Can Shared Control Improve Overtaking Performance? Combining Human and Automation Strengths for a Safer Maneuver
Abstract
:1. Introduction
1.1. The Road Safety Problem
1.2. The AD Solution
1.3. The Shared Control Solution
1.4. Current Research
1.5. Our Contributions
- A steering control strategy that provides smooth and context-dependent transitions for the de-activation and the re-activation of the automation.
- Steering torque corrections to avoid collision with oncoming vehicles (with an intensity of correction proportional to the driving risk indicator).
- An HMI that informs the driver about the system limitations and the suggestion to take control and overtake.
2. Methodology
2.1. Use Case
“On an extra-urban road, Silvano is driving an L2 vehicle in AD mode to come back home (at 90 km/h), when the vehicle approaches a big and slow truck ahead, driving at 70 km/h. The ADS cannot overtake due to the limited perception (it cannot “see” and check if other vehicles are coming in the opposite direction and thus if the left-lateral lane is free for the maneuver). In such a situation, the ADS can only slowly follow the vehicle in front, waiting until it changes its route. However, Silvano is in a hurry due to an appointment for dinner and thus he is getting nervous. In this sense, the system based on shared control asks Silvano for support in case he wants to overtake”.
2.2. Experimental Settings and Apparatus
2.3. Experiment Design
2.3.1. Participants
2.3.2. Experimental Conditions
- L2: As a baseline, an ADS with ALC and ACC activated is tested. When the driver decides to overtake, the system deactivates when the steering torque exceeds a 3 Nm threshold. A sound confirming deactivation is heard. During the takeover, the driver is free to drive, without any system intervention. Once the overtaking is finished and the conditions allow it, the driver needs to re-activate the system by pressing the button on the steering wheel and a confirmation sound is heard. A beep sound is issued when the ego-vehicle has spent a few seconds behind the truck as an indication to overtake, which is used only to have consistent overtaking attempts in the two experimental conditions.
- SC: As part of the proposed system, shared control functionalities are added over the baseline condition. The system is deactivated when there is enough field of view and if there is enough time to do the overtaking (not only by torque effort). In addition, the system reengages the automated mode without any explicit indication from the driver when returning to the right lane (not manually). If there is not enough time to overtake, the system increases the steering correction torque in proportion to the risk of collision to abort the maneuver. An HMI indicates to the driver that the system needs support to overtake and informs about the automation state.
2.3.3. Procedure
3. System Design
3.1. Arbitration
- Vehicle position: Represented as the lateral error of the vehicle to the center of the right lane. The labels of the membership functions (Right, Border, and Left) represent the different positions of the vehicle on a two-lane road.
- Driver intention: Represented as the derivative of the lateral error of the vehicle. The labels of the membership functions (Away, Stay, and Return) represent the driver’s intention to leave the lane, stay in the same direction, or return to the lane. This intention is combined with the lateral error to obtain an estimate of the lane change intention.
- Maneuver risk: Represented as the distance-to-collision between the vehicle and the oncoming vehicle in the left lane. The labels of the membership functions (Far and Close) represent the relative distance between the two vehicles, indicating low and high collision risk, respectively.
- Level of Authority: Represented as the maximum steering torque of the correction in Nm. The labels of the membership functions (Manual, Assistance, and Override) represent the full range of automation steering assistance from none to gentle corrections, to maximum assistance that can even exceed the force exerted by the driver.
3.2. Shared Controller (Operational Level)
- Minimization of objectives: Three main objectives are defined (as in Equation (1)). First, the tracking performance (, associated with vehicle position to the reference trajectory. Second, the driving comfort (, linked to the steering wheel angular velocity () and the vehicle yaw rate (ψ). Third and last, the steering effort, related to the torque control signal ( and its rate change (), is represented as the input optimization function .
- Constraints of variables: The ability of NMPC to add states and inputs constraints allows the limiting of values that can help in the preservation of safety, for example, a constraint in the yaw rate is included to avoid the vehicle drifting after the correction maneuver (Equation (2)). Additionally, constraints are added to the control variable for effort and comfort purpose (Equations (3) and (4)).
- Adaptive authority: To assist the driver with variable intensities of torque, the level of haptic authority is included in the road-vehicle model through the torque derivative equation (Equation (5)). In addition, the authority is linked to the maximum steering torque provided by the control through the constraint (Equation (3)).
- Stability Criterion: Adding authority to the controller is equivalent to increasing its stiffness, therefore the increase in the authority makes the system prone to oscillations. In this sense, a stability criterion is designed to keep the NMPC stability for different values of . It is related to the value of an equivalent damping value of the steering motor as in Equation (6).
3.3. Human–Machine Interface
4. Data Analysis and Results
4.1. Statistical Analysis of Objective Results
4.1.1. Driving Mode
4.1.2. Road Departure Events
4.1.3. Collision Events
- Crashes: When the two vehicles collide after an overtaking attempt. When TTC = 0.
- Near-misses: Defined as “incidents in which no property was damaged, and no personal injury was sustained, but where, given a slight shift in time or position, damage or injury easily could have occurred”. Although there is no definitive threshold for considering near misses, the overall value is between 0.5 s and 1 s [30]. Since the scenario already considers a critical situation with the appearance of unexpected vehicles, the threshold of 0.5 s was preferred to capture a better difference between the systems.
- Misses: Those presenting a high probability of collision (excluding accidents and near-misses). The safety threshold for this KPI is 1.5 s, which is half of the minimum TTC that naturally occurs when the left vehicle appears at a very close distance (125 m); this is also a value used as a safety threshold in the literature [31,32].
- Safe: Those outside the first three indicators with respect to the total number of overtaking events.
4.2. Statistical Analysis of Subjective Results
4.2.1. SUS
4.2.2. SAS
5. Discussion
5.1. Comparison with Similar Works
5.2. Limitations and Future Works
6. Conclusions
6.1. Summary
6.2. Lessons Learnt
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Disclaimer
References
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Right | Border | Left | |||||||
---|---|---|---|---|---|---|---|---|---|
Return | Stay | Away | Return | Stay | Away | Return | Stay | Away | |
Left | Assist | Assist | Assist | Assist | Assist | Override | Override | Override | Override |
Right | Assist | Assist | Assist | Assist | Assist | Manual | Manual | Manual | Manual |
Analyzed Variable | Category | Main Variable |
---|---|---|
Driving mode | Operation mode | Time in each mode |
Road departure events | Safety | Lateral error |
Collision events | Safety | Time-to-collision (TTC) |
Event | TTC to the Oncoming Vehicle |
---|---|
Crashes | TTC = 0 s |
Near misses | 0 s < TTC < 0.5 s |
Unsafe | 0.5 s ≤ TTC ≤ 1.5 s |
Safe | TTC ≥ 1.5 s |
# | Question |
---|---|
01 | I think that I would like to use this system frequently. |
02 | I found the system unnecessarily complex. |
03 | I thought the system was easy to use. |
04 | I think I would need the support of a technical person to be able to use this system. |
05 | I found the various functions in this system were well integrated. |
06 | I thought there was too much inconsistency in this system. |
07 | I would imagine that most people would learn to use this system very quickly. |
08 | I found the system very cumbersome to use. |
09 | I felt very confident using the system. |
10 | I needed to learn a lot of things before I could get going with this system. |
Useful | o | o | o | o | o | Useless |
Pleasant | o | o | o | o | o | Unpleasant |
Bad | o | o | o | o | o | Good |
Nice | o | o | o | o | o | Annoying |
Effective | o | o | o | o | o | Superfluous |
Irritating | o | o | o | o | o | Likeable |
Assisting | o | o | o | o | o | Worthless |
Undesirable | o | o | o | o | o | Desirable |
Raising alertness | o | o | o | o | o | Sleep-inducing |
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Marcano, M.; Tango, F.; Sarabia, J.; Chiesa, S.; Pérez, J.; Díaz, S. Can Shared Control Improve Overtaking Performance? Combining Human and Automation Strengths for a Safer Maneuver. Sensors 2022, 22, 9093. https://doi.org/10.3390/s22239093
Marcano M, Tango F, Sarabia J, Chiesa S, Pérez J, Díaz S. Can Shared Control Improve Overtaking Performance? Combining Human and Automation Strengths for a Safer Maneuver. Sensors. 2022; 22(23):9093. https://doi.org/10.3390/s22239093
Chicago/Turabian StyleMarcano, Mauricio, Fabio Tango, Joseba Sarabia, Silvia Chiesa, Joshué Pérez, and Sergio Díaz. 2022. "Can Shared Control Improve Overtaking Performance? Combining Human and Automation Strengths for a Safer Maneuver" Sensors 22, no. 23: 9093. https://doi.org/10.3390/s22239093
APA StyleMarcano, M., Tango, F., Sarabia, J., Chiesa, S., Pérez, J., & Díaz, S. (2022). Can Shared Control Improve Overtaking Performance? Combining Human and Automation Strengths for a Safer Maneuver. Sensors, 22(23), 9093. https://doi.org/10.3390/s22239093