5.2 GHz variable-gain amplifier and power amplifier driver for WLAN IEEE 802.11a transmitter front-end

A 5.2 GHz variable-gain amplifier (VGA) and a power amplifier (PA) driver are designed for WLAN IEEE 802.11a monolithic RFIC. The VGA and the PA driver are implemented in a 50 GHz 0.35 μm SiGe BiCMOS technology and occupy 1.12×1.25 mm~2 die area. The VGA with effective temperature compensation is controlled by 5 bits and has a gain range of 34 dB. The PA driver with tuned loads utilizes a differential input, single-ended output topology, and the tuned loads resonate at 5.2 GHz. The maximum overall gain of the VGA and the PA driver is 29 dB with the output third-order intercept point (OIP3) of 11 dBm. The gain drift over the temperature varying from -30 to 85℃ converges within±3 dB. The total current consumption is 45 mA under a 2.85 V power supply.

Driver response in active advanced warning signs at high-speed signalized intersections. Final report.

Federal Highway Administration, Washington, D.C.

Operator's manual : grinding kit, valve seat, electric, 35 degree angle, concentric drive, driver, AC/DC, 115-volt, 7,500 RPM rated no load speed (Albertson and Company model 1712-M) (4910-060-9983).

"June 1965."

How do other people influence your driving speed? Exploring the 'who' and the 'how' of social influences on speeding from a qualitative perspective

Using only legal sanctions to manage the speed at which people drive ignores the potential benefits of harnessing social factors such as the influence of others. Social influences on driver speeds were explored in this qualitative examination of 67 Australian drivers. Focus group interviews with 8 driver types (young, mid-age and older males and females, and self-identified Excessive and Rare speeders) were guided by Akers’ social learning theory (Akers, 1998). Findings revealed two types of influential others: people known to the driver (passengers and parents), and unknown other drivers. Passengers were generally described as having a slowing influence on drivers: responsibility for the safety of people in the car and consideration for passenger comfort were key themes. In contrast, all but the Rare speeders reported increasing their speed when driving alone. Parental role modelling was also described. In relation to other drivers, key themes included speeding to keep up with traffic flow and perceived pressure to drive faster. This ‘pressure’ from others to ‘speed up’ was expressed in all groups and reported strategies for managing this varied. Encouragingly, examples of actual or anticipated social rewards for speeding were less common than examples of social punishments. Three main themes relating to social punishments were embarrassment, breaching the trust of others, and presenting an image of a responsible driver. Impression management and self-presentation are discussed in light of these findings. Overall, our findings indicate scope to exploit the use of social sanctions for speeding and social praise for speed limit compliance to enhance speed management strategies.

Empirical measurement of the Enright phenomenon, a distortion of perceived driving speed

Purpose: In 1970, Enright observed a distortion of perceived driving speed, induced by monocular application of a neutral density (ND) filter. If a driver looks out of the right side of a vehicle with a filter over the right eye, the driver perceives a reduction of the vehicle’s apparent velocity, while applying a ND filter over the left eye increases the vehicle’s apparent velocity. The purpose of the current study was to provide the first empirical measurements of the Enright phenomenon. Methods: Ten experienced drivers were tested and drove an automatic sedan on a closed road circuit. Filters (0.9 ND) were placed over the left, right or both eyes during a driving run, in addition to a control condition with no filters in place. Subjects were asked to look out of the right side of the car and adjust their driving speed to either 40 km/h or 60 km/h. Results: Without a filter or with both eyes filtered subjects showed good estimation of speed when asked to travel at 60 km/h but travelled a mean of 12 to 14 km/h faster than the requested 40 km/h. Subjects travelled faster than these baselines by a mean of 7 to 9 km/h (p < 0.001) with the filter over their right eye, and 3 to 5 km/h slower with the filter over their left eye (p < 0.05). Conclusions: The Enright phenomenon causes significant and measurable distortions of perceived driving speed under realworld driving conditions.

Driver behaviour and decision making at railway level crossings : An exploratory on-road case study

Crashes at rail level crossings represent a significant problem, both in Australia and worldwide. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles, now provide researchers with the opportunity to further understand driver behaviour at rail level crossings in ways not previously possible. This paper gives an overview of a recent on-road pilot study of driver behaviour at rail level crossings in which 25 participants drove a pre-determined route, incorporating 4 rail level crossings, using MUARC's instrumented On-Road Test Vehicle (ORTeV). Drivers provided verbal commentary whilst driving the route, and a range of other data were collected, including eye fixations, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. Extracts from the wider analyses are used to examine in depth driver behaviour at one of the rail level crossings encountered during the study. The analysis presented, along with the overall analysis undertaken, gives insight into the driver and wider systems factors that shape behaviour at rail level crossings, and highlights the utility of using a multi-method, instrumented vehicle approach for gathering data regarding driver behaviour in different contexts.

Comprehensive evaluation of driver gaze pattern using fuzzy rules for driver training

The over representation of novice drivers in crashes is alarming. Research indicates that one in five drivers’ crashes within their first year of driving. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the drive. This paper presents a system that evaluates the data stream acquired from multiple in-vehicle sensors (acquired from Driver Vehicle Environment-DVE) using fuzzy rules and classifies the driving manoeuvres (i.e. overtake, lane change and turn) as low risk or high risk. The fuzzy rules use parameters such as following distance, frequency of mirror checks, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvre to assess risk. The fuzzy rules to estimate risk are designed after analysing the selected driving manoeuvres performed by driver trainers. This paper focuses mainly on the difference in gaze pattern for experienced and novice drivers during the selected manoeuvres. Using this system, trainers of novice drivers would be able to empirically evaluate and give feedback to the novice drivers regarding their driving behaviour.

To err (on the road) is human? An on-road study of driver errors

Human error, its causes and consequences, and the ways in which it can be prevented, remain of great interest to road safety practitioners. This paper presents the findings derived from an on-road study of driver errors in which 25 participants drove a pre-determined route using MUARC's On-Road Test Vehicle (ORTeV). In-vehicle observers recorded the different errors made, and a range of other data was collected, including driver verbal protocols, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. The drivers tested made a range of different errors, with speeding violations, both intentional and unintentional, being the most common. Further more detailed analysis of a sub-set of specific error types indicates that driver errors have various causes, including failures in the wider road 'system' such as poor roadway design, infrastructure failures and unclear road rules. In closing, a range of potential error prevention strategies, including intelligent speed adaptation and road infrastructure design, are discussed.

Are you a mindful driver? A review of the potential explanatory value of mindfulness in predicting speeding behaviour

Mindfulness is a concept which has been widely used in studies on consciousness, but has recently been applied to the understanding of behaviours in other areas, including clinical psychology, meditation, physical activity, education and business. It has been suggested that mindfulness can also be applied to road safety, though this has not yet been researched. A standard definition of mindfulness is “paying attention in a particular way, on purpose in the present moment and non-judgemental to the unfolding of experience moment by moment” [1]. Scales have been developed to measure mindfulness; however, there are different views in the literature on the nature of the mindfulness construct. This paper reviews the issues raised in the literature and arrives at an operational definition of mindfulness considered relevant to road safety. It is further proposed that mindfulness is best construed as operating together with other psychosocial factors to influence road safety behaviours. The specific case of speeding behaviour is outlined, where the psychosocial variables in the Theory of Planned Behaviour (TPB) have been demonstrated to predict both intention to speed and actual speeding behaviour. A role is proposed for mindfulness in enhancing the explanatory and predictive powers of the TPB concerning speeding. The implications of mindfulness for speeding countermeasures are discussed and a program of future research is outlined.

Microscopic modelling of freeway operations

Freeways are divided roadways designed to facilitate the uninterrupted movement of motor vehicles. However, many freeways now experience demand flows in excess of capacity, leading to recurrent congestion. The Highway Capacity Manual (TRB, 1994) uses empirical macroscopic relationships between speed, flow and density to quantify freeway operations and performance. Capacity may be predicted as the maximum uncongested flow achievable. Although they are effective tools for design and analysis, macroscopic models lack an understanding of the nature of processes taking place in the system. Szwed and Smith (1972, 1974) and Makigami and Matsuo (1990) have shown that microscopic modelling is also applicable to freeway operations. Such models facilitate an understanding of the processes whilst providing for the assessment of performance, through measures of capacity and delay. However, these models are limited to only a few circumstances. The aim of this study was to produce more comprehensive and practical microscopic models. These models were required to accurately portray the mechanisms of freeway operations at the specific locations under consideration. The models needed to be able to be calibrated using data acquired at these locations. The output of the models needed to be able to be validated with data acquired at these sites. Therefore, the outputs should be truly descriptive of the performance of the facility. A theoretical basis needed to underlie the form of these models, rather than empiricism, which is the case for the macroscopic models currently used. And the models needed to be adaptable to variable operating conditions, so that they may be applied, where possible, to other similar systems and facilities. It was not possible to produce a stand-alone model which is applicable to all facilities and locations, in this single study, however the scene has been set for the application of the models to a much broader range of operating conditions. Opportunities for further development of the models were identified, and procedures provided for the calibration and validation of the models to a wide range of conditions. The models developed, do however, have limitations in their applicability. Only uncongested operations were studied and represented. Driver behaviour in Brisbane was applied to the models. Different mechanisms are likely in other locations due to variability in road rules and driving cultures. Not all manoeuvres evident were modelled. Some unusual manoeuvres were considered unwarranted to model. However the models developed contain the principal processes of freeway operations, merging and lane changing. Gap acceptance theory was applied to these critical operations to assess freeway performance. Gap acceptance theory was found to be applicable to merging, however the major stream, the kerb lane traffic, exercises only a limited priority over the minor stream, the on-ramp traffic. Theory was established to account for this activity. Kerb lane drivers were also found to change to the median lane where possible, to assist coincident mergers. The net limited priority model accounts for this by predicting a reduced major stream flow rate, which excludes lane changers. Cowan's M3 model as calibrated for both streams. On-ramp and total upstream flow are required as input. Relationships between proportion of headways greater than 1 s and flow differed for on-ramps where traffic leaves signalised intersections and unsignalised intersections. Constant departure onramp metering was also modelled. Minimum follow-on times of 1 to 1.2 s were calibrated. Critical gaps were shown to lie between the minimum follow-on time, and the sum of the minimum follow-on time and the 1 s minimum headway. Limited priority capacity and other boundary relationships were established by Troutbeck (1995). The minimum average minor stream delay and corresponding proportion of drivers delayed were quantified theoretically in this study. A simulation model was constructed to predict intermediate minor and major stream delays across all minor and major stream flows. Pseudo-empirical relationships were established to predict average delays. Major stream average delays are limited to 0.5 s, insignificant compared with minor stream delay, which reach infinity at capacity. Minor stream delays were shown to be less when unsignalised intersections are located upstream of on-ramps than signalised intersections, and less still when ramp metering is installed. Smaller delays correspond to improved merge area performance. A more tangible performance measure, the distribution of distances required to merge, was established by including design speeds. This distribution can be measured to validate the model. Merging probabilities can be predicted for given taper lengths, a most useful performance measure. This model was also shown to be applicable to lane changing. Tolerable limits to merging probabilities require calibration. From these, practical capacities can be estimated. Further calibration is required of traffic inputs, critical gap and minimum follow-on time, for both merging and lane changing. A general relationship to predict proportion of drivers delayed requires development. These models can then be used to complement existing macroscopic models to assess performance, and provide further insight into the nature of operations.