PubMed · 11250862
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
W Jory. 2001-03-17. Testing night vision for driving.. https://pubmed.ncbi.nlm.nih.gov/11250862/
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
In the context of the European project ROSITA, the Institut of Legal Medicine Homburg/Saar has co-operated with the Saarland traffic police in order to assess different roadside drug tests for their functionality and reliability in traffic controls, and for their analytical force of evidence. In 254 cases within the time period from June 1999 to December 1999, police officers performed a (voluntary) roadside drug testing in saliva/sweat, or urine, to confirm or refute their initial suspicion that a driver had used drugs. Whereas in 45 cases the tests gave negative results (which were confirmed by lab urinalysis), in 209 cases the police officers ordered blood samples after a positive outcome of the tests. In 203 of the 209 positive cases, the results could be confirmed by GC/MS analysis. Regarding the prevalence of used drugs, a single consumption was found in 156 cases (113 cannabis, 38 amphetamines/methamphetamines, three opiates, two cocaine), and a consumption of two drugs was found in 44 cases (34 cannabis+amphetamines/methamphetamines, five cannabis+opiates, three cannabis + cocaine, two cocaine+amphetamines/methamphetamines). In three cases, multi-consumption was found. In six cases, the performed tests gave an incorrect prediction to the police officer at the roadside.The roadside tests gave 97.6% correct assistance to the police officers in the right direction (79.9% correct positive predictions and 17.7% correct negative predictions). As a consequence, the performed tests can be seen as a positive and needful tool for the police to get an immediate response to their initial suspicion and to take the right steps concerning a following legal action.
The aim with this study was to evaluate the accuracy of several on-site testing devices on the market. A part of this study is included in the European Union's (EU's) roadside testing assessment project (ROSITA). An other request for this kind of study came from the Finnish prison department in the Ministry of Justice. The evaluation was performed on both urine assays and oral fluid assays. The on-site test results were compared with laboratory results (gas chromatography-mass spectrometry (GC/MS)). The samples were tested on amphetamines (AMP), cannabinoids (THC), opiates (OPI) and cocaine metabolites (COC). Some of the tests also included a metamphetamine (MET) and a benzodiazepine (BZO) test. Both positive and negative samples were tested. A total of 800 persons and eight on-site devices for urine and two for oral fluid testing were included in this study. Good results were obtained for the urine on-site devices, with accuracies of 93-99% for amphetamines, 97-99% for cannabinoids, 94-98% for opiates and 90-98% for benzodiazepines. However, differences in the ease of performance and interpretation of test result were observed. It was possible to detect amphetamines and opiates in oral fluid by the used on-site devices, but the benzodiazepines and cannabinoids did not fulfil the needs of sensitivity.
We studied the eye movements of a racing driver during high-speed practice to see whether he took in visual information in a different way from a normal driver on a winding road [1, 2]. We found that, when cornering, he spent most of the time looking close to, but not exactly at, the tangent points on the inside edges of the bends. Each bend was treated slightly differently, and there was a highly repeatable pattern to the way the track edge was viewed throughout each bend. We also found a very close relationship between the driver's head direction and the rate of rotation of the car 1 s later. We interpret these observations as indicating that the driver's gaze is not driven directly by tangent point location, as it is in ordinary driving. Instead, we propose that his head direction is driven by the same information that he uses to control steering and speed, namely his knowledge of the track and his racing line round it. If he directs his head at an angle proportional to his estimate of car rotation speed, this will automatically bring his head roughly into line with the tangent points of the bends. From this standardized position, he can use the expected movements of the tangent points in his field of view to verify, and if necessary modify, his racing line during the following second.