The integrated CACC car-following model is based on the work of Milanés & Shladover [1], Xiao, Wang & van Arem [2] and Xiao, Wang, Schakel & van Arem [3], wherein the developed control law in the CACC control algorithm is explicitly divided into three modes: (i) speed (or cruising) control, (ii) gap control and (iii) gap-closing control. A fourth mode (i.e. collision avoidance mode) has been introduced within the project TransAID, when the CACC model was first integrated to SUMO [4].

see also ACC model.

(i) Speed control mode#

The speed control mode is designed to maintain the pre-defined by the driver desired speed and is activated when there are no preceding vehicles in the range covered by the sensors or when the time-gap is larger than 2 s.

Additionally, to ensure a smooth acceleration profile when closing in on a stopped vehicle, the speedControlMinGap is also evaluated to activate the speed control mode. (We found a default of 1.66m to be feasible.)

(ii) Gap control mode#

The gap control mode aims to maintain a constant time gap between the CACC-equipped vehicle and its predecessor and is activated when the gap and speed deviations (with respect to the preceding vehicle) are concurrently smaller than 0.2 m and 0.1 m/s, respectively.

(iii) Gap-closing control mode#

The gap-closing controller enables the smooth transition from speed control mode to gap control mode and is triggered when the time-gap is less than 1.5 s. If the time-gap is between 1.5 s and 2 s, the CACC-equipped vehicle retains the previous control strategy to provide hysteresis in the control loop and perform a smooth transfer between the two strategies.

(iv) Collision avoidance control mode#

The collision avoidance mode prevents rear-end collisions when safety critical conditions prevail. This mode is activated when the time-gap is less than 1.5 s and the gap deviation is negative.

Also, If the followSpeed computed by the CACC model grows higher than the safe followSpeed as computed by the default Krauss model by a given margin (configured by collisionAvoidanceOverride), the speed is limited to the value of Krauss-speed + margin. The override margin defaults to 2m/s.


  • The implemented model can be found in <SUMO_HOME>/src/microsim/cfmodels/MSCFModel_CACC.cpp.
  • This part of SUMO was developed and extended within the project TransAID.
  • The model is primarily intended for use in specific traffic situations.
  • When there is no leader vehicle, the model uses the same speed as the Krauss model to approach junctions and speed limits


The model is known to produce collisions at the default step-length of 1s. Better results can be achieved by setting a lower step length.


  1. Milanés, V., & Shladover, S. E. (2014). Modeling cooperative and autonomous adaptive cruise control dynamic responses using experimental data. Transportation Research Part C: Emerging Technologies, 48, pp. 285–300.
  2. Xiao, L., Wang, M., & van Arem, B. (2017). Realistic Car-Following Models for Microscopic Simulation of Adaptive and Cooperative Adaptive Cruise Control Vehicles. Transportation Research Record: Journal of the Transportation Research Board, 2623, pp. 1–9.
  3. Xiao, L., Wang, M., Schakel, W., & van Arem, B. (2018). Unravelling effects of cooperative adaptive cruise control deactivation on traffic flow characteristics at merging bottlenecks. Transportation Research Part C: Emerging Technologies, 96, 380–397.
  4. Porfyri, K. N., Mintsis, E., & Mitsakis, E. (2018). Assessment of ACC and CACC systems using SUMO. EPiC Series in Engineering, 2, 82-93.