An investigation on multi-vehicle motorcycle crashes using log-linear models

Motorcyclists are the most crash-prone road-user group in many Asian countries including Singapore; however, factors influencing motorcycle crashes are still not well understood. This study examines the effects of various roadway characteristics, traffic control measures and environmental factors on motorcycle crashes at different location types including expressways and intersections. Using techniques of categorical data analysis, this study has developed a set of log-linear models to investigate multi-vehicle motorcycle crashes in Singapore. Motorcycle crash risks in different circumstances have been calculated after controlling for the exposure estimated by the induced exposure technique. Results show that night-time influence increases crash risks of motorcycles particularly during merging and diverging manoeuvres on expressways, and turning manoeuvres at intersections. Riders appear to exercise more care while riding on wet road surfaces particularly during night. Many hazardous interactions at intersections tend to be related to the failure of drivers to notice a motorcycle as well as to judge correctly the speed/distance of an oncoming motorcycle. Road side conflicts due to stopping/waiting vehicles and interactions with opposing traffic on undivided roads have been found to be as detrimental factors on motorcycle safety along arterial, main and local roads away from intersections. Based on the findings of this study, several targeted countermeasures in the form of legislations, rider training, and safety awareness programmes have been recommended.

An estimate of road accident costs in Singapore

An earlier study by the Asian Development Bank (ADB) showed that the annual cost of road traffic accidents in 2001 was S$699.36 million which was 0.5% of the annual GDP. This paper attempts to update of the cost estimates of road traffic accidents. More precise methods of computing the human cost, lost output and property damage are adopted which grew in an annual cost of S$610.3 million or 0.338% of the annual GDP in 2003. A more conservative estimate of S$878,000 for fatal accident is also obtained, compared to the earlier figure of S$1.4 million. This study has shown that it is necessary to update the annual traffic accident costs regularly, as the figures vary with the number of accidents which change with time.

Modeling random effect and excess zeros in road traffic accident prediction

Poisson distribution has often been used for count like accident data. Negative Binomial (NB) distribution has been adopted in the count data to take care of the over-dispersion problem. However, Poisson and NB distributions are incapable of taking into account some unobserved heterogeneities due to spatial and temporal effects of accident data. To overcome this problem, Random Effect models have been developed. Again another challenge with existing traffic accident prediction models is the distribution of excess zero accident observations in some accident data. Although Zero-Inflated Poisson (ZIP) model is capable of handling the dual-state system in accident data with excess zero observations, it does not accommodate the within-location correlation and between-location correlation heterogeneities which are the basic motivations for the need of the Random Effect models. This paper proposes an effective way of fitting ZIP model with location specific random effects and for model calibration and assessment the Bayesian analysis is recommended.

Developing targeted countermeasures to improve motorcycle safety

The fatality and injury rate of motorcyclists per registered vehicle are higher than those of other motor vehicles by 13 and 7 times respectively. The crash involvement rate of motorcyclists as a victim party is 58% at intersections and as an offending party is 67% at expressways. Previous research efforts showed that the motorcycle safety programs are not very effective in improving motorcycle safety. This is perhaps due to inefficient design of safety program as specific causal factors may not be well explored. The objective of this study is to propose more sophisticated countermeasures and awareness programs for improving motorcycle safety after analyzing specific causal factors for motorcycle crashes at intersections and expressways. Methodologically this study applies the binary logistic model to explore the at-fault or not-at-fault crash involvement of motorcyclists at those locations. A number of explanatory variables representing roadway characteristics, environmental factors, motorcycle descriptions, and rider demographics have been evaluated. Results shows that the night time crash occurrence, presence of red light camera, lane position, rider age, licence class, and multivehicle collision significantly affect the fault of motorcyclists involved in crashes at intersections. On the other hand, the night time crash occurrence, lane position, speed limit, rider age, licence class, engine capacity, riding with pillion passenger, foreign registered motorcycles, and multivehicle collision has been found to be significant at expressways. Legislate to wear reflective clothes and using reflective markings on the motorcycles and helmets are suggested as an effective countermeasure for reducing their vulnerability. The red light cameras at intersections reduce the vulnerability of motorcycles and hence motorcycle flow and motorcycle crashes should be considered during installation of red light cameras. At signalized intersections, motorcyclists may be taught to follow correct movement and queuing rather than weaving through the traffic as it leads them to become victims of other motorists. The riding simulators in the training centers can be useful to demonstrate the proper movement and queuing at junctions. Riding with pillion passenger and excess speed at expressways are found to significantly influence the at at-fault crash involvement of the motorcyclists. Hence the motorcyclists should be advised to concentrate more on riding while riding with pillion passenger and encouraged to avoid excess speed at expressways. Very young and very older group of riders are found to be at-fault than middle aged groups. Hence this group of riders should be targeted for safety improvement. This can be done by arranging safety talks and programs in motorcycling clubs in colleges and universities as well as community riding clubs with high proportion of elderly riders. It is recommended that the driving centers may use the findings of this study to include in licensure program to make motorcyclists more aware of the different factors which expose the motorcyclists to crash risks so that more defensive riding may be needed.

Proactive management of collision risks in port waters using navigational traffic conflicts

Navigational collisions are one of the major safety concerns in many seaports. To address this safety concern, a comprehensive and structured method of collision risk management is necessary. Traditionally management of port water collision risks has been relied on historical collision data. However, this collision-data-based approach is hampered by several shortcomings, such as randomness and rarity of collision occurrence leading to obtaining insufficient number of samples for a sound statistical analysis, insufficiency in explaining collision causation, and reactive approach to safety. A promising alternative approach that overcomes these shortcomings is the navigational traffic conflict technique that uses traffic conflicts as an alternative to the collision data. This paper proposes a collision risk management method by utilizing the principles of this technique. This risk management method allows safety analysts to diagnose safety deficiencies in a proactive manner, which, consequently, has great potential for managing collision risks in a fast, reliable and efficient manner.

HMM triangle relative entropy concepts in sequential change detection applied to vision-based dim target manoeuvre detection

The quick detection of abrupt (unknown) parameter changes in an observed hidden Markov model (HMM) is important in several applications. Motivated by the recent application of relative entropy concepts in the robust sequential change detection problem (and the related model selection problem), this paper proposes a sequential unknown change detection algorithm based on a relative entropy based HMM parameter estimator. Our proposed approach is able to overcome the lack of knowledge of post-change parameters, and is illustrated to have similar performance to the popular cumulative sum (CUSUM) algorithm (which requires knowledge of the post-change parameter values) when examined, on both simulated and real data, in a vision-based aircraft manoeuvre detection problem.

Dealing with unfinished business : preparing pre-service social education teachers for curriculum change

Pre-service teacher education is unfinished business. New social education teachers face the challenge of fluid policy environments in which curriculum content and pedagogy are continually changing. The evolving Australian curriculum is the most recent example of such fluidity with its emphasis on shifting the educational agenda to a focus on discipline-based approaches. This paper addresses the concerns of final year pre-service and early career social education teachers, in terms of their professional development needs, by drawing on the findings of a pilot study with students and recent graduates from a university in south-east Queensland. It concludes that social education curriculum units which embed links to professional practice and professional development in teaching, learning and assessment may provide the way forward for enhancing the transition to practice for beginning teachers and assist them in navigating constant change.

Towards the development of a gas sensor system for monitoring pollutant gases in the low troposphere using small unmanned aerial vehicles

The world is facing problems due to the effects of increased atmospheric pollution, climate change and global warming. Innovative technologies to identify, quantify and assess fluxes exchange of the pollutant gases between the Earth’s surface and atmosphere are required. This paper proposes the development of a gas sensor system for a small UAV to monitor pollutant gases, collect data and geo-locate where the sample was taken. The prototype has two principal systems: a light portable gas sensor and an optional electric–solar powered UAV. The prototype will be suitable to: operate in the lower troposphere (100-500m); collect samples; stamp time and geo-locate each sample. One of the limitations of a small UAV is the limited power available therefore a small and low power consumption payload is designed and built for this research. The specific gases targeted in this research are NO2, mostly produce by traffic, and NH3 from farming, with concentrations above 0.05 ppm and 35 ppm respectively which are harmful to human health. The developed prototype will be a useful tool for scientists to analyse the behaviour and tendencies of pollutant gases producing more realistic models of them.