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C/ACC controller in Aimsun Next
Technical Note #63
By Martin Hartmann
October 2021
Intro
Vehicle automation attracts stakeholders that seek to predict the impacts of this technology on road traffic. The diverse stakeholder perspectives might range from high-level traffic planning policies to operational aspects for validation of perception sensors under adverse weather conditions. Aimsun covers the entire domain spectrum by offering modeling tools and services, from macroscopic models to complex real-time co-simulations of AV stacks with digital twins representing realistic traffic environments.
In this article, we explain and demonstrate the use of microscopic simulation of vehicles equipped with cooperative adaptive cruise control (CACC) in Aimsun Next. Since version 8.4, Aimsun Next has included a native implementation of the ACC and CACC algorithm (here labelled as C/ACC) developed by Milanes & Shladover, 2014 [1]. Hence, this technical note sets the controller implementation in the context of a microsimulation model, describes the parameter revealed to the user, and gives some practical examples from using the controller.
Key take-aways
C/ACC vehicles exhibit car-following behavior significantly different from the conventional (in Aimsun Next: Gipps-controlled) vehicles allowing very short time gaps within the platoons of connected vehicles. Let’s summarize the most important information about the C/ACC algorithm in context of microsimulation in Aimsun Next:
- Vehicles can be equipped either with ACC, CACC or non-equipped.
- C/ACC algorithm overwrites the default longitudinal behavior (acceleration and speed of the Gipps car-following model).
- The reaction time must be set to 0.1s for C/ACC equipped vehicles, conventional vehicles are recommended to keep their own reaction time (around 0.8s).
- Any vehicle equipped with CACC is capable of ACC. Therefore, CACC equipped vehicle following a vehicle without CACC is using ACC controller “only”.
- Additional CAMP collision avoidance algorithm keeps safe car-following gaps.
- The possibility for a vehicle to activate C/ACC and the maximum platoon size can be set in the road type.
- The resulting platooning behavior is affected by the combination of vehicles’ desired speed, max. platoon size and C/ACC controller parameters.
Controller states description
Next, there are five states that apply to a CACC-equipped vehicle:
- CC Speed regulation (“no preceding vehicle in your detection range, choose your acceleration”)
- ACC Gap regulation (“follow a preceding vehicle*, adjust acceleration to meet the desired time gap”)
- CACC Platoon Leader Gap Regulation (“max platoon size reached, you are the new leader, choose your acceleration”)
- CACC Platoon Follower Gap Regulation (“follow connected leader, adjust acceleration to meet the desired intra-platoon time gap”)
- Disabled (“no controller equipped or temporary disabled by CAMP algorithm”)
* the preceding vehicle can be a non-equipped vehicle, ACC or CACC equipped vehicle within the ACC Lower clearance threshold or CACC Lower Gap Threshold
ACC platoon parameters
- ACC controller gains: sensitivity parameters of the ACC controller on both the positioning and speed errors during free flow and following. The values are set to default values from the [1] paper and has been found to minimize the difference between the real empirical and simulated results. We recommend to most of the users to take over the default values.
- Lower clearance threshold: on- board detectors of the subject vehicle identified a leader; the subject vehicle enters the ACC Gap regulation state and tries to reach the Desired Time Gap.
- Upper clearance threshold: the leader is beyond the on-board sensors’ detection range; the subject vehicle leaves the platoon and enters the CC Speed regulation
- Desired Time Gap: the time distance between the subject vehicle and the leader within the platoon, the default value is set to the Nowakovski distribution (1,2 / 0,4 / 1,1 / 2,2s) [3].
CACC platoon parameters
- CACC controller gains: sensitivity parameters of the CACC controller adjusting the time gap between the subject vehicle and the leader.
- Current time gap > Upper Gap Threshold: the subject vehicle switches to the ACC Gap regulation state (e.g. the leader has increased its desired speed and is beyond the connectivity range).
- Current time gap < Lower Gap Threshold: the subject vehicle switches to the CACC Platoon Follower Gap Regulation state aiming for the intra-platoon Time Gap Follower (default 0,6s).
- Current time gap < Upper Gap Threshold & Max platoon size is reached ® the subject vehicle become a leader of its own platoon and enters the CACC Platoon Leader Gap Regulation state aiming for the Time Gap Leader (default 1,5s).
- Time Gap between Lower & Upper Gap Threshold: the subject vehicle will use the hysteresis control rule and apply the car-following state from the previous time step.
CAMP emergency takeover
The C/ACC model in Aimsun Next employs the CAMP forward collision warning algorithm [2]. This algorithm is included in the model to check if the gap between the subject vehicle and the leader is sufficient for safe car-following. If the CAMP algorithm is activated in any point, the C/ACC controller is disabled followed by a 20s cooldown before re-entering the last C/ACC state again.
Simulation examples
- CACC equipped vehicle (in red) with no preceding vehicle ® CC speed regulation
- CACC equipped vehicle (red, desired speed = 49,9 km/h) follows a non-equipped vehicle (blue, desired speed = 57 km/h) ® ACC speed regulation until Clearance > Upper clearance threshold (120m) ® CC speed regulation
Slow down the recording and highlight the Clearance and the Cruise Control Status values
Comment: You can collect individual vehicles’ time series (TS) of both values Gap to the leader (blue line) and Clearance to the leader (green line) to visualize the behavior.
- CACC equipped vehicle is connected and part of the platoon aiming for the intra-platoon Time Gap 0,6s > CACC Platoon Follower Gap Regulation
- CACC equipped vehicle with no leader (CC Speed regulation active) shortly before identifying a new preceding vehicle. After the Clearance drops below the Lower Clearance Threshold of 100m, the subject vehicle changes its state into the ACC Gap regulation.
Slow down the recording and highlight the Clearance and the Cruise Control Status values
- CACC equipped vehicle shortly before entering the CACC platoon: Current Time gap to go below Lower Gap Threshold of 0,5s applying the ACC Gap regulation for the moment (left image) and after entering the CACC platoon aiming for the Time Gap Follower ® CACC Platoon Follower Gap Regulation (right image).
Slow down the recording and highlight the Gap and the Cruise Control Status values
- platoon size restriction forces the subject vehicle to become a new platoon leader (left-most CACC platoon). The leader of the right-most platoon is in the ACC Gap regulation state as the preceding vehicles is closer than the Upper Clearance Threshold of 120m. After exceeding this threshold, the leader enters the CC Speed regulation state.
Closing remark
In the implemented model, a true platoon leader can be labelled with different CACC Control Status tags (even with platoon size = 1):
- CACC Platoon Leader: if the Max Platoon Size forces the vehicle to create a new platoon,
- ACC Gap Regulation: if the platoon leader is within the sensor range to a preceding vehicle,
- CC Speed Regulation: if the platoon leader is outside of the sensor range to a preceding vehicle.
References
[1] Vicente Milanés, Steven E. Shladover. Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data. Transportation research. Part C, Emerging technologies, Elsevier, 2014, pp.285-300. 10.1016/j.trc.2014.09.001 . hal-01091160
[2] Kiefer, R.J., Cassar, M.T., Flannagan, C.A., LeBlanc, D.J., Palmer, M.D., Deering, R.K., Shulman, M.A., 2003. Forward collision warning requirements project: refining the CAMP crash alert timing approach by examining” last-second” braking and lane change maneuvers under various kinematic conditions.NHTSA Research Report HS-809 574.
[3] Nowakowski, C., J. O’Connell, S.E. Shladover, and D. Cody, 2010, “Cooperative Adaptive Cruise Control: Driver Selection of Car-Following Gap Settings Less Than One Second”, 54th Annual Human Factors and Ergonomics Society Meeting, San Francisco, CA.
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