A Sliding Mode Observer Approach for Attack Detection and Estimation in Autonomous Vehicle Platoons using Event Triggered Communication
Summary (2 min read)
- The reliance of CACC platoons on inter-vehicle wireless communications, be it periodic or event-triggered –, may expose them to the same kind of threats as other networked control systems or Cyber-Physical Systems (CPS), such as Denial of Service (DoS), routing, replay and stealthy data injection attacks (see , ).
- While several works considered the case of event-triggered sliding mode control, such as –, the present approach would be, to the best of the authors knowledge, the first contribution considering sliding mode observers for fault, or cyber-attack detection and estimation in systems where event–triggered communication is present.
A. Error Dynamics of a Platoon using CACC
- In the present paper the authors will use the CACC formulation in  and its extension to event triggered communication introduced in , while the event-triggering condition will follow , .
- Ei and the string-stability of the platoon have been analysed in  and .
B. Attack and communication-induced effects
- The authors are not interested here in the actual implementation of the attack, for this, one can refer to –.
- (8) Here TL, TH and ∆yL ∈ R2 are user-designed parameters that define, respectively, the minimum and maximum intertriggering times, and the threshold for communication.
- In summary, communication is triggered on changes in local measurements of car i−1 since the last communication.
III. SLIDING MODE OBSERVER
- In this section a Sliding Mode Observer (SMO) for the dynamics Ei in eq. (5) is presented.
- Both are chosen to they verify the hypothesis of Theorem 1, to guarantee the SMO stability.
- This proof will only consider the upper bound of 1,i(t), the lower bound can be proved in a similar manner.
IV. ATTACK DETECTION THRESHOLDS
- As a novel contribution, the authors are introducing two pairs of robust attack detection thresholds on νi,fil, which are guaranteed against false alarms, even in the presence of measurement uncertainties and event-triggered communication.
- Each pair will comprise an upper and a lower bound on the values of νi,fil in non-attacked conditions.
- The two pairs are termed One-Switch-Ahead (OSA) and Multiple-SwitchesAhead (MSA) thresholds, for reasons that will be apparent in next sections.
- For brevity, the authors will derive only the upper bound of each threshold, which is of interest in the odd time intervals, as the lower bounds and the behaviour during even time intervals can be obtained via similar reasoning.
A. One-Switch-Ahead (OSA) Threshold
- Let us consider the behaviour of νi,fil during the odd interval, [t2k t2k+1] .
- This re-initialisation on the signal the threshold is attempting to bound leads to inconsistent detection.
B. Multiple-Switches-Ahead (MSA) Threshold
- The MSA threshold is based on the possible behaviour of νfil over more than one switch ahead in time, after a hypothetical occurrence of the worst case behaviour considered for the OSA threshold.
- Furthermore, ν̄i,fil,OSA(t2k) will only become the threshold if it is lower then the ν̄i,fil,MSA(t2k).
C. Threshold for Event Triggered Communication
- In case of event triggered communication, ∆ui−1 includes both the attack φi, and the communication-induced effect ∆uC,i−1 as defined in Section II-B.
- The proposed modification to the threshold will prevent this.
- Just like the attack, the communication error affects the observer through the dynamics of 2,i, and thus the threshold through ̄2,i .
- This worst case is when the maximum communication error ∆ūC,i−1 , ũi−1(τl) − ũi−1(τl−1) occurs constantly since the last communication.
- This scenario is implemented by computing all the terms needed for the threshold, using ̄2,i where ∆ui−1 = ∆ūC,i−1 for every t2k in the period [τl−1 τl].
V. ATTACK ESTIMATE
- In this section some preliminary results will be introduced toward the goal of estimating the attack term φ.
- This approach is valid only for the case without measurement uncertainty and with continuous observer dynamics.
VI. SIMULATION RESULT
- A CACC-controlled platoon of three vehicles using event triggered communication, equipped with the sliding mode observer presented in this paper, is implemented in Matlab/Simulink.
- The parameters used in the simulation are shown in tables I and II.
- The detection delays in these scenarios are 0.23 [s] and 0.6 [s], for the Continuous and Event triggered communication respectively.
- This detection time is scenario specific and depends on many parameters, including the attack and noise magnitudes, and the observer design parameters.
VII. CONCLUDING REMARKS
- Event-triggered Vehicle to Vehicle communication protocol based on the ETSI ITS G5 standard.
- This is combined with an adaptive threshold that is robust against false detection.
- This is done by combining the One-Switch-Ahead and the Multiple-SwitchesAhead thresholds.
- A second theoretical result was provided regarding the stability of the SMO under measurement uncertainties and event-triggered communication.
- Simulation results verified the expected behaviour and robustness of the proposed solution, and showed that attack estimation could be attained in practice also under non-ideal conditions.
Did you find this useful? Give us your feedback
Cites background from "A Sliding Mode Observer Approach fo..."
...Attack detection and resilient platooning operation are further investigated in ,  ....
...Vehicle platooning is a great example of such research focus, where the platoon vehicles can detect a malicious member and take decisions without any input from the node under attack ,  ,  , ....
"A Sliding Mode Observer Approach fo..." refers background in this paper
...The reliance of CACC platoons on inter-vehicle wireless communications, be it periodic or event-triggered –, may expose them to the same kind of threats as other networked control systems or Cyber-Physical Systems (CPS), such as Denial of Service (DoS), routing, replay and stealthy data injection attacks (see , )....
"A Sliding Mode Observer Approach fo..." refers methods in this paper
...The use of sliding mode observers for fault detection was pioneered by  and developed further by , , amongst others....
...Furthermore, as νi is a discontinuous switching term, the EOI νi,fil will be used to estimate ∆ui−1 ....
...In this paper, as in  and subsequent works on SMObased fault estimation, the EOI, derived from νi, will be used for estimating attacks ....
"A Sliding Mode Observer Approach fo..." refers background or methods in this paper
...Vehicles in a CACC platoon measure relative position and velocity of the preceding vehicle, and also communicate (see figure 1) in order to attain string stability, which is an important property resulting in dampening of velocity changes down the platoon ....
...Autonomous vehicle platoons and Cooperative Adaptive Cruise Control (CACC) are topics that received significant attention by researchers in recent years –....
...In the present paper we will use the CACC formulation in  and its extension to event triggered communication introduced in , while the event-triggering condition will follow , ....
...The stability and performance of the error dynamics Ei and the string-stability of the platoon have been analysed in  and ....
...In , a CACC control law is initially proposed in ideal conditions, as the solution to the following equation...