Road conditions are a critical issue for road users as, if not given sufficient attention, they may threaten users’ lives. The environmental parameters, such as snowy, icy, dry and wet, are important in relation to the condition of roads. This is particularly true in relation to the northern regions and greatest concern should be in relation to snowy and icy situations. In this thesis, a system based on an InGaAs area scan sensor utilizes NIR technology to detect water or ice on the road so as to enable drivers to avoid slippery road conditions. The conditions caused by freezing water on road surface are particularly dangerous and are not easy to observe and it is hope that this project will boost traffic safety. The system is able to assist road maintenance personnel in forecasting and detecting slippery road conditions during winter road maintenance (WRM). The system, which is based on FPGA, has functionalities that display the captured images on an HDMI monitor and send the images to the software on a host PC via the UART protocol. An interface board, which carries the sensor and which connects to the FPGA board, is developed for NIR sensor. VHDL implementation and PC software design are the works included in the project. Besides, this device is exploited utilizing InGaAs image sensor. According to its features, it can be applied in other applications which will also be discussed. Finally, experiments are conducted in order to investigate the system’s operation with the variation of temperature.

To provide an adequate level of safety at grade crossings, Transport Canada has allocated several millions annually to prevent collisions at grade crossings through the implementation of countermeasures, such as train-actuated warning devices and track devices. Railway companies and provincial agencies have also provided additional support to improve safety at highway-railway grade crossings. One of technical challenges in estimating safety effect of countermeasures at highway-railway grade crossing is an extremely rare occurrence of collisions. Given that the collision process is random with significant variation over time and space, it is hard to judge whether a specific crossing is safe or safer than other crossings solely based on the number of collisions in a given year. Decision makers are also required to make difficult decisions on safety investment accounting for uncertainty in effectiveness of countermeasures. The level of uncertainty is even higher when there is lack of observed collision data before and after the implementation of specific countermeasures. This study proposes a Bayesian data fusion method which overcomes these limitations. In this method, we used previous research findings on the effect of a given countermeasure, which could vary by jurisdictions and operating conditions, to obtain a priori inference on its expected effects. We then used locally calibrated models, which are valid for a specific jurisdiction, to provide better estimates of the countermeasure effects. Within a Bayesian framework, these two sources were integrated to obtain the posterior distribution of the countermeasure effect. The outputs provided not only the expected collision response to a specific countermeasure, but also its variance and corresponding probability distribution for a range of likely values. Some numerical examples using Canadian highway-railway grade crossing data illustrate how the proposed method can be used to predict the effects of prior knowledge and data likelihood on the estimates of countermeasure effects.

<p>Road traffic safety has increasingly become in need of educated road safety professionals, as the number of accidents in the World Health Organization member countries exceeds one million. The profession itself is transitioning from experience based decision making to empirical, theoretical and mathematical based solutions. However, road traffic safety is a multidiscipline, crossing over many fields and requiring a high degree of communication between different institutions. There are very few institutions that provide programs in the field; furthermore, they employ traditional lecture-based teaching methods. The traditional teaching environment does not fulfill the educational needs of future traffic safety professionals due to its rigidity and lack of problem solving exercises.</p><p>An alternative method, namely problem based learning, is recommended as an alternative teaching method in this paper. The thesis is constructed in such a way as to develop a complete road traffic safety educational module at graduate and post graduate level.</p><p>The theoretical basis on which a road traffic safety module is later built is presented in the first part of the thesis. Major concepts in road traffic safety, as well as problem based learning methods are investigated. In addition, a literature review SWOT analysis based on literature is conducted.The module development consists of establishing the road traffic safety learning goals for each segment in the module, appropriate assessment criteria and group work format. The module contains gradual difficulty level problems, starting from the easiest topic and easiest format (closed ended problem) and ending with the hardest topic and hardest format (open ended problem).</p><p>The last section employs the SWOT analysis findings in the theoretical section to develop a SWOT analysis of the road traffic safety module presented in the thesis.</p>

Thesis (M.S.C.E.)--University of Central Florida, 2009. / Adviser: Mohamed Abdel-Aty. Includes bibliographical references (p. 155-159).

To research the interaction between the elements of the traffic safety system “Traffic Participant – Vehicle – Road (Traffic Environment)” and the influencing factors, and to provide recommendations for the improvement of traffic safety in Lithuania. The following main problems were solved in the research: • to research the models applied for the analysis of traffic safety system; • to identify the key factors influencing the traffic safety system reliability; • to perform reaction tests of traffic participants, during which the driver’s reaction time in usual situations and in potentially dangerous or unforeseen situations is identified, i.e. while talking on a mobile phone, distractions, headlight dazzle at night, and other situations; • based on mathematical calculation methods and the tests performed, to identify the factors influencing the driver’s reaction time; • based on traffic accident data on certain main roads and by applying statistical mathematical packages, to identify the factors affecting the number of traffic accidents; • after analyzing the factors affecting the traffic safety system, to formulate substantiated trends for the improvement of traffic safety and to implement that traffic safety improvement means for these trends; • to assess the efficiency of traffic safety improvement means.

No description available.

No description available.

Thesis (Ph. D.)--Ohio University, June, 2003. / Title from PDF t.p. Includes bibliographical references (leaves 101-105).

Thesis (M.S.)--University of Wyoming, 2007. / Title from PDF title page (viewed on Nov. 6, 2008). Includes bibliographical references (p. 155-157).

Thesis (Ph.D.) - University of Glasgow, 2007. / Ph.D. thesis submitted the Faculty of Information and Mathematical Sciences, Department of Computing Science. Includes bibliographical references. Print version also available.