INFLUENCE OF ROAD SURFACES ON THE CALCULATION OF A TARGET VISIBILITY TAKING INTO ACCOUNT THE DIRECT AND INDIRECT LIGHTING

Street lighting ensures visibility and legibility for road users. In this paper, performances of the lighting installation of four road sections with different type of road surface are simulated in accordance with guidelines and road lighting standards. Then, the calculation of the visibility level of a target according to the Adrian’s model is included. Next, the light reflections on the road surface are added to the calculation of the target luminance. For this, the area considered in front of the target as well as the number of elementary surfaces are fixed and a Q_0-scaling of the r-table obtained for α=45° is performed. We compare the results obtained for each section with and without considering the light reflections and conclude that there is negligible incidence of the nature of the road surface on the target luminance. However, an effect of the road surface on the visibility level of the target is observed.

Design of Driving Waveform Based on Overdriving Voltage for Shortening Response Time in Electrowetting Displays

A fast response speed of a pixel is important for electrowetting displays (EWDs). However, traditional driving waveforms of EWDs have the disadvantage of long response time. So, a driving waveform, which based on overdriving voltages and charge trapping theory, was proposed in this paper to shorten the response time of EWDs. The driving waveform was composed of an overdriving stage and a driving stage. Firstly, a simplified physical model was introduced to analyze the influence of driving voltages on the response time. Then, an overdriving voltage was applied in the overdriving stage to increase the respond speed of oil, and a target voltage was applied in the driving stage to obtain a target luminance. In addition, the effect of different overdriving voltages and overdriving time values on the response time was analyzed by charge trapping theory to achieve an optimal performance. Finally, the driving waveform was imported into an EWD for performance testing. Experimental results showed that the response time of the EWD can be shortened by 29.27% compared with a PWM driving waveform.

A Driving System for Fast and Precise Gray-Scale Response Based on Amplitude–Frequency Mixed Modulation in TFT Electrowetting Displays

The gray-scale display which is driven by PWM (pulse width modulation) in TFT (thin film transistor) electrowetting displays (EWDs) has some shortcomings, such as large amplitude of oil oscillation in pixels and slow response speed for displaying gray scale. In this paper, an amplitude–frequency mixed modulation driving system is proposed to improve the response speed of driving gray scale and enhance the oil stability when the gray scale is displayed. In the initial stage of the driving process, the oil is driven by a high voltage to close to the target luminance, and the driving voltage is then decreased to stabilize the oil. The electrowetting hysteresis curve was used to calculate the relation model between the driving voltage and the luminance of the pixel in the system, and the driving voltage value of the pixel at each driving stage was then set to make the oil precisely and rapidly stabilize at the target luminance value. In the output driving platform, the amplitude–frequency mixed modulation is realized based on the source IC, which was used to realize digital-to-analog conversion. An 8 inch EWD was tested using an Admesy colorimeter, and the experimental results show that the pixel response time is reduced by 70% and the gray-scale oscillation is reduced by 80%.

Discriminating between anticipatory and visually triggered saccades: measuring minimal visual saccadic response time using luminance

We describe a novel behavioral method to accurately discriminate anticipatory (i.e., saccades not generated by visual input) from visually triggered saccades and to identify the minimal visual saccadic reaction time (SRT). This method can be used to calculate a feasible lower bound cutoff for latencies of visually triggered saccades within a certain experimental context or participant group. We apply this method to compute the minimal visual SRT for two different saccade target luminance levels. Three main findings are presented: 1) the minimal visual SRT for all participants was 46 ms shorter for bright targets than for dim targets, 2) the transition from non-visually triggered to visually triggered saccades occurred abruptly, independent of target luminance, and 3) although the absolute minimal visual SRTs varied between participants, the response pattern (response to bright targets being faster than to dim targets) was consistent across participants. These results are consistent with variability in saccadic and neural responses to luminance as has been reported in monkeys. On the basis of these results, we argue that differences in the minimal visual SRT can easily occur when stimuli vary in luminance or other saliency features. Applying an absolute cutoff (i.e., 70–90 ms) that approaches the minimal neuronal conduction delays, which is general practice in many laboratories, may result in the wrongful inclusion of saccades that are not visually triggered. It is suggested to assess the lower SRT bound for visually triggered saccades when piloting an experimental setup and before including saccades based on particular latency criteria. NEW & NOTEWORTHY We successfully developed an anticipation paradigm to discriminate between anticipatory and visually triggered saccades by measuring the minimal visual saccadic response time (SRT). We show that the 70- to 90-ms lower bound cutoff for visually triggered saccades should be applied in a flexible way and that the transitional interval is very short. The paradigm can be employed to investigate the effects of different stimulus features, experimental conditions, and participant groups on the minimal visual SRT in humans.

Linking express saccade occurance to stimulus properties and sensorimotor integration in the superior colliculus

Express saccades represent the fastest possible eye movements to visual targets with reaction times that approach minimum sensory-motor conduction delays. Previous work in monkeys has identified two specific neural signals in the superior colliculus (SC: a midbrain sensorimotor integration structure involved in gaze control) that are required to execute express saccades: 1) previsual activity consisting of a low-frequency increase in action potentials in sensory-motor neurons immediately before the arrival of a visual response; and 2) a transient visual-sensory response consisting of a high-frequency burst of action potentials in visually responsive neurons resulting from the appearance of a visual target stimulus. To better understand how these two neural signals interact to produce express saccades, we manipulated the arrival time and magnitude of visual responses in the SC by altering target luminance and we examined the corresponding influences on SC activity and express saccade generation. We recorded from saccade neurons with visual-, motor-, and previsual-related activity in the SC of monkeys performing the gap saccade task while target luminance was systematically varied between 0.001 and 42.5 cd/m2 against a black background (∼0.0001 cd/m2). Our results demonstrated that 1) express saccade latencies were linked directly to the arrival time in the SC of visual responses produced by abruptly appearing visual stimuli; 2) express saccades were generated toward both dim and bright targets whenever sufficient previsual activity was present; and 3) target luminance altered the likelihood of producing an express saccade. When an express saccade was generated, visuomotor neurons increased their activity immediately before the arrival of the visual response in the SC and saccade initiation. Furthermore, the visual and motor responses of visuomotor neurons merged into a single burst of action potentials, while the visual response of visual-only neurons was unaffected. A linear combination model was used to test which SC signals best predicted the likelihood of producing an express saccade. In addition to visual response magnitude and previsual activity of saccade neurons, the model identified presaccadic activity (activity occurring during the 30-ms epoch immediately before saccade initiation) as a third important signal for predicting express saccades. We conclude that express saccades can be predicted by visual, previsual, and presaccadic signals recorded from visuomotor neurons in the intermediate layers of the SC.