521 resultados para on-road driving assessment


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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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We conducted on-road and simulator studies to explore the mechanisms underpinning driver-rider crashes. In Study 1 the verbal protocols of 40 drivers and riders were assessed at intersections as part of a 15km on-road route in Melbourne. Network analysis of the verbal transcripts highlighted key differences in the situation awareness of drivers and riders at intersections. In a further study using a driving simulator we examined in car drivers the influence of acute exposure to motorcyclists. In a 15 min simulated drive, 40 drivers saw either no motorcycles or a high number of motorcycles in the surrounding traffic. In a subsequent 45-60 min drive, drivers were asked to detect motorcycles in traffic. The proportion of motorcycles was manipulated so that there was either a high (120) or low (6) number of motorcycles during the drive. Those drivers exposed to a high number of motorcycles were significantly faster at detecting motorcycles. Fundamentally, the incompatible situation awareness at intersections by drivers and riders underpins the conflicts. Study 2 offers some suggestion for a countermeasure here, although more research around schema and exposure training to support safer interactions is needed.

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Human exposures in transportation microenvironments are poorly represented by ambient stationary monitoring. A number of on-road studies using vehicle-based mobile monitoring have been conducted to address this. Most previous studies were conducted on urban roads in developed countries where the primary emission source was vehicles. Few studies have examined on-road pollution in developing countries in urban settings. Currently, no study has been conducted for roadways in rural environments where a substantial proportion of the population live. This study aimed to characterize on-road air quality on the East-West Highway (EWH) in Bhutan and identify its principal sources. We conducted six mobile measurements of PM10, particle number (PN) count and CO along the entire 570 km length of the EWH. We divided the EWH into five segments, R1-R5, taking the road length between two district towns as a single road segment. The pollutant concentrations varied widely along the different road segments, with the highest concentrations for R5 compared with other road segments (PM10 = 149 µg/m3, PN = 5.74 × 104 particles/cm-3, CO = 0.19 ppm), which is the final segment of the road to the capital. Apart from vehicle emissions, the dominant sources were road works, unpaved roads and roadside combustion activities. Overall, the highest contributions above the background levels were made by unpaved roads for PM10 (6 times background), and vehicle emissions for PN and CO (5 and 15 times background, respectively). Notwithstanding the differences in instrumentation used and particle size range measured, the current study showed lower PN concentrations compared with similar on-road studies. However, concentrations were still high enough that commuters, road maintenance workers and residents living along the EWH, were potentially exposed to elevated pollutant concentrations from combustion and non-combustion sources. Future studies should focus on assessing the dispersion patterns of roadway pollutants and defining the short- and long-term health impacts of exposure in Bhutan, as well as in other developing countries with similar characteristics.

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Assessment and prediction of the impact of vehicular traffic emissions on air quality and exposure levels requires knowledge of vehicle emission factors. The aim of this study was quantification of emission factors from an on road, over twelve months measurement program conducted at two sites in Brisbane: 1) freeway type (free flowing traffic at about 100 km/h, fleet dominated by small passenger cars - Tora St); and 2) urban busy road with stop/start traffic mode, fleet comprising a significant fraction of heavy duty vehicles - Ipswich Rd. A physical model linking concentrations measured at the road for specific meteorological conditions with motor vehicle emission factors was applied for data analyses. The focus of the study was on submicrometer particles; however the measurements also included supermicrometer particles, PM2.5, carbon monoxide, sulfur dioxide, oxides of nitrogen. The results of the study are summarised in this paper. In particular, the emission factors for submicrometer particles were 6.08 x 1013 and 5.15 x 1013 particles per vehicle-1 km-1 for Tora St and Ipswich Rd respectively and for supermicrometer particles for Tora St, 1.48 x 109 particles per vehicle-1 km-1. Emission factors of diesel vehicles at both sites were about an order of magnitude higher than emissions from gasoline powered vehicles. For submicrometer particles and gasoline vehicles the emission factors were 6.08 x 1013 and 4.34 x 1013 particles per vehicle-1 km-1 for Tora St and Ipswich Rd, respectively, and for diesel vehicles were 5.35 x 1014 and 2.03 x 1014 particles per vehicle-1 km-1 for Tora St and Ipswich Rd, respectively. For supermicrometer particles at Tora St the emission factors were 2.59 x 109 and 1.53 x 1012 particles per vehicle-1 km-1, for gasoline and diesel vehicles, respectively.

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This study investigated the effects of visual status, driver age and the presence of secondary distracter tasks on driving performance. Twenty young (M = 26.8 years) and 19 old (M = 70.2 years) participants drove around a closed-road circuit under three visual (normal, simulated cataracts, blur) and three distracter conditions (none, visual, auditory). Simulated visual impairment, increased driver age and the presence of a distracter task detrimentally affected all measures of driving performance except gap judgments and lane keeping. Significant interaction effects were evident between visual status, age and distracters; simulated cataracts had the most negative impact on performance in the presence of visual distracters and a more negative impact for older drivers. The implications of these findings for driving behaviour and acquisition of driving-related information for people with common visual impairments are discussed

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Road curves are an important feature of road infrastructure and many serious crashes occur on road curves. In Queensland, the number of fatalities is twice as many on curves as that on straight roads. Therefore, there is a need to reduce drivers’ exposure to crash risk on road curves. Road crashes in Australia and in the Organisation for Economic Co-operation and Development(OECD) have plateaued in the last five years (2004 to 2008) and the road safety community is desperately seeking innovative interventions to reduce the number of crashes. However, designing an innovative and effective intervention may prove to be difficult as it relies on providing theoretical foundation, coherence, understanding, and structure to both the design and validation of the efficiency of the new intervention. Researchers from multiple disciplines have developed various models to determine the contributing factors for crashes on road curves with a view towards reducing the crash rate. However, most of the existing methods are based on statistical analysis of contributing factors described in government crash reports. In order to further explore the contributing factors related to crashes on road curves, this thesis designs a novel method to analyse and validate these contributing factors. The use of crash claim reports from an insurance company is proposed for analysis using data mining techniques. To the best of our knowledge, this is the first attempt to use data mining techniques to analyse crashes on road curves. Text mining technique is employed as the reports consist of thousands of textual descriptions and hence, text mining is able to identify the contributing factors. Besides identifying the contributing factors, limited studies to date have investigated the relationships between these factors, especially for crashes on road curves. Thus, this study proposed the use of the rough set analysis technique to determine these relationships. The results from this analysis are used to assess the effect of these contributing factors on crash severity. The findings obtained through the use of data mining techniques presented in this thesis, have been found to be consistent with existing identified contributing factors. Furthermore, this thesis has identified new contributing factors towards crashes and the relationships between them. A significant pattern related with crash severity is the time of the day where severe road crashes occur more frequently in the evening or night time. Tree collision is another common pattern where crashes that occur in the morning and involves hitting a tree are likely to have a higher crash severity. Another factor that influences crash severity is the age of the driver. Most age groups face a high crash severity except for drivers between 60 and 100 years old, who have the lowest crash severity. The significant relationship identified between contributing factors consists of the time of the crash, the manufactured year of the vehicle, the age of the driver and hitting a tree. Having identified new contributing factors and relationships, a validation process is carried out using a traffic simulator in order to determine their accuracy. The validation process indicates that the results are accurate. This demonstrates that data mining techniques are a powerful tool in road safety research, and can be usefully applied within the Intelligent Transport System (ITS) domain. The research presented in this thesis provides an insight into the complexity of crashes on road curves. The findings of this research have important implications for both practitioners and academics. For road safety practitioners, the results from this research illustrate practical benefits for the design of interventions for road curves that will potentially help in decreasing related injuries and fatalities. For academics, this research opens up a new research methodology to assess crash severity, related to road crashes on curves.

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Purpose. To investigate the effect of various presbyopic vision corrections on nighttime driving performance on a closed-road driving circuit. Methods. Participants were 11 presbyopes (mean age, 57.3 ± 5.8 years), with a mean best sphere distance refractive error of R+0.23±1.53 DS and L+0.20±1.50 DS, whose only experience of wearing presbyopic vision correction was reading spectacles. The study involved a repeated-measures design by which a participant's nighttime driving performance was assessed on a closed-road circuit while wearing each of four power-matched vision corrections. These included single-vision distance lenses (SV), progressive-addition spectacle lenses (PAL), monovision contact lenses (MV), and multifocal contact lenses (MTF CL) worn in a randomized order. Measures included low-contrast road hazard detection and avoidance, road sign and near target recognition, lane-keeping, driving time, and legibility distance for street signs. Eye movement data (fixation duration and number of fixations) were also recorded. Results. Street sign legibility distances were shorter when wearing MV and MTF CL than SV and PAL (P < 0.001), and participants drove more slowly with MTF CL than with PALs (P = 0.048). Wearing SV resulted in more errors (P < 0.001) and in more (P = 0.002) and longer (P < 0.001) fixations when responding to near targets. Fixation duration was also longer when viewing distant signs with MTF CL than with PAL (P = 0.031). Conclusions. Presbyopic vision corrections worn by naive, unadapted wearers affected nighttime driving. Overall, spectacle corrections (PAL and SV) performed well for distance driving tasks, but SV negatively affected viewing near dashboard targets. MTF CL resulted in the shortest legibility distance for street signs and longer fixation times.

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PURPOSE: This study investigated the effects of simulated visual impairment on nighttime driving performance and pedestrian recognition under real-road conditions. METHODS: Closed road nighttime driving performance was measured for 20 young visually normal participants (M = 27.5 +/- 6.1 years) under three visual conditions: normal vision, simulated cataracts, and refractive blur that were incorporated in modified goggles. The visual acuity levels for the cataract and blur conditions were matched for each participant. Driving measures included sign recognition, avoidance of low contrast road hazards, time to complete the course, and lane keeping. Pedestrian recognition was measured for pedestrians wearing either black clothing or black clothing with retroreflective markings on the moveable joints to create the perception of biological motion ("biomotion"). RESULTS: Simulated visual impairment significantly reduced participants' ability to recognize road signs, avoid road hazards, and increased the time taken to complete the driving course (p < 0.05); the effect was greatest for the cataract condition, even though the cataract and blur conditions were matched for visual acuity. Although visual impairment also significantly reduced the ability to recognize the pedestrian wearing black clothing, the pedestrian wearing "biomotion" was seen 80% of the time. CONCLUSIONS: Driving performance under nighttime conditions was significantly degraded by modest visual impairment; these effects were greatest for the cataract condition. Pedestrian recognition was greatly enhanced by marking limb joints in the pattern of "biomotion," which was relatively robust to the effects of visual impairment.

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Purpose: To compare self-reported driving difficulty by persons with hemianopic or quadrantanopic field loss with that reported by age-matched drivers with normal visual fields; and to examine how their self- reported driving difficulty compares to ratings of driving performance provided by a certified driving rehabilitation specialist(CDRS). Method: Participants were 17 persons with hemianopic field loss, 7 with quadrantanopic loss, and 24 age-matched controls with normal visual fields, all of whom had current drivers’ licenses. Information was collected via questionnaire regarding driving difficulties experienced in 21 typical driving situations grouped into 3 categories(involvement of peripheral vision, low visibility conditions, and independent mobility). On-road driving performance was evaluated by a CDRS using a standard assessment scale. Results: Drivers with hemianopic and quadrantanopic field loss expressed significantly more difficulty with driving maneuvers involving peripheral vision and independent mobility, compared to those with normal visual fields. Drivers with hemianopia and quadrantanopia who were rated as unsafe to drive based upon an on-road assessment by the CDRS were no more likely to report driving difficulty than those rated as safe. Conclusion: This study highlights aspects of driving that hemianopic or quadrantanopic persons find particularly problematic, thus suggesting areas that could be focused on driving rehabilitation. Some drivers with hemianopia or quadrantanopia may inappropriately view themselves as good drivers when in fact their driving performance is unsafe as judged by a driving professional.

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Drink driving contributes towards high injury rates for Indigenous populations in Canada and Australia, particularly in more isolated regions. At present there is limited research on the cultural and psychosocial factors that underpin Indigenous peoples’ drink driving. This study is part of a broader project aiming to inform a culturally sensitive program. Qualitative interviews with 29 convicted Indigenous drink drivers (aged 20-51 years) from a remote region of Queensland, Australia were used to explore their cognitions about, and underlying motivation for, drink driving as well as the factors that might facilitate or impede it. Although a number of themes were identified, this paper will focus on the first theme, respondents’ self-perceived rationale for their behaviour. Two subthemes were identified: ‘being the hero’ referred to situations where respondents were motivated by a bravado mentality to drive after drinking despite having, on some occasions, the opportunity to avoid this (e.g. another person offering to drive); and ‘family obligations’ which referred to situations where respondents described pressure from members of their extended families to drive after drinking. The underlying responsibility for transporting family members appeared to be difficult to avoid and related to cultural values. Findings indicate the social and individual characteristics for younger drink drivers are similar to mainstream populations. However, the reinforcers for Indigenous drink drivers may be different for this population, consistent with findings on other Indigenous populations outside Australia. Specific programs should contain a family-centred approach and explore the kinship value system to build strategies around these strong relationships.

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Situation awareness, ones understanding of ‘what is going on’, is a critical commodity for road users. Although the concept has received much attention in the driving context, situation awareness in vulnerable road users, such as cyclists, remains unexplored. This paper presents the findings from an exploratory on-road study of cyclist situation awareness, the aim of which was to explore how cyclists develop situation awareness, what their situation awareness comprises, and what the causes of degraded cyclist situation awareness may be. Twenty participants cycled a pre-defined urban on-road study route. A range of data were collected, including verbal protocols, forward scene video and rear video, and a network analysis procedure was used to describe and assess cyclist situation awareness. The analysis produced a number of key findings regarding cyclist situation awareness, including the potential for cyclists’ awareness of other road users to be degraded due to additional situation awareness and decision making requirements that are placed on them in certain road situations. Strategies for improving cyclists’ situation awareness are discussed.

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Background. To establish whether sensorimotor function and balance are associated with on-road driving performance in older adults. Methods. The performance of 270 community-living adults aged 70–88 years recruited via the electoral roll was measured on a battery of peripheral sensation, strength, flexibility, reaction time, and balance tests and on a standardized measure of on-road driving performance. Results. Forty-seven participants (17.4%) were classified as unsafe based on their driving assessment. Unsafe driving was associated with reduced peripheral sensation, lower limb weakness, reduced neck range of motion, slow reaction time, and poor balance in univariate analyses. Multivariate logistic regression analysis identified poor vibration sensitivity, reduced quadriceps strength, and increased sway on a foam surface with eyes closed as significant and independent risk factors for unsafe driving. These variables classified participants into safe and unsafe drivers with a sensitivity of 74% and specificity of 70%. Conclusions. A number of sensorimotor and balance measures were associated with driver safety and the multivariate model comprising measures of sensation, strength, and balance was highly predictive of unsafe driving in this sample. These findings highlight important determinants of driver safety and may assist in developing efficacious driver safety strategies for older drivers.

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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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Self-regulation is a coping strategy that allows older drivers to drive safely for longer. Self-regulation depends largely on the ability of drivers to evaluate their own driving. Therefore the success of self-regulation, in terms of driving safety, is influenced by the ability of older drivers to have insight into their declining driving performance. In addition, previous studies suggest that providing feedback to older adults regarding their driving skills may lead them to change their driving behaviour. However, little is currently known about the impact of feedback on older drivers’ self-awareness and their subsequent driving regulatory behaviour. This study explored the process of self-regulation and driving cessation among older drivers using the PAPM as a framework. It also investigated older adults’ perceptions and opinions about receiving feedback in regards to their driving abilities. Qualitative focus groups with 27 participants aged 70 years or more were conducted. Thematic analysis resulted in the development of five main themes; the meaning of driving, changes in driving pattern, feedback, the planning process, and solutions. The analysis also resulted in an initial model of driving self-regulation among older drivers that is informed by the current research and the Precaution Adoption Process Model as the theoretical framework. It identifies a number of social, personal, and environmental factors that can either facilitate or hinder people’s transition between stages of change. The findings from this study suggest that further elaboration of the PAPM is needed to take into account the role of insight and feedback on the process of self-regulation among older drivers.

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Objective Driver sleepiness contributes substantially to road crash incidents. Simulator and on-road studies clearly reveal an impairing effect from sleepiness on driving ability. However, the degree to which drivers appreciate the dangerousness of driving while sleepy is somewhat unclear. This study sought to determine drivers’ on-road experiences of sleepiness, their prior sleep habits, and personal awareness of the signs of sleepiness. Methods Participants were a random selection of 92 drivers travelling on a major highway in the state of Queensland, Australia, who were stopped by police as part of routine drink driving operations. Participants completed a brief questionnaire that included demographic information, sleepy driving experiences (signs of sleepiness and on-road experiences of sleepiness), and prior sleep habits. A modified version of the Karolinska Sleepiness Scale (KSS) was used to assess subjective sleepiness in the 15 minutes prior to being stopped by police. Results Participants rating of subjective sleepiness were quite low, with 90% reporting being alert to extremely alert on the KSS. Participants were reasonably aware of the signs of sleepiness, with many signs of sleepiness associated with on-road experiences of sleepiness. Additionally, the number of hours spent driving was positively correlated with the drivers’ level of sleep debt. Conclusions The results suggest the participants had moderate experience of driving while sleepy and many were aware of the signs of sleepiness. The relationship between driving long distances and increased sleep debt is a concern for road safety – increased education regarding the dangers of sleepy driving seems warranted.