as the road surface roughness affects the vehicle dynamic forces, the monitoring of pavements for highways and bridges is an important task. This paper presents a novel algorithm to identify these dynamic interaction forces which involves direct instrumentation of a vehicle with accelerometers. The ability of this approach to predict the pavement roughness is also presented. Moving force identification theory is applied to a vehicle model in theoretical simulations in order to obtain the interaction forces and pavement roughness from the measured accelerations. The method is tested for a range of bridge spans in simulations and the influence of road roughness level on the accuracy of the results is investigated. Finally, the challenge for the real-world problem is addressed in a laboratory experiment.

Statistical classification of road pavements using near field vehicle rolling noise measurements

Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

Processos de avaliação dos pavimentos rodoviários: Caso de estudo: reforço do pavimento em dois trechos do sublanço Enxara/Torres Vedras Sul

Relatório de Estágio Curricular para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Vias de Comunicação e Transportes

Impacts de l'écoulement souterrain sur la dégradation du pergélisol

Les changements climatiques mesurés dans le Nord-ouest canadien au cours du XXIe siècle entraînent une dégradation du pergélisol. Certaines des principales conséquences physiques sont la fonte de la glace interstitielle lors du dégel du pergélisol, l’affaissement du sol et la réorganisation des réseaux de drainage. L’effet est particulièrement marqué pour les routes bâties sur le pergélisol, où des dépressions et des fentes se créent de façon récurrente, rendant la conduite dangereuse. Des observations et mesures de terrain effectuées à Beaver Creek (Yukon) entre 2008 et 2011 ont démontré qu’un autre processus très peu étudié et quantifié dégradait le pergélisol de façon rapide, soit la chaleur transmise au pergélisol par l’écoulement souterrain. Suite aux mesures de terrain effectuées (relevé topographique, étude géotechnique du sol, détermination de la hauteur de la nappe phréatique et des chenaux d’écoulement préférentiels, température de l’eau et du sol, profondeur du pergélisol et de la couche active), des modèles de transfert de chaleur par conduction et par advection ont été produits. Les résultats démontrent que l’écoulement souterrain dans la couche active et les zones de talik contribue à la détérioration du pergélisol via différents processus de transfert de chaleur conducto-convectifs. L’écoulement souterrain devrait être pris en considération dans tous les modèles et scénarios de dégradation du pergélisol. Avec une bonne caractérisation de l’environnement, le modèle de transfert de chaleur élaboré au cours de la présente recherche est applicable dans d’autres zones de pergélisol discontinu.

Ungulate behavioral responses to the heterogeneous road-network of a touristic protected area in Africa

Understanding how wildlife responds to road and traffic is essential for effective conservation. Yet, not many studies have evaluated how roads influence wildlife in protected areas, particularly within the large iconic African National Parks where tourism is mainly based on sightings from motorized vehicles with the consequent development and intense use of roads. To reduce this knowledge gap, we studied the behavioral response and local spatial distribution of impala Aepyceros melampus along the heterogeneous (with variation in road surface type and traffic intensity) road-network of Kruger National Park (KNP, South Africa). We surveyed different types of roads (paved and unpaved) recording the occurrence of flight responses among sighted impala and describing their local spatial distribution (in relation to the roads). We observed relatively few flight responses (19.5% of 118 observations), suggesting impalas could be partly habituated to vehicles in KNP. In addition, impala local distribution is apparently unaffected by unpaved roads, yet animals seem to avoid the close proximity of paved roads. Overall, our results suggest a negative, albeit small, effect of traffic intensity, and of presence of pavement on roads on the behavior of impala at KNP. Future studies would be necessary to understand how roads influence other species, but our results show that even within a protected area that has been well-visited for a long time, wildlife can still be affected by roads and traffic. This result has ecological (e.g., changes in spatial distribution of fauna) and management implications (e.g., challenges of facilitating wildlife sightings while minimizing disturbance) for protected areas where touristic activities are largely based on driving.