Comparison of moped, scooter and motorcycle crash risk and crash severity

The increased popularity of mopeds and motor scooters in Australia and elsewhere in the last decade has contributed substantially to the greater use of powered two-wheelers (PTWs) as a whole. As the exposure of mopeds and scooters has increased, so too has the number of reported crashes involving those PTW types, but there is currently little research comparing the safety of mopeds and, particularly, larger scooters with motorcycles. This study compared the crash risk and crash severity of motorcycles, mopeds and larger scooters in Queensland, Australia. Comprehensive data cleansing was undertaken to separate motorcycles, mopeds and larger scooters in police-reported crash data covering the five years to 30 June 2008. The crash rates of motorcycles (including larger scooters) and mopeds in terms of registered vehicles were similar over this period, although the moped crash rate showed a stronger downward trend. However, the crash rates in terms of distance travelled were nearly four times higher for mopeds than for motorcycles (including larger scooters). More comprehensive distance travelled data is needed to confirm these findings. The overall severity of moped and scooter crashes was significantly lower than motorcycle crashes but an ordered probit regression model showed that crash severity outcomes related to differences in crash characteristics and circumstances, rather than differences between PTW types per se. Greater motorcycle crash severity was associated with higher (>80 km/h) speed zones, horizontal curves, weekend, single vehicle and nighttime crashes. Moped crashes were more severe at night and in speed zones of 90 km/h or more. Larger scooter crashes were more severe in 70 km/h zones (than 60 km/h zones) but not in higher speed zones, and less severe on weekends than on weekdays. The findings can be used to inform potential crash and injury countermeasures tailored to users of different PTW types.

Building an augmented map for road risk assessment

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.

Suicide and religion : new evidence on the differences between Protestantism and Catholicism

Suicide has remained a persistent social phenomenon and now accounts for more deaths than motor vehicle accidents. There has been much debate, however, over which religious constructs might best explain the variation in suicide rates. Our empirical analysis reveals that even though theological and social differences between Catholicism and Protestantism have decreased, Catholics are still less likely than Protestants to commit or accept suicide. This difference holds even after we control for such confounding factors as social and religious networks. In addition, although religious networks do mitigate suicides among Protestants, the influence of church attendance is more dominant among Catholics. Our analysis also indicates that alternative concepts such as religious commitment and religiosity strongly reduce suicide acceptance.

Identification of mechanism, PECARN risk factors and injury patterns in severe paediatric cervical spine injuries in Queensland

Introduction Canadian C spine rule and NEXUS criteria have identified risk factors for cervical spine injury in adults but not for children. PECARN has developed an 8 variable model for cervical spine injury in children. We sought to identify the mechanism, prevalence of PECARN risk factors, injury patterns, and management of severe Paediatric cervical spine injuries presenting to the major children’s hospitals in Brisbane, Australia. Methods This a retrospective study of the children with cervical spine injuries who presented directly or were referred to the major children’s hospitals in Brisbane over 5 years. Results There were 38 patients with 18 male and 20 female.The mean age was 8.6 years. They were divided into two groups according to their age, (Group 1 < =8 years had 18 (47%) patients, while group 2 (9-15 years) had 20 (53%) patients. Motor vehicle related injuries were the most common (61%) in Group 1 while it was sporting injuries (50%) in group 2. All patients in group 1 had upper cervical injury (C0-C2) while subaxial injuries were most common in group 2 (66.6%). 82% of the patients had 2 or more PECARN risk factors. 18 children (47%) had normal neurological assessment at presentation, 6 (16%) had radicular symptoms, 11 (29%) could not be assessed as they had already been intubated due to the severity of the injury, 3 (8%) had incomplete cord injury. 29 (69%) patients had normal neurological assessment at final follow up and 2 children died from their injuries. Conclusion Our study confirms that younger children sustain upper cervical injuries most commonly secondary to motor vehicle accidents, while the older sustain subaxial injuries from sporting activities. The significant prevalence of the PECARN risk factors among this cohort of patients have led to them being incorporated into a protocol at these hospitals used to assess patients with suspected cervical spinal injury.

A comparison of road traffic crashes along mountainous and non-mountainous roads in Sabah, Malaysia

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.

A comparison of road traffic crashes along mountainous and non-mountainous roads in Sabah, Malaysia

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.

A probability-based approach for assessing the relationship between crash accidents and pavement properties

Skid resistance is a condition parameter characterising the contribution that a road makes to the friction between a road surface and a vehicle tyre. Studies of traffic crash histories around the world have consistently found that a disproportionate number of crashes occur where the road surface has a low level of surface friction and/or surface texture, particularly when the road surface is wet. Various research results have been published over many years and have tried to quantify the influence of skid resistance on accident occurrence and to characterise a correlation between skid resistance and accident frequency. Most of the research studies used simple statistical correlation methods in analysing skid resistance and crash data.----- ------ Preliminary findings of a systematic and extensive literature search conclude that there is rarely a single causation factor in a crash. Findings from research projects do affirm various levels of correlation between skid resistance and accident occurrence. Studies indicate that the level of skid resistance at critical places such as intersections, curves, roundabouts, ramps and approaches to pedestrian crossings needs to be well maintained.----- ----- Management of risk is an integral aspect of the Queensland Department of Main Roads (QDMR) strategy for managing its infrastructure assets. The risk-based approach has been used in many areas of infrastructure engineering. However, very limited information is reported on using risk-based approach to mitigate crash rates related to road surface. Low skid resistance and surface texture may increase the risk of traffic crashes.----- ----- The objectives of this paper are to explore current issues of skid resistance in relation to crashes, to provide a framework of probability-based approach to be adopted by QDMR in assessing the relationship between crash accidents and pavement properties, and to explain why the probability-based approach is a suitable tool for QDMR in order to reduce accident rates due to skid resistance.

Do motor vehicle crashes arise from single or multiple unique risk processes? An inquiry into crash causes and modelling

Crashes at any particular transport network location consist of a chain of events arising from a multitude of potential causes and/or contributing factors whose nature is likely to reflect geometric characteristics of the road, spatial effects of the surrounding environment, and human behavioural factors. It is postulated that these potential contributing factors do not arise from the same underlying risk process, and thus should be explicitly modelled and understood. The state of the practice in road safety network management applies a safety performance function that represents a single risk process to explain crash variability across network sites. This study aims to elucidate the importance of differentiating among various underlying risk processes contributing to the observed crash count at any particular network location. To demonstrate the principle of this theoretical and corresponding methodological approach, the study explores engineering (e.g. segment length, speed limit) and unobserved spatial factors (e.g. climatic factors, presence of schools) as two explicit sources of crash contributing factors. A Bayesian Latent Class (BLC) analysis is used to explore these two sources and to incorporate prior information about their contribution to crash occurrence. The methodology is applied to the state controlled roads in Queensland, Australia and the results are compared with the traditional Negative Binomial (NB) model. A comparison of goodness of fit measures indicates that the model with a double risk process outperforms the single risk process NB model, and thus indicating the need for further research to capture all the three crash generation processes into the SPFs.

All-terrain vehicle crashes and associated injuries in North Queensland : findings from the Rural and Remote Road Safety Study

Objective: To define characteristics of all-terrain vehicle (ATV) crashes occurring in north Queensland from March 2004 till June 2007 with the exploration of associated risk factors. Design: Descriptive analysis of ATV crash data collected by the Rural and Remote Road Safety Study. Setting: Rural and remote north Queensland. Participants: Forty-two ATV drivers and passengers aged 16 years or over hospitalised at Atherton, Cairns, Mount Isa or Townsville for at least 24 hours as a result of a vehicle crash. Main outcome measures: Demographics of participants, reason for travel, nature of crash, injuries sustained and risk factors associated with ATV crash. Results: The majority of casualties were men aged 16–64. Forty-one per cent of accidents occurred while performing agricultural tasks. Furthermore, 39% of casualties had less than one year’s experience riding ATVs. Over half the casualties were not wearing a helmet at the time of the crash. Common injuries were head and neck and upper limb injuries. Rollovers tended to occur while performing agricultural tasks and most commonly resulted in multiple injuries. Conclusions: Considerable trauma results from ATV crashes in rural and remote north Queensland. These crashes are not included in most general vehicle crash data sets, as they are usually limited to events occurring on public roads. Minimal legislation and regulation currently applies to ATV use in agricultural, recreational and commercial settings. Legislation on safer design of ATVs and mandatory courses for riders is an essential part of addressing the burden of ATV crashes on rural and remote communities.

Mapping a suburb with a single camera using a biologically inspired SLAM system

This paper describes a biologically inspired approach to vision-only simultaneous localization and mapping (SLAM) on ground-based platforms. The core SLAM system, dubbed RatSLAM, is based on computational models of the rodent hippocampus, and is coupled with a lightweight vision system that provides odometry and appearance information. RatSLAM builds a map in an online manner, driving loop closure and relocalization through sequences of familiar visual scenes. Visual ambiguity is managed by maintaining multiple competing vehicle pose estimates, while cumulative errors in odometry are corrected after loop closure by a map correction algorithm. We demonstrate the mapping performance of the system on a 66 km car journey through a complex suburban road network. Using only a web camera operating at 10 Hz, RatSLAM generates a coherent map of the entire environment at real-time speed, correctly closing more than 51 loops of up to 5 km in length.

On the nature of over-dispersion in motor vehicle crash prediction models

Statistical modeling of traffic crashes has been of interest to researchers for decades. Over the most recent decade many crash models have accounted for extra-variation in crash counts—variation over and above that accounted for by the Poisson density. The extra-variation – or dispersion – is theorized to capture unaccounted for variation in crashes across sites. The majority of studies have assumed fixed dispersion parameters in over-dispersed crash models—tantamount to assuming that unaccounted for variation is proportional to the expected crash count. Miaou and Lord [Miaou, S.P., Lord, D., 2003. Modeling traffic crash-flow relationships for intersections: dispersion parameter, functional form, and Bayes versus empirical Bayes methods. Transport. Res. Rec. 1840, 31–40] challenged the fixed dispersion parameter assumption, and examined various dispersion parameter relationships when modeling urban signalized intersection accidents in Toronto. They suggested that further work is needed to determine the appropriateness of the findings for rural as well as other intersection types, to corroborate their findings, and to explore alternative dispersion functions. This study builds upon the work of Miaou and Lord, with exploration of additional dispersion functions, the use of an independent data set, and presents an opportunity to corroborate their findings. Data from Georgia are used in this study. A Bayesian modeling approach with non-informative priors is adopted, using sampling-based estimation via Markov Chain Monte Carlo (MCMC) and the Gibbs sampler. A total of eight model specifications were developed; four of them employed traffic flows as explanatory factors in mean structure while the remainder of them included geometric factors in addition to major and minor road traffic flows. The models were compared and contrasted using the significance of coefficients, standard deviance, chi-square goodness-of-fit, and deviance information criteria (DIC) statistics. The findings indicate that the modeling of the dispersion parameter, which essentially explains the extra-variance structure, depends greatly on how the mean structure is modeled. In the presence of a well-defined mean function, the extra-variance structure generally becomes insignificant, i.e. the variance structure is a simple function of the mean. It appears that extra-variation is a function of covariates when the mean structure (expected crash count) is poorly specified and suffers from omitted variables. In contrast, when sufficient explanatory variables are used to model the mean (expected crash count), extra-Poisson variation is not significantly related to these variables. If these results are generalizable, they suggest that model specification may be improved by testing extra-variation functions for significance. They also suggest that known influences of expected crash counts are likely to be different than factors that might help to explain unaccounted for variation in crashes across sites

Digital human modelling for vehicle design and manufacturing

Digital human modelling (DHM) has today matured from research into industrial application. In the automotive domain, DHM has become a commonly used tool in virtual prototyping and human-centred product design. While this generation of DHM supports the ergonomic evaluation of new vehicle design during early design stages of the product, by modelling anthropometry, posture, motion or predicting discomfort, the future of DHM will be dominated by CAE methods, realistic 3D design, and musculoskeletal and soft tissue modelling down to the micro-scale of molecular activity within single muscle fibres. As a driving force for DHM development, the automotive industry has traditionally used human models in the manufacturing sector (production ergonomics, e.g. assembly) and the engineering sector (product ergonomics, e.g. safety, packaging). In product ergonomics applications, DHM share many common characteristics, creating a unique subset of DHM. These models are optimised for a seated posture, interface to a vehicle seat through standardised methods and provide linkages to vehicle controls. As a tool, they need to interface with other analytic instruments and integrate into complex CAD/CAE environments. Important aspects of current DHM research are functional analysis, model integration and task simulation. Digital (virtual, analytic) prototypes or digital mock-ups (DMU) provide expanded support for testing and verification and consider task-dependent performance and motion. Beyond rigid body mechanics, soft tissue modelling is evolving to become standard in future DHM. When addressing advanced issues beyond the physical domain, for example anthropometry and biomechanics, modelling of human behaviours and skills is also integrated into DHM. Latest developments include a more comprehensive approach through implementing perceptual, cognitive and performance models, representing human behaviour on a non-physiologic level. Through integration of algorithms from the artificial intelligence domain, a vision of the virtual human is emerging.

Experimental studies of wireless communication and GNSS kinematic positioning performance in high-mobility vehicle environments

In order to support intelligent transportation system (ITS) road safety applications such as collision avoidance, lane departure warnings and lane keeping, Global Navigation Satellite Systems (GNSS) based vehicle positioning system has to provide lane-level (0.5 to 1 m) or even in-lane-level (0.1 to 0.3 m) accurate and reliable positioning information to vehicle users. However, current vehicle navigation systems equipped with a single frequency GPS receiver can only provide road-level accuracy at 5-10 meters. The positioning accuracy can be improved to sub-meter or higher with the augmented GNSS techniques such as Real Time Kinematic (RTK) and Precise Point Positioning (PPP) which have been traditionally used in land surveying and or in slowly moving environment. In these techniques, GNSS corrections data generated from a local or regional or global network of GNSS ground stations are broadcast to the users via various communication data links, mostly 3G cellular networks and communication satellites. This research aimed to investigate the precise positioning system performances when operating in the high mobility environments. This involves evaluation of the performances of both RTK and PPP techniques using: i) the state-of-art dual frequency GPS receiver; and ii) low-cost single frequency GNSS receiver. Additionally, this research evaluates the effectiveness of several operational strategies in reducing the load on data communication networks due to correction data transmission, which may be problematic for the future wide-area ITS services deployment. These strategies include the use of different data transmission protocols, different correction data format standards, and correction data transmission at the less-frequent interval. A series of field experiments were designed and conducted for each research task. Firstly, the performances of RTK and PPP techniques were evaluated in both static and kinematic (highway with speed exceed 80km) experiments. RTK solutions achieved the RMS precision of 0.09 to 0.2 meter accuracy in static and 0.2 to 0.3 meter in kinematic tests, while PPP reported 0.5 to 1.5 meters in static and 1 to 1.8 meter in kinematic tests by using the RTKlib software. These RMS precision values could be further improved if the better RTK and PPP algorithms are adopted. The tests results also showed that RTK may be more suitable in the lane-level accuracy vehicle positioning. The professional grade (dual frequency) and mass-market grade (single frequency) GNSS receivers were tested for their performance using RTK in static and kinematic modes. The analysis has shown that mass-market grade receivers provide the good solution continuity, although the overall positioning accuracy is worse than the professional grade receivers. In an attempt to reduce the load on data communication network, we firstly evaluate the use of different correction data format standards, namely RTCM version 2.x and RTCM version 3.0 format. A 24 hours transmission test was conducted to compare the network throughput. The results have shown that 66% of network throughput reduction can be achieved by using the newer RTCM version 3.0, comparing to the older RTCM version 2.x format. Secondly, experiments were conducted to examine the use of two data transmission protocols, TCP and UDP, for correction data transmission through the Telstra 3G cellular network. The performance of each transmission method was analysed in terms of packet transmission latency, packet dropout, packet throughput, packet retransmission rate etc. The overall network throughput and latency of UDP data transmission are 76.5% and 83.6% of TCP data transmission, while the overall accuracy of positioning solutions remains in the same level. Additionally, due to the nature of UDP transmission, it is also found that 0.17% of UDP packets were lost during the kinematic tests, but this loss doesn't lead to significant reduction of the quality of positioning results. The experimental results from the static and the kinematic field tests have also shown that the mobile network communication may be blocked for a couple of seconds, but the positioning solutions can be kept at the required accuracy level by setting of the Age of Differential. Finally, we investigate the effects of using less-frequent correction data (transmitted at 1, 5, 10, 15, 20, 30 and 60 seconds interval) on the precise positioning system. As the time interval increasing, the percentage of ambiguity fixed solutions gradually decreases, while the positioning error increases from 0.1 to 0.5 meter. The results showed the position accuracy could still be kept at the in-lane-level (0.1 to 0.3 m) when using up to 20 seconds interval correction data transmission.

Aircraft collision avoidance using spherical visual predictive control and single point features

This paper presents practical vision-based collision avoidance for objects approximating a single point feature. Using a spherical camera model, a visual predictive control scheme guides the aircraft around the object along a conical spiral trajectory. Visibility, state and control constraints are considered explicitly in the controller design by combining image and vehicle dynamics in the process model, and solving the nonlinear optimization problem over the resulting state space. Importantly, range is not required. Instead, the principles of conical spiral motion are used to design an objective function that simultaneously guides the aircraft along the avoidance trajectory, whilst providing an indication of the appropriate point to stop the spiral behaviour. Our approach is aimed at providing a potential solution to the See and Avoid problem for unmanned aircraft and is demonstrated through a series.