Objective: Intersection movement assist (IMA) has been recognized as one of the prominent countermeasures to reduce angle crashes at intersections, which constitute 22% of total crashes in the United States. Utilizing vehicle-based sensors, vehicle-to-vehicle (V2V), and vehicle-to-infrastructure (V2I) communications, IMA offers extended vision to provide early warning for an imminent crash. However, most of IMA-related research implements their methods and strategies only in simulations, test tracks, or driving simulator studies that have quite a few assumptions and limitations and hence the effectiveness evaluations reported may not be transferable or comparable.
Methods: This study seeks to develop a generalized evaluation scheme that can be used not only to assess the effectiveness of IMA on improving traffic safety at intersections but to facilitate comparisons across similar studies. The proposed evaluation scheme utilizes the concepts of traffic conflict in terms of time-to-collision (TTC) as a crash surrogate. This approach avoids the issue of having insufficient crash frequency data for system evaluation. To measure the effectiveness of IMA on reducing traffic conflicts, a relative risk is calculated for comparing the risk of with/without using the IMA. As a proof-of-concept study, this study applied the proposed evaluation scheme and reported the effectiveness of IMA on improving traffic safety in a field operation test (FOT). Seven test scenarios were conducted at 4 intersections, and a total of 40 participants were recruited to use the IMA for 6 months.
Results: It was estimated that IMA users have 26% fewer conflicts with TTC less than 5 s and have 15% fewer conflicts with TTC less than 4 s. However, the results vary across different sites and different definitions of conflicts in terms of TTC.
Conclusions: Overall, IMA is promising to effectively reduce angle crashes related to sight obstruction and has potential to reduce not only crash frequency but crash severity. 相似文献
Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies. 相似文献
Mercury concentrations have been analysed in bream (Abramis brama L.) and zebra mussels (Dreissena polymorpha) collected at 17 freshwater sites in Germany from 1993-2009 and 1994-2009, respectively, within the German Environmental Specimen programme. Mercury concentrations in bream ranged from 21 to 881 ng g−1 wet weight with lowest concentrations found at the reference site Lake Belau and highest in fish from the river Elbe and its tributaries. Statistical analysis revealed site-specific differences and significant decreasing temporal trends in mercury concentrations at most of the sampling sites. The decrease in mercury levels in bream was most pronounced in fish from the river Elbe and its tributary Mulde, while in fish from the river Saale mercury levels increased. Temporal trends seem to level off in recent years. Mercury concentrations in zebra mussels were much lower than those in bream according to their lower trophic position and varied by one order of magnitude from 4.1 to 42 ng g−1 wet weight (33-336 ng g−1 dry weight). For zebra mussels, trend analyses were performed for seven sampling sites at the rivers Saar and Elbe of which three showed significant downward trends. There was a significant correlation of the geometric mean concentrations in bream and zebra mussel over the entire study period at each sampling site (Pearson’s correlation coefficient = 0.892, p = 0.00002). A comparison of the concentrations in bream with the environmental quality standard (EQS) of 20 ng g−1 wet weight set for mercury in biota by the EU showed that not a single result was in compliance with this limit value, not even those from the reference site. Current mercury levels in bream from German rivers exceed the EQS by a factor 4.5-20. Thus, piscivorous top predators are still at risk of secondary poisoning by mercury exposure via the food chain. It was suggested focusing monitoring of mercury in forage fish (trophic level 3 or 4) for compliance checking with the EQS for biota and considering the age dependency of mercury concentrations in fish in the monitoring strategy. 相似文献