982 resultados para road vehicles


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KEEP CLEAR pavement markings are widely used at urban signalised intersections to indicate to drivers to avoid entering blocked intersections. For example, ‘Box junctions’ are most widely used in the United Kingdom and other European countries. However, in Australia, KEEP CLEAR markings are mostly used to improve access from side roads onto a main road, especially when the side road is very close to a signalised intersection. This paper aims to reveal how the KEEP CLEAR markings affect the dynamic performance of the queuing vehicles on the main road, where the side road access is near a signalised intersection. Raw traffic field data was collected from an intersection at the Gold Coast, Australia, and the Kanade–Lucas–Tomasi (KLT) feature tracker approach was used to extract dynamic vehicle data from the raw video footage. The data analysis reveals that the KEEP CLEAR markings generate positive effects on the queuing vehicles in discharge on the main road. This finding refutes the traditional viewpoint that the KEEP CLEAR pavement markings will cause delay for the queuing vehicles’ departure due to the enlarged queue spacing. Further studies are suggested in this paper as well.

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In Victoria, as in other jurisdictions, there is very little research on the potential risks and benefits of lane filtering by motorcyclists, particularly from a road safety perspective. This on-road proof of concept study aimed to investigate whether and how lane filtering influences motorcycle rider situation awareness at intersections and to address factors that need to be considered for the design of a larger study in this area. Situation awareness refers to road users’ understanding of ‘what is going on’ around them and is a critical commodity for safe performance. Twenty-five experienced motorcyclists rode their own instrumented motorcycle around an urban test route in Melbourne whilst providing verbal protocols. Lane filtering occurred in 27% of 43 possible instances in which there were one or more vehicles in the traffic queue and the traffic lights were red on approach to the intersection. A network analysis procedure, based on the verbal protocols provided by motorcyclists, was used to identify differences in motorcyclist situation awareness between filtering and non-filtering events. Although similarities in situation awareness across filtering and nonfiltering motorcyclists were found, the analysis revealed some differences. For example, filtering motorcyclists placed more emphasis on the timing of the traffic light sequence and on their own actions when moving to the front of the traffic queue, whilst non-filtering motorcyclists paid greater attention to traffic moving through the intersection and approaching from behind. Based on the results of this study, the paper discusses some methodological and theoretical issues to be addressed in a larger study comparing situation awareness between filtering and non-filtering motorcyclists.

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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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Recent road safety statistics show that the decades-long fatalities decreasing trend is stopping and stagnating. Statistics further show that crashes are mostly driven by human error, compared to other factors such as environmental conditions and mechanical defects. Within human error, the dominant error source is perceptive errors, which represent about 50% of the total. The next two sources are interpretation and evaluation, which accounts together with perception for more than 75% of human error related crashes. Those statistics show that allowing drivers to perceive and understand their environment better, or supplement them when they are clearly at fault, is a solution to a good assessment of road risk, and, as a consequence, further decreasing fatalities. To answer this problem, currently deployed driving assistance systems combine more and more information from diverse sources (sensors) to enhance the driver's perception of their environment. However, because of inherent limitations in range and field of view, these systems' perception of their environment remains largely limited to a small interest zone around a single vehicle. Such limitations can be overcomed by increasing the interest zone through a cooperative process. Cooperative Systems (CS), a specific subset of Intelligent Transportation Systems (ITS), aim at compensating for local systems' limitations by associating embedded information technology and intervehicular communication technology (IVC). With CS, information sources are not limited to a single vehicle anymore. From this distribution arises the concept of extended or augmented perception. Augmented perception allows extending an actor's perceptive horizon beyond its "natural" limits not only by fusing information from multiple in-vehicle sensors but also information obtained from remote sensors. The end result of an augmented perception and data fusion chain is known as an augmented map. It is a repository where any relevant information about objects in the environment, and the environment itself, can be stored in a layered architecture. This thesis aims at demonstrating that augmented perception has better performance than noncooperative approaches, and that it can be used to successfully identify road risk. We found it was necessary to evaluate the performance of augmented perception, in order to obtain a better knowledge on their limitations. Indeed, while many promising results have already been obtained, the feasibility of building an augmented map from exchanged local perception information and, then, using this information beneficially for road users, has not been thoroughly assessed yet. The limitations of augmented perception, and underlying technologies, have not be thoroughly assessed yet. Most notably, many questions remain unanswered as to the IVC performance and their ability to deliver appropriate quality of service to support life-saving critical systems. This is especially true as the road environment is a complex, highly variable setting where many sources of imperfections and errors exist, not only limited to IVC. We provide at first a discussion on these limitations and a performance model built to incorporate them, created from empirical data collected on test tracks. Our results are more pessimistic than existing literature, suggesting IVC limitations have been underestimated. Then, we develop a new CS-applications simulation architecture. This architecture is used to obtain new results on the safety benefits of a cooperative safety application (EEBL), and then to support further study on augmented perception. At first, we confirm earlier results in terms of crashes numbers decrease, but raise doubts on benefits in terms of crashes' severity. In the next step, we implement an augmented perception architecture tasked with creating an augmented map. Our approach is aimed at providing a generalist architecture that can use many different types of sensors to create the map, and which is not limited to any specific application. The data association problem is tackled with an MHT approach based on the Belief Theory. Then, augmented and single-vehicle perceptions are compared in a reference driving scenario for risk assessment,taking into account the IVC limitations obtained earlier; we show their impact on the augmented map's performance. Our results show that augmented perception performs better than non-cooperative approaches, allowing to almost tripling the advance warning time before a crash. IVC limitations appear to have no significant effect on the previous performance, although this might be valid only for our specific scenario. Eventually, we propose a new approach using augmented perception to identify road risk through a surrogate: near-miss events. A CS-based approach is designed and validated to detect near-miss events, and then compared to a non-cooperative approach based on vehicles equiped with local sensors only. The cooperative approach shows a significant improvement in the number of events that can be detected, especially at the higher rates of system's deployment.

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The Safe System approach to road safety utilises a holistic view of the interactions among vehicles, roads and road users. Yet, the contribution of each of these factors to crashes is vastly different. The role of road users is widely acknowledged as an overwhelming contributor to road crashes. Substantial gains have been made with improvements to vehicle and roads over a number of years. However, improvements of the road user’s behaviour has been (in some cases) less substantial. A road user behaviour that is relatively unregulated is driver sleepiness, which is part of the ‘fatal five’ of risky road user behaviours. The effect of sleepiness is ubiquitous – sleepiness is a state that most, if not all drivers on our roads has experienced, and is habitually exposed to. The quality and quantity of daily sleep is integral to our level of neurobehavioural performance during wakefulness and as such can have a compounding effect on a number of other risky driving behaviours. This paper will discuss the potential influence of sleepiness as an interceding factor for a number of risky driving behaviours. Little effort has been given to increasing awareness of the deleterious and wide ranging effects that sleepiness has on road safety. Given the wide ranging influence of sleepiness, improvements of ‘sleep health’ as a protective factor at the community or individual level could lead to significant reductions in road trauma and increases of general well being. A discussion of potential actions to reduce sleepiness is required if reductions of road trauma are to continue.

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Ethiopia has one of Africa’s fastest growing non-oil producing economies and an increasing level of motorisation (AfDB, OECD, UNDP, & UNECA, 2012). This rapidly increasing mobility has created some unique road safety concerns; however there is scant published information and related commentary (United Nations Economic Commission for Africa, 2009). The objective of this paper is to quantify police-reported traffic crashes in Ethiopia and characterise the existing state of road safety. Six years (July 2005 - June 2011) of police-reported crash data were analysed, consisting of 12,140 fatal and 29,454 injury crashes on the country’s road network. The 12,140 fatal crashes involved 1,070 drivers, 5,702 passengers, and 7,770 pedestrians, totalling 14,542 fatalities, an average of 1.2 road user fatalities per crash. An important and glaring trend that emerges is that more than half of the fatalities in Ethiopia involve pedestrians. The majority of the crashes occur during daytime hours, involve males, and involve persons in the 18-50 age group—Ethiopia’s active workforce. Crashes frequently occur in mid blocks or roadways. The predominant collision between motor vehicles and pedestrians was a rollover on a road tangent section. Failing to observe the priority of pedestrians and speeding were the major causes of crashes attributed by police. Trucks and minibus taxis were involved in the majority of crashes, while automobiles (small vehicles) were less involved in crashes relative to other vehicle types, partially because small vehicles tend to be driven fewer kilometres per annum. These data illustrate and justify a high priority to identify and implement effective programs, policies, and countermeasures focused on reducing pedestrian crashes.

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Bicyclists are among the most vulnerable of road users, with high fatal crash rates. Although visibility aids have been widely advocated to help prevent bicycle-vehicle conflicts, to date no study has investigated, among crash-involved cyclists, the kind of visibility aids they were using at the time of the crash. This study undertook a detailed investigation of visibility factors involved in bicyclist-motor-vehicle crashes. We surveyed 184 bicyclists (predominantly from Australia via internet cycling forums) who had been involved in motor vehicle collisions regarding the perceived cause of the collision, ambient weather and general visibility, as well as the clothing and bicycle lights used by the bicyclist. Over a third of the crashes occurred in low light levels (dawn, dusk or night-time), which is disproportionate given that only a small proportion of bicyclists typically ride at these times. Importantly, 19% of these bicyclists reported not using bicycle lights at the time of the crash, and only 34% were wearing reflective clothing. Only two participants (of 184) nominated bicyclist visibility as the cause of the crash: 61% attributed the crash to driver inattention. These findings demonstrate that crash-involved bicyclists tend to under-rate and under-utilise visibility aids as a means of improving their safety.

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Portable water-filled barriers (PWFBs) are roadside appurtenances that are used to prevent errant vehicles from penetrating into temporary construction zones on roadways. A numerical model of the composite PWFB, consisting of a plastic shell, steel frame, water and foam was developed and validated against results from full scale experimental tests. This model can be extended to larger scale impact cases, specifically ones that include actual vehicle models. The cost-benefit of having a validated numerical model is significant and this allows the road barrier designer to conduct extensive tests via numerical simulations prior to standard impact tests Effects of foam cladding as additional energy absorption material in the PWFB was investigated. Different types of foam were treated and it was found that XPS foam was the most suitable foam type. Results from this study will aid PWFB designers in developing new generation of roadside structures which will provide enhanced road safety.

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Portable water-filled barriers (PWFBs) are roadside appurtenances that prevent vehicles from penetrating into temporary construction zones on roadways. PWFBs are required to satisfy the strict regulations for vehicle re-direction in tests. However, many of the current PWFBs fail to re-direct the vehicle at high speeds due to the inability of the joints to provide appropriate stiffness. The joint mechanism hence plays a crucial role in the performance of a PWFB system at high speed impacts. This paper investigates the desired features of the joint mechanism in a PWFB system that can re-direct vehicles at high speeds, while limiting the lateral displacement to acceptable limits. A rectangular “wall” representative of a 30 m long barrier system was modeled and a novel method of joining adjacent road barriers was introduced through appropriate pin-joint connections. The impact response of the barrier “wall” and the vehicle was obtained and the results show that a rotational stiffness of 3000 kNm/rad at the joints seems to provide the desired features of the PWFB system to re-direct impacting vehicles and restrict the lateral deflection. These research findings will be useful to safety engineers and road barrier designers in developing a new generation of PWFBs for increased road safety.

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This paper elaborates on the Cybercars-2 Wireless Communication Framework for driverless city vehicles, which is used for Vehicle-to-Vehicle and Vehicle-to-Infrastructure communication. The developed framework improves the safety and efficiency of driverless city vehicles. Furthermore, this paper also elaborates on the vehicle control software architecture. On-road tests of both the communication framework and its application for real-time decision making show that the communication framework is reliable and useful for improving the safe operation of driverless city vehicles.

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This paper presents an object-oriented world model for the road traffic environment of autonomous (driver-less) city vehicles. The developed World Model is a software component of the autonomous vehicle's control system, which represents the vehicle's view of its road environment. Regardless whether the information is a priori known, obtained through on-board sensors, or through communication, the World Model stores and updates information in real-time, notifies the decision making subsystem about relevant events, and provides access to its stored information. The design is based on software design patterns, and its application programming interface provides both asynchronous and synchronous access to its information. Experimental results of both a 3D simulation and real-world experiments show that the approach is applicable and real-time capable.

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Although safety statistics indicate that road crashes are the most common form of work-related fatalities, many organizations fail to treat company vehicles in the same manner as other physical safety hazards within the workplace. Traditionally, work-related road safety has targeted primarily driver-related issues and not adequately addressed organizational processes, such as the organizations’ safety system and risk management processes and practice. This inadequacy generally stems from a lack of specific contextual knowledge and basic requirements to improve work-related road safety, including the supporting systems to ensure any intervention strategy or initiative’s ongoing effectiveness. Therefore, informed by previous research and based on a case study methodology, the Organizational Work-Related Road Safety Situational Analysis was developed to assess organizations’ current work-related road safety system, including policy, procedures, processes and practice. The situational analysis tool is similar to a safety audit however is more comprehensive in detail, application and provides sufficient evidence to enable organizations to mitigate and manage their work-related road safety risks. In addition, data collected from this process assists organizations in making informed decisions regarding intervention strategy design, development, implementation and ongoing effectiveness. This paper reports on the effectiveness of the situational analysis tool to assess WRRS systems across five differing and diverse organizations; including gas exploration and mining, state government, local government, and not for profit/philanthropy. The outcomes of this project identified considerable differences in the degree by which the organizations’ addressed work-related road safety across their vehicle fleet operations and provides guidelines for improving organizations’ work-related road safety systems.

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Exhaust emissions from motor vehicles vary widely and depend on factors such as engine operating conditions, fuel, age, mileage and service history. A method has been devised to rapidly identify high-polluting vehicles as they travel on the road. The method is able to monitor emissions from a large number of vehicles in a short time and avoids the need to conduct expensive and time consuming tests on chassis dynamometers. A sample of the exhaust plume is captured as each vehicle passes a roadside monitoring station and the pollutant emission factors are calculated from the measured concentrations using carbon dioxide as a tracer. Although, similar methods have been used to monitor soot and gaseous mass emissions, to-date it has not been used to monitor particle number emissions from a large fleet of vehicles. This is particularly important as epidemiological studies have shown that particle number concentration is an important parameter in determining adverse health effects. The method was applied to measurements of particle number emissions from individual buses in the Brisbane City Council diesel fleet operating on the South-East Busway. Results indicate that the particle number emission factors are gamma- distributed, with a high proportion of the emissions being emitted by a small percentage of the buses. Although most of the high-emitters are the oldest buses in the fleet, there are clear exceptions, with some newer buses emitting as much. We attribute this to their recent service history, particularly pertaining to improper tuning of the engines. We recommend that a targeted correction program would be a highly effective measure in mitigating urban environmental pollution.

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This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e. the autonomous vehicles’ ability to make appropriate driving decisions in city road traffic situations. After decomposing the problem into two consecutive decision making stages, and giving a short overview about previous work, the paper explains how Multiple Criteria Decision Making (MCDM) can be used in the process of selecting the most appropriate driving maneuver.

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As governments seek to transition to more efficient vehicle fleets, one strategy has been to incentivize ‘green’ vehicle choice by exempting some of these vehicles from road user charges. As an example, to stimulate sales of Energy-Efficient Vehicles (EEVs) in Sweden, some of these automobiles were exempted from Stockholm’s congestion tax. In this paper the effect this policy had on the demand for new, privately-owned, exempt EEVs is assessed by first estimating a model of vehicle choice and then by applying this model to simulate vehicle alternative market shares under different policy scenarios. The database used to calibrate the model includes owner-specific demographics merged with vehicle registry data for all new private vehicles registered in Stockholm County during 2008. Characteristics of individuals with a higher propensity to purchase an exempt EEV were identified. The most significant factors included intra-cordon residency (positive), distance from home to the CBD (negative), and commuting across the cordon (positive). By calculating vehicle shares from the vehicle choice model and then comparing these estimates to a simulated scenario where the congestion tax exemption was inactive, the exemption was estimated to have substantially increased the share of newly purchased, private, exempt EEVs in Stockholm by 1.8% (+/- 0.3%; 95% C.I.) to a total share of 18.8%. This amounts to an estimated 10.7% increase in private, exempt EEV purchases during 2008 i.e. 519 privately owned, exempt EEVs.