A Driver Advisory Tool to Reduce Fuel Consumption

Neurocognitive symptoms persist in many people living with HIV (PLWH). Safe driving practices are dependent on intact cognition. Research in the general driving population suggests that PLWH with neurocognitive impairment (NCI) perform worse on driving assessment tasks than cognitively intact PLWH. We explored the relationship between HIV status, NCI, and driving ability in vocational drivers. Two-hundred-and-four male drivers [68 drivers with HIV] completed neuropsychological testing and two driving simulator tasks assessing driving under routine and challenging circumstances. Drivers with NCI, regardless of HIV status, exhibited worse driving performance than cognitively intact drivers overall (p = .032), and on the challenging drive (p = .048) in particular. Better driving performance was associated with having received professional driver training. Other favorable predictors included being a truck driver and not having HIV. Drivers with NCI are at greater risk of making driving simulator errors, and errors are more evident under challenging driving conditions. Driver training interventions may be effective in remediating poorer driving performance in drivers with NCI. Studying the impact of HIV and cognition in individuals who are working professionally is a complex undertaking that requires consideration of factors (e.g., training and experience) alongside the usual variables considered when studying the general population.

An appropriate driver-assistance in order to use regenerative braking effectively is significant as a feasible method of a smart power management for energy-saving and economical solutions in sustainable electric railway operation. It is substantially significant to suppress braking force in high speed so that the braking force is less than corresponding traction force in the field-weakening speed region so that the whole braking force can be supplied by the regenerative electric brakes without active use of ordinary mechanical brakes. This power limitation in high speed is also beneficial to reduce the probability of regenerative braking cancellation caused by occasional high voltage at pantographs. If one limit the braking force, the total traveling time is increased, but this supplemental running time is relatively small, when the limitation of the deceleration is only applied in high speed and this supplemental time can be absorbed in realistic time margin, which is the difference of the initially scheduled conservative running time and actual one. Authors propose this type of the fully used electric braking pattern as “constant-power braking” or “power-limiting braking” and for realistic application to existing rolling stocks, they also propose a minor variation called as discrete approximate constant-power electric braking. The train driver must start braking operation considerably earlier than conventional ordinary train operation, and the braking force must be precisely controlled depending on the actual train speed timely. Since this driving method is, therefore, inherently more complicated than conventional one, a smart onboard driver-assistance or automatic train stopping control is requested for the realization.

The objective of this study was to determine the effects of display modality, level of driver interaction, and amount of information on the driving performance and system operation performance of commercial drivers. Introducing any level of interaction with an Advanced Traveler Information System (ATIS) will probably result in some level of increased workload for the driver. However, it is possible that the increase in workload would not result in unsafe driving behavior. A secondary objective of this study was to determine at what level of ATIS task demand driving performance begins to degrade to the point of becoming unsafe. To test the impact of having commercial drivers operate a multi-function ATIS, a prototype display was developed that would provide a variety of tasks to be performed while driving. The prototype for this experiment consisted of baseline information that was always presented to the driver in addition to an underlying menu structure that allows the driver to perform more complex information retrieval functions. The baseline ATIS display used for both taxi and truck drivers was identical, while the underlying menu structures were different to reflect the different types of information the drivers might require or desire. The system was designed for use as a visual-only system or as a combination visual and auditory system. An auditory-only system was not tested because it was felt that any feasible system would include at least some visual elements. Based upon the results of this research, guidelines have been developed to aid in the design of ATIS.

Driving simulators to evaluate road geometric design effects on driver behaviour: A systematic review

Fatigue increases the tendency of poor train driving strategy decision. Decision making in cognitive overload and cognitive underload situation mostly outputs bad decisions. Accordingly, train driver’s cognitive function is required to be sTable during travel so that they can give correct response at a given situation. This study constructs a conceptual framework for cognitive workload management (CWM) of train driver by taking the energy expenses from cognition into the account. This study combines objective and subjective cognitive workload analysis to evaluate train driver duty readiness. The objective load analysis was performed through energy level approximation based on neuronal dynamics simulation from 76 brain regions. The cognitive energy expenditure (CEE) calculated from neuron action potential (NAP) and the ion-membrane current (IMC) from the simulation results. The cognitive load (CL) approximated by converts the continuous time-based CEE to discrete frequency-based CL using Fourier series. The subjective cognitive workload obtained from train simulation results followed by 27 participants. The participants fill the questionnaire based on their simulated journey experience. The results of the evaluation used to build readiness evaluation classifier based on control chart. The control chart evaluation helps the management to determine weekly rest period and daily short rest period treatment base on each train driver workload. The CWM framework allows different recovery treatment to be applied to each train driver. The impact of the CWM application is the performance of train drivers are kept stable. Thus, the CWM framework based on CEE is useful to prevent physical and mental fatigue

This simulator-based study examined the use of conventional auditory warnings (tonal, non-verbal sounds) and auditory icons (representational, non-verbal sounds), alone and in combination with a dash-mounted visual display to warn commercial motor vehicle operators of impending front-to-rear and side collision situations. Driver performance was measured in the simulated driving task via brake response time in the front-to-rear collision scenarios and via a count of accident occurrence in the side collision scenarios. For both front-to-rear and side collision scenarios, auditory icons elicited significantly improved driver performance over conventional auditory warnings. Driver performance improved when collision warning information was presented through multiple modalities.

More energy efficient and sustainable systems become increasingly widespread in automotive applications (e.g., hybrid electric vehicles; HEVs). Yet, their real-world energy efficiency strongly depends on driver behaviour and, often, showing optimal eco-driving behaviour is challenging especially if energy dynamics are not sufficiently represented in the driver interface. For example, previous research indicated that HEV drivers try to actively utilize and regain electric energy, without sufficiently considering conversion losses that are part of this process (i.e., energy conversion fallacy). One possible explanation is that HEV drivers do not actively consider kinetic energy while driving, mainly because it is not represented in energy displays. The object of the present research was to examine whether drivers can be supported in a less biased perception of the efficiency of regenerative braking when an indicator of kinetic energy is also represented in the interface. To this end, we designed an online video experiment. Two displays were presented to drivers, a conventional energy flow display in which only electric energy resources were represented and an adapted display in which also kinetic energy resources were represented. Drivers rated the perceived energy efficiency of two types of deceleration scenarios, regenerative braking and neutral mode. The results provide first evidence that adding a representation of kinetic energy resources to displays of energy flows in HEVs can reduce drivers’ energy conversion fallacy.

• The performance of Adaptive Cruise Control (ACC) is limited on road curves. • The Intelligent Speed Adaptation for Visibility (V-ISA) adjusts speed based on road conditions. • A driving simulation study assessed the influence of ACC and V-ISA on driver behaviour. • Integrating ACC and V-ISA significantly improved longitudinal driving performance. • The system achieved high system acceptance with no added mental workload. Advanced Driver Assistance Systems (ADAS) have become an integral part of modern vehicles, significantly changing the driving experience. Adaptive Cruise Control (ACC) assists drivers in maintaining a constant speed and a safe following distance; however, it does not moderate the speed along curves when sight limitations occur, thus compromising safety. To address these challenges, this study integrates the Intelligent Speed Adaptation for Visibility (V-ISA) system with ACC. The V-ISA system dynamically adjusts the vehicle speed based on real-time visibility conditions, thereby enhancing safety on road curves where sight distance is restricted. Additionally, this study evaluates the impact of the ACC + V-ISA system on driver performance, specifically focusing on speed management, lateral vehicle control, and driver experience with assistance systems. The study was conducted in a simulated environment with forty-five participants. The results revealed that the ACC + V-ISA system effectively reduced vehicle speed on curves with limited visibility. The ability of the system to regulate speed according to prevailing road conditions highlights its potential to improve road safety. Moreover, the findings suggest that using the V-ISA system integrated with ACC maintains user acceptance and satisfaction while imposing no additional mental workload compared to using ACC alone. These insights are crucial for the future design of ADAS and autonomous vehicles and emphasize the importance of introducing this system into vehicles. LED bar colour

PurposeThis paper addressed some critical issues in the development of hybrid electric powertrains for aircraft and propose a design methodology based on multi-objective optimization algorithms and mission-based simulations.Design/methodology/approachScalable models were used for the main components of the powertrain, namely, the (two stroke diesel) engine, the (lithium) batteries and the (permanent magnet) motor. The optimization was performed with the NSGA-II genetic algorithm coupled with an in-house MATLAB tool. The input parameters were the size of engine, the hybridization degree and the specification of the battery (typology, nominal capacity, bus voltage, etc.). The outputs were electric endurance, additional volume, performance parameters and fuel consumption over a specified mission.FindingsElectric endurance was below 30 min in the two test cases (unmanned aerial vehicles [UAVs]) but, thanks to the recharging of the batteries on-board, the total electric time was higher. Fuel consumption was very high for the largest UAV, while an improvement of 11 per cent with respect to a conventional configuration was obtained for the smallest one.Research limitations/implicationsThe research used a simplified approach for flight mechanics. Some components were not sized in the proposed test cases.Practical implicationsThe results of the test cases stressed the importance of improving energy density and power density of the electric path.Social implicationsThe proposed methodology is aimed at minimizing the environmental impact of aircraft.Originality/valueThe proposed methodology was obtained from the automotive field with several original contributions to account for the aircraft application.

Hybrid-Electric aircraft powertrain modeling for Unmanned Aerial Systems (UAS) is a useful tool for predicting powertrain performance of the UAS aircraft. However, for small UAS, potential gains in range and endurance can depend significantly on the aircraft flight profile and powertrain control logic in addition to the subsequent impact on the performance of powertrain components. Small UAS aircraft utilize small-displacement engines with poor thermal efficiency and, therefore, could benefit from a hybridized powertrain by reducing fuel consumption. This study uses a dynamic simulation of a UAS, representative flight profiles, and powertrain control logic approaches to evaluate the performance of a series hybrid-electric powertrain. Hybrid powertrain component models were developed using lookup tables of test data and model parameterization approaches to generate a UAS dynamic system model. These models were then used to test three different hybrid powertrain control strategies for their ability to provide efficient IC engine operation during the charging process. The baseline controller analyzed in this work does not focus on optimizing fuel efficiency. In contrast, the other two controllers utilize engine fuel consumption data to develop a scheme to reduce fuel consumption during the battery charging operation. The performance of the powertrain controllers is evaluated for a UAS operating on three different representative mission profiles relevant to cruising, maneuvering, and surveillance missions. Fuel consumption and battery state of charge form two metrics that are used to evaluate the performance of each controller. The first fuel efficiency-focused controller is the ideal operating line (IOL) strategy. The IOL strategy uses performance maps obtained by engine characterization on a specialized dynamometer. The simulations showed the IOL strategy produced average fuel economy improvements ranging from 12%-15% for a 30-minute mission profile compared to the baseline controller. The last controller utilizes fuzzy logic to manage the charging operations while maintaining efficient fuel operation where it produced similar fuel saving to the IOL method but were generally higher by 2-3%. The importance of developing detailed dynamic system models to capture the power variations during flight with fuel-efficient powertrain controllers is key to maximizing small UAS hybrid powertrain performance in varying operating conditions.

Safety and performance of train drivers are crucial factors in railway operations. Shift work systems involving night shifts, irregular rotations, and long working hours can lead to work-related fatigue (burnout), which impacts performance. This study aims to analyze the effect of work shifts on train driver performance with burnout as a mediating variable at PT Kereta Api Indonesia (Persero). The research uses a quantitative approach with a survey of 2,184 train drivers. Data analysis is conducted using Partial Least Squares–Structural Equation Modeling (PLS-SEM). The results reveal that work shifts have a significant positive effect on burnout (β = 0.608), work shifts have a significant negative effect on train driver performance (β = –0.339), and burnout has a very strong negative effect on performance (β = –0.839). Burnout significantly mediates the relationship between work shifts and performance, with a mediation effect of 51%. These findings emphasize that the decline in train driver performance is more influenced by burnout than by direct effects of work shifts. Comparatively, Japan’s fatigue management practices through a Fatigue Risk Management System (FRMS) are more systematic and preventive compared to Indonesia. This research contributes to strengthening the role of burnout as a mediating variable in the Job Demands–Resources framework and offers practical implications for PT KAI in reforming shift work policies for safety.

Praxis Critical Systems Ltd carries out systems and software engineering and we develop requirements using our own method called REVEALB. REVEAL is a general method and makes no distinction between software and any other method of implementing a system. The same principles and the same process apply to all kinds of requirements, but the particular issues, notations and tools depend on the scale and nature of the problem and to some extent on the technology of the system being developed. This commonality is important because it means we can use insights and methods from one discipline to solve problems in other disciplines. This talk will describe the principles behind REVEAL and explain how they generalise ideas from software (for example Parnas' four variable model) and from systems engineering. It will outline the REVEAL process which ensures that wc understand the way that the system and its environment interact to satisfy the mission needs. We have applied this process to projects ranging from a $I million software development to a $10 billion railway upgrade. Clearly the nature of the environment is very different in these two extremes. In the software project the environment is a collection of other software and hardware, plus a few system users. The important concerns include software interfaces, and the system is specified using fairly traditional software notations. In the rail upgrade the environment includes the geography of the UK and the behaviour of rail passengers, train drivers and many other people and systems. Concerns include the safety and performance of the system in the face of human and natural unpredictability. The system specification uses a wide variety of notations including for example track layouts, electrification, signalling and human procedures. In both cases, having a common method gave us important insights and ideas which we could carry over from one kind of development to the other. Our experience suggests that requirements engineering can be applied in a unified way across a wide range of projects in many disciplines.

Ethanol is important both forensically ('drunk driving' or driving while under the influence, 'DWI', regulations) and commercially (alcoholic beverages). Blood- and breath-alcohol testing can be imposed on individuals operating private vehicles such as cars, boats or snowmobiles, or operators of commercial vehicles like trucks, planes and ships. The various levels of blood alcohol that determine whether these operators are considered legally impaired vary depending on the circumstances and locality. Accurate calibration and validation of instrumentation is critical in areas of forensic testing where quantitative analysis directly affects the outcome of criminal prosecutions, as is the case with the determination of ethanol in blood and breath. Additionally, the accurate assessment of the alcoholic content of beverages is a commercially important commodity.In 2002, the CCQM conducted a key comparison (CCQM-K27) for the determination of ethanol in aqueous matrix with nine participants. A report on this project has been approved by the CCQM and can be found at the BIPM website. CCQM-K27 comprised three samples, one at low mass fraction of ethanol in water (nominal concentration of 0.8 mg/g), one at high level (nominal concentration of 120 mg/g) and one wine matrix (nominal concentration of 81 mg/g). Overall agreement among eight participants using gas chromatography with flame ionization detection (GC-FID), titrimetry, isotope dilution gas chromatography/mass spectrometry (GC-IDMS) and gas chromatography–combustion-isotope ratio mass spectrometry (ID-GC-C-IRMS) was good. The ninth participant used a headspace GC-FID method that had not been validated in an earlier pilot study (CCQM-P35).A follow-on key comparison, CCQM-K27-Subsequent, was initiated in 2003 to accommodate laboratories that had not been ready to benchmark their methods in the original CCQM-K27 study or that wished to benchmark a different method. Four levels of ethanol in water were used in the subsequent study (nominal concentrations of 0.2 mg/g, 1 mg/g, 3 mg/g and 60 mg/g). The three participants in the CCQM-K27-Subsequent key comparison demonstrated their ability to measure ethanol in aqueous matrix in the concentration range of 0.2 mg/g to 60 mg/g. A report on this project has been approved by the CCQM and can be found at the BIPM website.A second follow-on key comparison, CCQM-K27.2 Second Subsequent, was initiated in 2006 to accommodate laboratories that had not been ready to benchmark their methods in the previous two CCQM-K27 studies. Two levels of ethanol in water were used in the second subsequent study ranging in concentration between 0.5 mg/g and 4 mg/g. Four of the five participants in the CCQM-K27.2 Second Subsequent key comparison demonstrated their ability to measure ethanol in aqueous matrix in that concentration range.Main text.To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database kcdb.bipm.org/.The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

Transition States

This study estimates the dose–response relationship between body mass index (BMI) and crash risk in operators of heavy commercial motor vehicles. Intake data were collected during the first two weeks of instruction from 744 new truck drivers training for their commercial driver's licenses at a school operated by the cooperating trucking firm. Drivers were then followed prospectively on the job using the firm's operational data for two years, or until employment separation, whichever came first. Multivariate Poisson regression and Cox proportional hazards models were used to estimate the relationship between crash risk and BMI, controlling for demographic characteristics and for variations in the exposure to risks on the road. Results from the Poisson regression, which used cumulative miles driven as an exposure control, indicated that compared to normal BMI (18.5<BMI<25) the risk ratio (RR) for all crashes was significantly higher for drivers in the combined obesity Classes II and III: RR=1.55 (95% CI 1.24–1.94). Similarly, the multivariate Cox proportional hazard model (controlling for miles and job type on a week-by-week basis) showed that crash risk was significantly higher compared to normal BMI for the same combined obesity Classes II and III: RR=1.54 (95% CI 1.13–2.10). The results of this prospective study establish an association between obesity and crash risk and have important implications for driver health and public safety.