An analysis of accidents in New York State by make of vehicle. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Spectral analysis of the effects of daylight saving time on motor vehicle fatal traffic accidents. Final report.

National Highway Traffic Safety Administration, Mathematical Analysis Division, Washington, D.C.

Driver and vehicle characteristics as related to the precipitation of accidents. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Summary of motor vehicle traffic accidents.

Each monthly issue is cumulative.

Summary of motor vehicle traffic accidents :

Description based on: 6 months, 1959; title from caption.

Estimation and prediction of average vehicle occupancies using traffic accident records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver’s age, and driver’s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Estimation and Prediction of Average Vehicle Occupancies using Traffic Accident Records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver¡¯s age, and driver¡¯s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

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.

Vehicle-to-vehicle real-time relative positioning using 5.9 GHz DSRC media

Vehicular accidents are one of the deadliest safety hazards and accordingly an immense concern of individuals and governments. Although, a wide range of active autonomous safety systems, such as advanced driving assistance and lane keeping support, are introduced to facilitate safer driving experience, these stand-alone systems have limited capabilities in providing safety. Therefore, cooperative vehicular systems were proposed to fulfill more safety requirements. Most cooperative vehicle-to-vehicle safety applications require relative positioning accuracy of decimeter level with an update rate of at least 10 Hz. These requirements cannot be met via direct navigation or differential positioning techniques. This paper studies a cooperative vehicle platform that aims to facilitate real-time relative positioning (RRP) among adjacent vehicles. The developed system is capable of exchanging both GPS position solutions and raw observations using RTCM-104 format over vehicular dedicated short range communication (DSRC) links. Real-time kinematic (RTK) positioning technique is integrated into the system to enable RRP to be served as an embedded real-time warning system. The 5.9 GHz DSRC technology is adopted as the communication channel among road-side units (RSUs) and on-board units (OBUs) to distribute GPS corrections data received from a nearby reference station via the Internet using cellular technologies, by means of RSUs, as well as to exchange the vehicular real-time GPS raw observation data. Ultimately, each receiving vehicle calculates relative positions of its neighbors to attain a RRP map. A series of real-world data collection experiments was conducted to explore the synergies of both DSRC and positioning systems. The results demonstrate a significant enhancement in precision and availability of relative positioning at mobile vehicles.

The role of sleepiness, sleep disorders, and the work environment on heavy-vehicle crashes in 2 Australian states

Heavy-vehicle driving involves a challenging work environment and a high crash rate. We investigated the associations of sleepiness, sleep disorders, and work environment (including truck characteristics) with the risk of crashing between 2008 and 2011 in the Australian states of New South Wales and Western Australia. We conducted a case-control study of 530 heavy-vehicle drivers who had recently crashed and 517 heavy-vehicle drivers who had not. Drivers' crash histories, truck details, driving schedules, payment rates, sleep patterns, and measures of health were collected. Subjects wore a nasal flow monitor for 1 night to assess for obstructive sleep apnea. Driving schedules that included the period between midnight and 5:59 am were associated with increased likelihood of crashing (odds ratio = 3.42, 95% confidence interval: 2.04, 5.74), as were having an empty load (odds ratio = 2.61, 95% confidence interval: 1.72, 3.97) and being a less experienced driver (odds ratio = 3.25, 95% confidence interval: 2.37, 4.46). Not taking regular breaks and the lack of vehicle safety devices were also associated with increased crash risk. Despite the high prevalence of obstructive sleep apnea, it was not associated with the risk of a heavy-vehicle nonfatal, nonsevere crash. Scheduling of driving to avoid midnight-to-dawn driving and the use of more frequent rest breaks are likely to reduce the risk of heavy-vehicle nonfatal, nonsevere crashes by 2–3 times.