Field effectiveness evaluation of advanced driver assistance systems

Abstract

Objective: Advanced driver assistance systems (ADAS) are a class of vehicle technologies designed to increase safety by providing drivers with timely warnings and autonomously intervening to avoid hazardous situations. Though laboratory testing suggests that ADAS technologies will greatly impact crash involvement rates, real-world evidence that characterizes their effectiveness is still limited. This study evaluates and quantifies the association of ADAS technologies with the likelihood of a moderate or severe crash for new-model BMWs in the United States.

Methods: Vehicle ADAS option information for the cohort of model year 2014 and later BMW passenger vehicles sold after January 1, 2014 (n?=?1,063,503), was coded using VIN-identified options data. ADAS technologies of interest include frontal collision warning with autonomous emergency braking, lane departure warning, and blind spot detection. BMW Automated Crash Notification system data (from January 2014 to November 2017) were merged with vehicle data by VIN to identify crashed vehicles (n?=?15,507), including date, crash severity (delta V), and area of impact. Using Cox proportional hazards regression modeling, the study calculates the adjusted hazard ratio for crashing among BMW passenger vehicles with versus without ADAS technologies. The adjusted percentage reduction in moderate and severe crashes associated with ADAS is interpreted as one minus the hazard ratio.

Results: Vehicles equipped with both autonomous emergency braking and lane departure warning were 23% less likely to crash than those not equipped (hazard ratio [HR]?=?0.77; 95% confidence interval [CI], 0.73–0.81), controlling for model year, vehicle size and body type. Autonomous emergency braking and lane departure warning generally occur together, making it difficult to tease apart their individual effects. Blind spot detection was associated with a 14% reduction in crashes after controlling for the presence of autonomous emergency braking and lane departure warning (HR =0.86; 95% CI, 0.744–0.99). Differences were observed by vehicle type and crash type. The combined effect of autonomous emergency braking and lane departure warning was greater in newer model vehicles: Equipped vehicles were 13% less likely to crash (HR =0.87; 95% CI, 0.79–0.95) among 2014 model year vehicles versus 34% less likely to crash (HR =0.66; 95% CI, 0.57–0.77) among 2017 model year vehicles.

Conclusion: This robust cohort study contributes to the growing evidence on the effectiveness of ADAS technologies.     

Use of native mosses as biomonitors of heavy metals and nitrogen deposition in the surroundings of two steel works

A biomonitoring survey using the moss species Hypnum cupressiforme Hedw. was conducted in the surroundings of two steel plants located in the North of Spain. Levels of V, Cr, Ni, Cu, Zn, As, Cd, Hg, Pb and N were determined. Very high concentrations in the areas of study were detected when compared to nearby unaffected regions. Similar trends were observed for all the elements in the differently orientated transects, showing an appreciable influence of the NW prevailing winds of the region in the dispersion of pollutants, as well as a clear decreasing gradient in the concentrations of metals in mosses within a distance of 1500 meters from the facilities. A differentiation between the elements emitted by the chimney as result of the industrial activity (V, Cr, Ni, Cu and As) and those with a high presence in steel slag deposits (Zn, Cd, Hg and Pb) was observed. The range of contamination was also established by means of the Contamination Factor, indicating a category 4 out of 6 categories, which shows the high levels reported in the areas of study. A different dynamic was registered for nitrogen regarding the rest of the heavy metals analysed except for Hg, probably due to the elevated volatility and mobility of both elements, as well as their high persistence in the atmosphere.     

Use of Animal Species Data in Environmental Impact Assessments

Environmental Impact Assessments (EIAs) should ideally help minimize adverse effects on biological diversity by considering impacts of projects on wide ranges of species. This paper investigates how recent Dutch EIAs included the species comprising animal diversity. We present results of two studies on fauna data used in the EIAs. Objectives were to determine for different taxa (a) the relative representation of species in Environmental Impact Statements (EISs); (b) the extent to which EISs referred to specific species and the accuracy of survey data referred to; and (c) apparent roles of different EIA actors in species inclusion. EIAs were found to use data on various taxa but on limited numbers of species. The frequency with which taxa were included varied significantly. Birds were most frequently included, followed by mammals, amphibians, and other species groups. The quality of data on birds exceeded that regarding other vertebrates. Our results indicate that (a) EIA working groups of independent experts were the most influential in determining the data to be used; (b) on average, proponents included data more often than required by guidelines; and (c) in 30 to 40% of the EIAs, the participation of nongovernmental organizations prompted use of data. Despite the key role of experts in data inclusion, the taxon rankings found in the EIAs showed little deviation from those observed in studies on people’s preferences for species. Given the limited ranges of species considered, it is doubtful that the EIAs examined effectively contributed to conserving animal species diversity. Edo Knegtering produced this work in his personal capacity     

The development and application of remote sensing to monitor sand dune habitats

Sand dunes are complex systems that contain several habitats, often as mosaics or transitions between types. Several of these habitats are afforded protection under European Legislation and in the UK nationally within Special Areas of Conservation (SAC) and Sites of Special Scientific Interest (SSSI). Natural England has a statutory duty to report to Europe on the conservation status and condition of sand dunes; and is required to report to the UK Government on designated sites. To achieve this we have sought ways of capturing, analysing and interpreting data on the extent and location of sand dune habitats. This requires an ability to be able to obtain data over large areas of coastline in an efficient way. Natural England and Environment Agency Geomatics have worked collaboratively for over 16 years, sharing data and ecological knowledge. In 2012 work started to evaluate the use of remote sensing to map UK BAP and Annex I sand dune habitats. A methodology has now been developed and tested to map sand dune habitats. The key objective was to provide an operational tool that will help to map these habitats and understand change on sites around England. This has been achieved through analysis of LIDAR and Compact Airborne Spectrographic Imager (CASI) data using Object Orientated Image Analysis. Quality Control (QC) and accuracy assessments have shown this approach to be successful and 11 sites have been mapped to date. These techniques are providing a new approach to monitoring change in coastal vegetation communities and informing management of protected sites.     

Removal of PCBs from a Contaminated Soil Using CF-Systems® Solvent Extraction Process

ABSTRACT

The U.S. Environmental Protection Agency’s (EPA) Superfund Technical Assistance Response Team (START) in cooperation with EPA’s Superfund Innovative Technology Evaluation (SITE) program evaluated a pilot scale solvent extraction process developed by CF-Systems. This process uses liquefied propane to extract organic contaminants from soils, sludges, and sediments. A pilot-scale evaluation was conducted in Golden, CO at Hazen Research, Inc., using CF-Systems’ trailer-mounted organics extraction unit. Approximately 1,000 pounds of soil, with an average poly-chlorinated biphenyl (PCB) concentration of 260 mg/kg, was obtained from a remote Superfund site. Six 100-pound batches of the contaminated soil were extracted using multiple extraction sequences. Three of the six batch runs were subjected to three extraction sequences each, so that process variability could be evaluated. Results showed that PCB removal efficiencies varied between 91.4 and 99.4%, with the propane-extracted soils retaining low concentrations of PCBs (19.0–1.8 mg/kg). Removal efficiencies of oil and grease (O&G) were found to be 96.0 to 99.6% with propane-extracted soils retaining O&G concentrations from 279 to <20 mg/kg. Overall extraction efficiency was found to be dependant upon the numberof extraction cycles used.