984 resultados para ROAD UTILITY VEHICLE


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Preformed structural reinforcements have shown good performance in crash tests, where the great advantage is their weight. These reinforcements are designed with the aim of increasing the rigidity of regions with large deformations, thus stabilising sections of the vehicle that work as load path during impact. The objective of this work is to show the application of structural reinforcements made of polymeric material PA66 in the field of vehicle safety, through finite element simulations. Simulations of frontal impact at 50 km/h and in ODB (offset deformable barrier) at 57 km/h configurations (standards such as ECE R-94 and ECE R-12) were performed in the software LS-DYNA R (R) and MADYMO (R). The simulations showed that the use of polymeric reinforcements leads to a 70% reduction in A-pillar intrusion, a 65% reduction in the displacement of the steering column and a 59% reduction in the deformation in the region of the occupant legs and feet. The level of occupant injuries was analysed by MADYMO (R) software, and a reduction of 23.5% in the chest compression and 80% in the tibia compression were verified. According to the standard, such conditions lead to an improvement in the occupant safety in a vehicle collision event.

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In this study, a method for vehicle tracking through video analysis based on Markov chain Monte Carlo (MCMC) particle filtering with metropolis sampling is proposed. The method handles multiple targets with low computational requirements and is, therefore, ideally suited for advanced-driver assistance systems that involve real-time operation. The method exploits the removed perspective domain given by inverse perspective mapping (IPM) to define a fast and efficient likelihood model. Additionally, the method encompasses an interaction model using Markov Random Fields (MRF) that allows treatment of dependencies between the motions of targets. The proposed method is tested in highway sequences and compared to state-of-the-art methods for vehicle tracking, i.e., independent target tracking with Kalman filtering (KF) and joint tracking with particle filtering. The results showed fewer tracking failures using the proposed method.

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Crashes at rail level crossings represent a significant problem, both in Australia and worldwide. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles, now provide researchers with the opportunity to further understand driver behaviour at rail level crossings in ways not previously possible. This paper gives an overview of a recent on-road pilot study of driver behaviour at rail level crossings in which 25 participants drove a pre-determined route, incorporating 4 rail level crossings, using MUARC's instrumented On-Road Test Vehicle (ORTeV). Drivers provided verbal commentary whilst driving the route, and a range of other data were collected, including eye fixations, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. Extracts from the wider analyses are used to examine in depth driver behaviour at one of the rail level crossings encountered during the study. The analysis presented, along with the overall analysis undertaken, gives insight into the driver and wider systems factors that shape behaviour at rail level crossings, and highlights the utility of using a multi-method, instrumented vehicle approach for gathering data regarding driver behaviour in different contexts.

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Human error, its causes and consequences, and the ways in which it can be prevented, remain of great interest to road safety practitioners. This paper presents the findings derived from an on-road study of driver errors in which 25 participants drove a pre-determined route using MUARC's On-Road Test Vehicle (ORTeV). In-vehicle observers recorded the different errors made, and a range of other data was collected, including driver verbal protocols, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. The drivers tested made a range of different errors, with speeding violations, both intentional and unintentional, being the most common. Further more detailed analysis of a sub-set of specific error types indicates that driver errors have various causes, including failures in the wider road 'system' such as poor roadway design, infrastructure failures and unclear road rules. In closing, a range of potential error prevention strategies, including intelligent speed adaptation and road infrastructure design, are discussed.

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Improving safety at rail level crossings is an important part of both road and rail safety strategies. While low in number, crashes between vehicles and trains at level crossings are catastrophic events typically involving multiple fatalities and serious injuries. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles with eye and head tracking, provide researchers with the opportunity to further understand driver behaviour at such crossings in ways not previously possible. This paper describes a study conducted to further understand the factors that shape driver behaviour at rail level crossings using instrumented vehicles. Twenty-two participants drove an On-Road Test Vehicle (ORTeV) on a predefined route in regional Victoria with a mix of both active (flashing lights with/without boom barriers) and passively controlled (stop, give way) crossings. Data collected included driving performance data, head checks, and interview data to capture driver strategies. The data from an integrated suite of methods demonstrated clearly how behaviour differs at active and passive level crossings, particularly for inexperienced drivers. For example, the head check data clearly show the reliance and expectancies of inexperienced drivers for active warnings even when approaching passively controlled crossings. These studies provide very novel and unique insights into how level crossing design and warnings shape driver behaviour.

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In recent decades, highly motorised countries, such as Australia, have witnessed significant improvements in population health through reductions in fatalities and injuries from road traffic crashes. In Australia, concerted efforts have been made to reduce the road trauma burden since road fatalities reached their highest level in in the early 1970s. Since that time, many improvements have been made drawing on various disciplines to reduce the trauma burden (e.g., road and vehicle design, road user education, traffic law enforcement practices and enforcement technologies). While road fatalities have declined significantly since the mid-1970s, road trauma remains a serious public health concern in Australia. China has recently become the largest car market in the world (Ma, Li, Zhou, Duan, & Bishai, 2012). This rapid motorisation has been accompanied by substantial expansion of the road network as well as a large road trauma burden. Road traffic injuries are a major cause of death in China, reported as accounting for one third of all injury-deaths between 2002 and 2006 (Ma et al., 2012). In common with Australia, China has experienced a reported decline in fatalities since 2002 (see Hu, Wen & Baker, 2008). However, there remains a strong need for action in this area as rates of motorisation continue to climb in China. In Australia, a wide range of organisations have contributed to the improvements in road safety including government agencies, professional organisations, advocacy groups and research centres. In particular, Australia has several highly regarded and multi-disciplinary, university-based research centres that work across a range of road safety fields, including engineering, intelligent transportation systems, the psychology of road user behaviour, and traffic law enforcement. Besides conducting high-quality research, these centres fulfil an important advocacy role in promoting safer road use and facilitating collaborations with government and other agencies, at both the national and international level. To illustrate the role of these centres, an overview will be provided of the Centre for Accident Research and Road Safety-Queensland (CARRS-Q), which was established in 1996 and has gone on to become a recognised world-leader in road safety and injury prevention research. The Centre’s research findings are used to provide evidence-based recommendations to government and have directly contributed to promoting safer road use in Australia. Since 2006, CARRS-Q has also developed strong collaborative links with various universities and organisations in China to assist in building understanding, connections and capacity to assist in reducing the road trauma burden. References Hu, G., Wen, M., Baker, T. D., & Baker, S. P. (2008). Road-traffic deaths in China, 1985–2005: threat and opportunity. Injury Prevention, 14, 149-153. Ma, S., Li, Q., Zhou, M., Duan, L., & Bishai, D. (2012). Road Traffic Injury in China: A Review of National Data Sources. Traffic Injury Prevention, 13(S1), 57-63.

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Constrained topography and complex road geometry along rural mountainous roads often represent a demanding driving situation. As a result, traffic crashes along mountainous roads are likely to have different characteristics to crashes on roads in flatter areas; however, there is little research on this topic. The objective of this study is to examine the characteristics of road traffic crashes on rural mountainous roads and to compare these with the characteristics of crashes on non-mountainous roads. This paper explores and compares general crash characteristics including crash type, crash severity, roadway geometric features and environmental factors, and road user/vehicle characteristics. Five years of road traffic crash data (2008-2012) for Sabah were obtained from the Malaysian Institute of Road Safety Research. During this period, a total of 25,439 crashes occurred along federal roads in Sabah, of which 4,875 crashes occurred in mountainous areas. Categorical data analysis techniques were used to examine the differences between mountainous and non-mountainous crashes. Results show that the odds ratio of ‘out-of-control’ crashes and the crash involvement due to speeding are respectively about 4.2 times and 2.8 times higher on mountainous than non-mountainous roads. Other factors and crash characteristics that increase the odds of crashes along mountainous roads compared with non-mountainous roads include horizontal curved sections compared with straight sections, single-vehicle crashes compared with multi-vehicle crashes and weekend crashes compared with weekday crashes. This paper identifies some of the basic characteristics of crashes along rural mountainous roads to aid future research on traffic safety along mountainous roads.

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Constrained topography and complex road geometry along rural mountainous roads often represent a demanding driving situation. As a result, traffic crashes along mountainous roads are likely to have different characteristics to crashes on roads in flatter areas; however, there is little research on this topic. The objective of this study is to examine the characteristics of road traffic crashes on rural mountainous roads and to compare these with the characteristics of crashes on non-mountainous roads. This paper explores and compares general crash characteristics including crash type, crash severity, roadway geometric features and environmental factors, and road user/vehicle characteristics. Five years of road traffic crash data (2008-2012) for Sabah were obtained from the Malaysian Institute of Road Safety Research. During this period, a total of 25,439 crashes occurred along federal roads in Sabah, of which 4,875 crashes occurred in mountainous areas. Categorical data analysis techniques were used to examine the differences between mountainous and non-mountainous crashes. Results show that the odds ratio of ‘out-of-control’ crashes and the crash involvement due to speeding are respectively about 4.2 times and 2.8 times higher on mountainous than non-mountainous roads. Other factors and crash characteristics that increase the odds of crashes along mountainous roads compared with non-mountainous roads include horizontal curved sections compared with straight sections, single-vehicle crashes compared with multi-vehicle crashes and weekend crashes compared with weekday crashes. This paper identifies some of the basic characteristics of crashes along rural mountainous roads to aid future research on traffic safety along mountainous roads.

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This paper describes a series of tests conducted on a UK trunk road, in which the dynamic tyre forces generated by over 1500 heavy goods vehicles (HGVs) were measured using a load measuring mat containing 144 capacitive strip sensors. The data was used to investigate the relative road damaging potential of the various classes of vehicles, and the degree of spatial repeatability of tyre forces present in a typical highway fleet. Approximately half the vehicles tested were found to contribute to a spatially repeatable pattern of pavement loading. On average, air suspended vehicles were found to generate lower dynamic load coefficients than steel suspended vehicles. However, air suspended vehicles also generated higher mean levels of theoretical road damage (aggregate force) than steel suspended vehicles, indicating that the ranking of suspensions depends on the pavement damage criterion used.