Study on the Traffic Safety Intelligent Warning Technologies and Methods Based on the Integrated Traffic Safety Data

Author(s):  
Yin Zhu
Keyword(s):  
2011 ◽  
Vol 26 (S2) ◽  
pp. 194-194
Author(s):  
A. Brunnauer ◽  
F. Segmiller ◽  
I. Hermisson ◽  
F. Seemüller ◽  
M. Riedel ◽  
...  

ObjectivesDriving is a daily activity for most people in developed countries and is important in maintaining independence. Bipolar patients may have an impaired driving behavior because of the pathology itself, with psychomotor and cognitive disturbances. Additionally, adverse effects of pharmacologic treatment may be detrimental.Methods24 remitted bipolar outpatients diagnosed according to ICD-10 criteria were enrolled in the study, receiving either lithium (n = 12) or lamotrigine (n = 12). Participants were investigated under steady state plasma level conditions. According to the German Guidelines for road and traffic safety data were collected with the Wiener Testsystem (WTS) measuring visual perception, reactivity, stress tolerance, concentration and vigilance.Psychopathologic symptoms were rated with the Montgomery-Asberg Depression Rating Scale (MADRS) and the Young Mania Rating Scale - Clinician rated (YMRS-C).ResultsAbout 40% of patients were without clinically relevant psychomotor disturbances. In 40% of cases mild to moderate impairments could be seen, and 20% of the patients were considered as severely impaired. Data show that patients under lamotrigine had an altogether better test performance than patients treated with lithium. Especially in visual perception and stress tolerance differences were most pronounced.ConclusionsAbout 20% of remitted bipolar outpatients treated with lithium or lamotrigine must be considered unfit to drive. In 40% of the cases it seems justified to counsel patients individually, taking into account compensational factors. Analysis of our data point to an advantage for bipolar patients treated with lamotrigine when compared with lithium. However causal relationships can not be drawn from our data.


2020 ◽  
Vol 70 (6) ◽  
pp. 59-64
Author(s):  
Péter Holló

Az egyik legfontosabb közlekedésbiztonsági teljesítménymutató a biztonságiöv-viselési arány. A hazai értékek alakulása és elemzése, más országokhoz történő viszonyítása fontos információkkal szolgál. Az írás a biztonságiöv-viselési arány hazai értékeinek alakulását elemzi más országokhoz képest. Erre az IRTAD (International Traffic Safety Data and Analysis Group), az OECD tagországok közúti forgalmi és baleseti adatbankja ad lehetőséget, ugyanis ez az útkategóriák szerint tartalmazza a személygépkocsik különböző ülésein megfigyelt biztonságiöv-viselési arányokat.


Author(s):  
H H de Jong ◽  
F Preti ◽  
G W H van Es

This paper outlines a proposal for a framework of indicators developed with the aim to improve European safety performance monitoring of Air Navigation Services. The extension of scope from the usual choice of Air Traffic Management to Air Navigation Services has been made to address the complication that Air Traffic Management is a different service from Communication, Navigation, and Surveillance, but intimately connected with it. The framework considers the potential influence of Air Navigation Services on air traffic safety, and it uses accidents, their causal/contributing factors, and incidents related to these services as source data for the indicators. Those occurrence categories are considered for which Air Navigation Services have the potential to improve risk. This approach is independent of the notion of a service's contribution to occurrences, which is normally used, but which suffers from a considerable degree of subjectivity. In the data flows from air traffic operations to safety performance indicators, weak links are human incident reporting, varying proportions of incidents actually investigated sufficiently well plus different ways to perform the investigations, and differences in interpretation in providing overviews of the resulting safety data on the level of States. In view of these weaknesses, conditions are developed to prevent data of insufficient quality from being used. The paper mentions a number of aspects to consider when using the indicators. Before drawing conclusions, statistical significance and the existence of reporting bias need to be assessed. The paper finishes with a discussion of the relation of the framework with existing targets and indicates how the framework could support deriving appropriate targets and performance of safety assessments.


Author(s):  
Jun Liu ◽  
Asad J. Khattak ◽  
Cong Chen ◽  
Dan Wan ◽  
Jiaqi Ma ◽  
...  

Hit-and-run crashes often delay emergency response and may result in increasing/secondary harms/damages to the victims in the crash. This study revisited hit-and-run crashes using a geo-spatial modeling approach, specifically, Geographically Weighted Regression (GWR), to explore geo-referenced crash data. The data cover motor vehicle crashes ( N = 138,529) in Southeast Michigan including 20,813 hit-and-run crashes in 2015. This study presented the results from both traditional regression and GWR models. GWR model results can be mapped in space, and the maps offer visual insights about the spatially varying correlates of hit-and-run crashes that are not available from previous studies. Results from traditional binary logit model are generally consistent with findings in previous studies. For example, hit-and-run is more likely to occur on weekends or during nighttime (especially without street lights on). Driving under impairment (DUI) seems to increase the likelihood of hit-and-run. GWR models also uncovered spatially varying correlates of hit-and-run. For example, DUI crashes in the northwest of the Detroit metropolitan area are associated with an even greater hit-and-run likelihood than those in other parts in this area. In addition, the local socio-economic factors are included in the analysis. Results show that hit-and-run is more likely to occur in census tracts with a higher unemployment rate, a lower household income, a smaller portion of college-educated population, and a greater population density. The study demonstrates a way of making sense of geo-referenced traffic safety data. The geo-spatial modeling method is useful for prioritizing specific geographic regions/corridors for safety improvement countermeasures, and outperforms traditional modeling techniques.


2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Ying Chen ◽  
Zhongxiang Huang

Inclement weather affects traffic safety in various ways. Crashes on rainy days not only cause fatalities and injuries but also significantly increase travel time. Accurately predicting crash risk under inclement weather conditions is helpful and informative to both roadway agencies and roadway users. Safety researchers have proposed various analytic methods to predict crashes. However, most of them require complete roadway inventory, traffic, and crash data. Data incompleteness is a challenge in many developing countries. It is common that safety researchers only have access to data on sites where a crash has occurred (i.e., zero-truncated data). The conventional crash models are not applicable to zero-truncated safety data. This paper proposes a finite-mixture zero-truncated negative binomial (FMZTNB) model structure. The model is applied to three-year wet-road crash data on 395 divided roadway segments (total 586 km), and the parameters are estimated using the Markov chain Monte Carlo (MCMC) method. Comparison indicates that the proposed FMZTNB model has better fitting performance and is more accurate in predicting the number of wet-road crashes. The model is capable of capturing the heterogeneity within the sample crash data. In addition, lane width showed mixed effects in different components on wet-road crashes, which are not observed in conventional modeling approaches. Practitioners are encouraged to consider the finite-mixture zero-truncated modeling approach when complete safety dataset is not available.


1970 ◽  
Vol 25 (2) ◽  
pp. 169-176
Author(s):  
Slađana Janković ◽  
Snežana Mladenović ◽  
Krsto Lipovac ◽  
Dušan Mladenović ◽  
Slavko Vesković

One class of methods for black spots identification is based on the analysis of: traffic accidents (TA), road parameters, and traffic intensity. The data used in the analysis can be grouped into the information about: roads, persons participating in TA, vehicles participating in TA, traffic accidents and their consequences, and traffic. These categories of data are usually under the jurisdiction of different traffic and non-traffic subjects. Therefore, it is necessary to exchange traffic safety data among the following sources: traffic police, road manager, and health and judicial sector. This paper proposes a model for the exchange and integration of traffic safety data into a single database, which allows the calculation of risks for road sections, as well as the classification and ranking of the sections. The model is based on B2B integration of service-oriented applications. This paper describes a practical example that demonstrates the proposed integration model.


2012 ◽  
Author(s):  
Christopher Monsere ◽  
◽  
Myenwoo Lim ◽  
Chengxin Dai ◽  
Xiaowei Wu ◽  
...  

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