This project will take an experimental and theoretical approach to understanding a driver’s speed choice and accelerator/brake control strategy, particularly in urban freight situations where the vehicle spends little time at constant speed. Driving simulator experiments and field data will be used to validate a theoretical driver model. The model will then be used to investigate pedal force feedback for modifying the driver behaviour to reduce emissions and fuel consumption. The project particularly complements Project 4B: Low energy B2B deliver vehicles, in which energy recovery during braking is investigated. The combination of feedback to the driver and energy recovery during braking could realise significant reductions in fuel consumption and emissions. The project builds upon expertise developed over twelve years in the Driver-Vehicle Dynamics Group at CUED (www.vehicledynamics.org).
- Develop and validate a theoretical model of the driver’s speed choice and accelerator/brake control strategy, building upon existing published information and new data collected from driving simulator experiments and/or analysis of field data, and focussing on the urban environment. Coupled with an appropriate vehicle model, fuel consumption and emissions will be predicted for a range of driver behaviours.
- Extend the driver-vehicle model to include pedal/foot dynamics and ‘two-player game’ interaction, in order that the effect of pedal force feedback to the driver and consequent fuel consumption and emissions can be predicted. Validate the model with further data from driving simulator and/or vehicle tests.
- Propose and assess strategies to reducing fuel consumption and emissions by means of pedal force feedback. Optimise the strategies using the driver-vehicle model. Assess the effectiveness of the strategies using driving simulator and/or vehicle tests.
Programme, Methodology and Deliverables
Task 4C1. Review existing published models of driver control, building upon a current project in longitudinal driver-vehicle dynamics . Develop a driver model based on the ‘state of the art’. Couple the driver model to a truck model in order to predict fuel consumption and emissions. Model various driver strategies by means of a theoretical ‘cost function’.
Task 4C2. The CUED fixed-base driving simulator presently has passive pedals and therefore a haptic interface for the accelerator and brake pedals is required.
Task 4C3. Identify and validate the model developed in 4C1 using data from new driving simulator experiments and field data. Driving simulator experiments will be developed initially using in-house test subjects. To generate statistically significant results, paid test subjects will be required.
Task 4C4. Extend and validate the driver model to include pedal/foot neuromuscular dynamics. This task will build upon recent experimental and theoretical work on neuromuscular dynamics in the steering task .
Task 4C5. Extend and validate the driver model to include ‘two-player game’ interaction, whereby a controller on board the vehicle provides feedback to the driver in order to minimise a cost function (including fuel consumption) that might be different from the driver’s cost function. This task will build upon recent work in applying game theory to the interaction between a driver and semi-autonomous steering control .
Task 4C6. Propose strategies to reducing fuel consumption and emissions by use of force-feedback pedals. Optimise the solutions using the extended driver-vehicle model.
Task 4C7. Assess the optimised strategies using driving simulator and/or vehicle tests.
The project should deliver experimental assessments of pedal force feedback for reducing emissions and new theoretical understanding of the interaction between a driver and a vehicle equipped with pedal feedback.
- CUED’s fixed-base driving simulator, augmented with new force feedback pedals.
- Field data on vehicle speed, fuel consumption and driver control actions, either existing data, or new data collected for the project.
- Mathematical model of vehicle.
- Paid test subjects.
Academic Impact: New theoretical understanding of driver-pedal-vehicle interaction could enable progress in related areas of academic research. For example, hybrid vehicles with regenerative braking can exhibit non-ideal response to the brake pedal; haptic pedal feedback might enable improved braking response.
Commercial and Social Impact: Adoption of pedal feedback to the driver, if effectively designed, may lead to reductions in fuel consumption and CO2 emissions. There may also be reductions in the workload and fatigue of the driver. Improved acceleration and speed control by the driver may lead to improved traffic flow and reduced congestion, as well as reduced wear on the vehicle.
1. Cathcart HA, Cole DJ, Stoffels H and Glover K, A mathematical occupant-vehicle model for investigating discomfort during transient longitudinal acceleration, to be presented at 23rd International Symposium on Dynamics of Vehicles on Roads and Tracks, 19-23 August 2013, Qingdao, China.
2. Cole DJ, A path-following driver-vehicle model with neuromuscular dynamics, including measured and simulated responses to a step in steering angle overlay. VSD, 50(4), p573-596, 2012.
3. Na X and Cole DJ, Linear quadratic game and non-cooperative predictive methods for potential application to modelling driver–AFS interactive steering control, Vehicle System Dynamics, 51(2), p165-198, 2013.