Vibrotactile pedals : provision of haptic feedback to support economical driving

The use of haptic feedback is currently an underused modality in the driving environment, especially with respect to vehicle manufacturers. This exploratory study evaluates the effects of a vibrotactile (or haptic) accelerator pedal on car driving performance and perceived workload using a driving simulator. A stimulus was triggered when the driver exceeded a 50% throttle threshold, past which is deemed excessive for economical driving. Results showed significant decreases in mean acceleration values, and maximum and excess throttle use when the haptic pedal was active as compared to a baseline condition. As well as the positive changes to driver behaviour, subjective workload decreased when driving with the haptic pedal as compared to when drivers were simply asked to drive economically. The literature suggests that the haptic processing channel offers a largely untapped resource in the driving environment, and could provide information without overloading the other attentional resource pools used in driving

Development of a Lower Extremity Mobility Assessment Methodology for Motor Vehicle Operation and Initial Validation

Limited quantifiable data exists on lower extremity mobility and function during driving. To date, the most appropriate existing measures of successful driving function are assessed by a driving rehabilitation specialist during an on-road evaluation. Establishing the kinematic chain- or the order and magnitude in which joints are moved- during driving may prove to be a useful tool in lower extremity function assessment in drivers. To this end, a study was conducted instrumenting both the left and right legs of healthy licensed male drivers (18-26 years old) with a system of angle measuring goniometers (Biometrics, Ltd.) in a driving simulator (DriveSafety CDS-250). The motions across the hip, knee and AFC joints were measured during active driving simulator scenarios, performing pedal tasks with both the right and left leg. Subjects completed 3 trials for each leg in which they were required to respond to braking tasks and peripheral queuing, and comparisons between left versus right leg driving over time were conducted for measuring brake response time, return to gas movement time, and joint angle minimums, maximums, and ranges of motion. Kinematic chain joint angles were also correlated against each other so as to yield a slope and strength of correlation, allowing the development of a numerical assessment of the kinematic chain. Results of this work indicate that left leg driving requires characteristically different kinematic chain in lower extremity motions, primarily with respect to the altered use of AFC inversion/eversion. Left limb correlation values were found, in general, to have a higher value, indicating a greater degree of repeatable gross motor movement. Right leg motions showed a greater range of fine motor control, which could be characteristic of dominant leg driving in general. Similar movement patterns were found in both phases of pedal transition, both the brake application and the return from brake to gas. This study showed that the distinctive motions seen in right versus left-footed driving can indeed be characterized by goniometric application. Further studies should explore the effects of left leg driver training in a longitudinal manner, testing this driving task over the period of several weeks. If these future studies show a development and improvement of left leg driver performance, patients undergoing right leg orthopedic procedures could be taught to drive effectively with the left leg during rehabilitation for extended periods of time, thereby allowing those patients to maintain their independence

Traffic flow Impacts of a congestion assistant

This paper presents the results from a microscopic traffic simulation study that was conducted to investigate the impacts of a so-called Congestion Assistant on traffic efficiency and traffic safety. The Congestion Assistant is an in-vehicle system that supports the driver with an Active pedal when approaching a traffic jam and a Stop & Go when driving in a traffic jam. Six variants of the Congestion Assistant with different equipment rates on a four-lane highway with a lane drop were assessed. The traffic simulation tool was calibrated and validated using measured loop data on a segment of the Dutch A12 highway. The Congestion Assistant was found to reduce the amount of congestion significantly, especially due to the Stop & Go. This function led to more efficient car-following behavior by adapting smaller headways and eliminating the reaction time of drivers. The Active pedal of the Congestion Assistant hardly influenced traffic efficiency; rather it affected traffic safety through a safer approach to a jam

Safe driving in a green world : a review of driver performance benchmarks and technologies to support ‘smart’ driving

Road transport is a significant source of both safety and environmental concerns. With climate change and fuel prices increasingly prominent on social and political agendas, many drivers are turning their thoughts to fuel efficient or ‘green’ (i.e., environmentally friendly) driving practices. Many vehicle manufacturers are satisfying this demand by offering green driving feedback or advice tools. However, there is a legitimate concern regarding the effects of such devices on road safety – both from the point of view of change in driving styles, as well as potential distraction caused by the in-vehicle feedback. In this paper, we appraise the benchmarks for safe and green driving, concluding that whilst they largely overlap, there are some specific circumstances in which the goals are in conflict. We go on to review current and emerging in-vehicle information systems which purport to affect safe and/or green driving, and discuss some fundamental ergonomics principles for the design of such devices. The results of the review are being used in the Foot-LITE project, aimed at developing a system to encourage ‘smart’ – that is safe and green – driving

A series elastic brake pedal for improving driving performance under regenerative braking

Electric and hybrid vehicles are favored to decrease the carbon footprint on the planet. The electric motor in these vehicles serves a dual purpose. The use of electric motor for deceleration, by converting the kinetic energy of the vehicle into electrical energy to be stored in the battery is called regenerative braking. Regenerative braking is commonly employed by electrical vehicles to signi cantly improve energy e ciency and to help to meet emission standards. When the regenerative and friction brakes are simultaneously activated by the driver interacting with the brake pedal, the conventional haptic brake pedal feel is disturbed due to the regenerative braking. In particular, while there exists a physical coupling between the brake pedal and the conventional friction brakes, no such physical coupling exists for the regenerative braking. As a result, no reaction forces are fed back to the brake pedal, resulting in a unilateral power ow between the driver and the vehicle. Consequently, the relationship between the brake pedal force and the vehicle deceleration is strongly in uenced by the regenerative braking. This results in a unfamiliar response of the brake pedal, negatively impacting the driver's performance and posing a safety concern. The reaction forces due to regenerative braking can be fed back to the brake pedal, through actuated pedals that re-establish the bilateral power ow to recover the natural haptic pedal feel. We propose a force-feedback brake pedal with series elastic actuation to preserve the conventional brake pedal feel during regenerative braking. The novelty of the proposed design is due to the deliberate introduction of a compliant element between the actuator and the brake pedal whose de ections are measured to estimate interaction forces and to perform closed-loop force control. Thanks to its series elasticity, the force-feedback brake pedal can utilize robust controllers to achieve high delity force control, possesses favorable output impedance characteristics over the entire frequency spectrum, and can be implemented in a compact package using low-cost components. We introduce pedal feel compensation algorithms to recover the missing regenerative brake forces on the brake pedal. The proposed algorithms are implemented for both two-pedal cooperative braking and one-pedal driving conditions. For those driving conditions, the missing pedal feedback due to the regenerative brake forces are rendered through the active pedal to recover the conventional pedal force mapping. In two-pedal cooperative braking, the regenerative braking is activated by pressing the brake pedal, while in one-pedal driving the activation takes place as soon as the throttle pedal is released. The applicability and e ectiveness of the proposed series elastic brake pedal and haptic pedal feel compensation algorithms in terms of driving safety and performance have been investigated through human subject experiments. The experiments have been conducted using a haptic pedal feel platform that consists of a SEA brake pedal, a torque-controlled dynamometer, and a throttle pedal. The dynamometer renders the pedal forces due to friction braking, while the SEA brake pedal renders the missing pedal forces due to the regenerative braking. The throttle pedal is utilized for the activation of regenerative braking in one-pedal driving. The simulator implements a vehicle pursuit task similar to the CAMP protocol and provides visual feedback to the participant. The e ectiveness of the preservation of the natural brake pedal feel has been studied under two-pedal cooperative braking and one-pedal driving scenarios. The experimental results indicate that pedal feel compensation can signi cantly decrease the number of hard braking instances, improving safety for both two-pedal cooperative braking and one-pedal driving. Volunteers also strongly prefer compensation, while they equally prefer and can e ectively utilize both two-pedal and one-pedal driving conditions. The bene cial e ects of haptic pedal feel compensation on safety is evaluated to be larger for the two-pedal cooperative braking condition, as lack of compensation results in sti ening/softening pedal feel characteristics in this cas

How do drivers negotiate intersections with pedestrians? The importance of pedestrian time-to-arrival and visibility

Forward collision warning (FCW) and autonomous emergency braking (AEB) systems are increasingly available and prevent or mitigate collisions by alerting the driver or autonomously braking the vehicle. Threat-assessment and decision-making algorithms for FCW and AEB aim to find the best compromise for safety by intervening at the “right” time: neither too early, potentially upsetting the driver, nor too late, possibly missing opportunities to avoid the collision.Today, the extent to which activation times for FCW and AEB should depend on factors such as pedestrian speed and lane width is unknown. To guide the design of FCW and AEB intervention time, we employed a fractional factorial design, and determined how seven factors (crossing side, car speed, pedestrian speed, crossing angle, pedestrian size, zebra-crossing presence, and lane width) affect the driver’s response process and comfort zone when negotiating an intersection with a pedestrian. Ninety-four volunteers drove through an intersection in a fixed-base driving simulator, which was based on open-source software (OpenDS). Several parameters, including pedestrian time-to-arrival and driver response time, were calculated to describe the driver response process and define driver comfort boundaries.Linear mixed-effect models showed that driver responses depended mainly on pedestrian time-to-arrival and visibility, whereas factors such as pedestrian size, zebra-crossing presence, and lane width did not significantly influence the driver response process. Some drivers changed their negotiation strategy (proportion of pedal braking to engine braking) to minimize driving effort over the course of the experiment. Experienced drivers changed more than less experienced drivers; nevertheless, all drivers behaved similarly, independent of driving experience. The flexible and customizable driving environment provided by OpenDS may be a viable platform for behavioural experiments in driving simulators.Results from this study suggest that visibility and pedestrian time-to-arrival are the most important variables for defining the earliest acceptable FCW and AEB activations. Fractional factorial design effectively compared the influence of several factors on driver behaviour within a single experiment; however, this design did not allow in-depth data analysis. In the future, OpenDS might become a standard platform, enabling crowdsourcing and favouring repeatability across studies in traffic safety. Finally, this study advises future design and evaluation procedures (e.g. new car assessment programs) for FCW and AEB by highlighting which factors deserve further investigation and which ones do not

Analysis of Disengagements in Semi-Autonomous Vehicles: Drivers’ Takeover Performance and Operational Implications

This report analyzes the reactions of human drivers placed in simulated Autonomous Technology disengagement scenarios. The study was executed in a human-in-the-loop setting, within a high-fidelity integrated car simulator capable of handling both manual and autonomous driving. A population of 40 individuals was tested, with metrics for control takeover quantification given by: i) response times (considering inputs of steering, throttle, and braking); ii) vehicle drift from the lane centerline after takeover as well as overall (integral) drift over an S-turn curve compared to a baseline obtained in manual driving; and iii) accuracy metrics to quantify human factors associated with the simulation experiment. Independent variables considered for the study were the age of the driver, the speed at the time of disengagement, and the time at which the disengagement occurred (i.e., how long automation was engaged for). The study shows that changes in the vehicle speed significantly affect all the variables investigated, pointing to the importance of setting up thresholds for maximum operational speed of vehicles driven in autonomous mode when the human driver serves as back-up. The results shows that the establishment of an operational threshold could reduce the maximum drift and lead to better control during takeover, perhaps warranting a lower speed limit than conventional vehicles. With regards to the age variable, neither the response times analysis nor the drift analysis provide support for any claim to limit the age of drivers of semi-autonomous vehicles

Influence of accelerator pedal force feedback on truck drivers' speed control

The UK government has set clear targets for 80% reductions (compared with 1990 levels) in greenhouse gas emissions by 2050 and pressure is increasing on the road transport industry to reduce the fuel consumption and harmful exhaust emissions of Heavy Goods Vehicles (HGVs). Vehicle manufacturers and operators alike are having to investigate and find new ways of making reductions. It is thought that improving driver behaviour offers significant potential for these reductions in fuel consumption and emissions. This thesis considers the use of Active Accelerator Pedals (AAPs) and the potential for improved driver performance that they may offer by providing pedal force feedback to the driver. In order to develop understanding of the interactions between the human driver and accelerator pedal, two near identical tractor units, operated by Turners of Soham Ltd, were fitted with the a data logger. Data was collected and stored over a period of four months as they operated on the road. This data provided the basis for a vehicle model to be developed using real-world conditions, rather than strictly controlled test track conditions. Analysis of the behaviour of the two drivers also identified differences is styles, and explained 7% fuel consumption differences between the two drivers when negotiating roundabouts. A new mathematical model of the human driver’s longitudinal control was also developed to include the driver’s cognitive control of the accelerator pedal. Model Predictive Control theory, commonly used for modelling the driver’s steering control, was used and different driving styles were replicated by varying the weightings in a cost function, and a series of driving simulator experiments were performed to validate the model. Nine human drivers, two of which were professionals, performed two driving scenarios (drive cycle and car-following). The driver model was fitted to each driver individually to mathematically express the differences in their styles. The simulated RMS pedal forces from the fitted driver models lay within 20% of the measured simulator values. The driver model was also extended to include the interactions between a human driver and an AAP using mathematical game theory. Three frameworks were proposed: decentralised, cooperative and one-sided cooperative, but, as the cooperative framework would have been very difficult to implement experimentally, it was only considered theoretically. The same nine human drivers were presented with drive cycle and car-following scenarios whilst being assisted by pedal feedback to validate the model. Both decentralised and one-sided cooperative frameworks were applied to the fitting and compared. In the drive cycle scenario, the one-sided cooperative framework output an identical controller to the decentralised framework. In the car-following scenario, the one-sided cooperative framework produced the best fit, suggesting that the human drivers adapted their strategy to reflect the guidance from the AAP. It was noted in both scenarios that the peak pedal displacement decreased by approximately 20% with the presence of pedal force feedback. Further work is suggested to improve the mass and road gradient data obtained from the data loggers in vehicles in order to reduce the uncertainty in the traction force and fuel rate maps. With a model for the interactions of a human driver with an AAP now in place, the pedal feedback strategy can now be optimised to improve the performance of the human driver.Centre for Sustainable Road Freight and EPSR

Ergonomics of intelligent vehicle braking systems

The present thesis examines the quantitative characteristics of driver braking and pedal operation and discusses the implications for the design of braking support systems for vehicles. After the current status of the relevant research is presented through a literature review, three different methods are employed to examine driver braking microscopically, supplemented by a fourth method challenging the potential to apply the results in an adaptive brake assist system. First, thirty drivers drove an instrumented vehicle for a day each. Pedal inputs were constantly monitored through force, position sensors and a video camera. Results suggested a range of normal braking inputs in terms of brake-pedal force, initial brake-pedal displacement and throttle-release (throttle-off) rate. The inter-personal and intra-personal variability on the main variables was also prominent. [Continues.