The integrated CACC car-following model is based on the work of Milanés & Shladover , Xiao, Wang & van Arem  and Xiao, Wang, Schakel & van Arem , wherein the developed control law in the ACC control algorithm is explicitly divided into three modes: (i) speed (or cruising) control, (ii) gap-closing control and (iii) gap control. A fourth mode (i.e. collision avoidance mode) has been introduced within the project TransAID.
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.
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.
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.
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.
- 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.
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.
- 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. https://doi.org/10.1016/j.trc.2014.09.001
- 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. https://doi.org/10.3141/2623-01
- 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. https://doi.org/10.1016/j.trc.2018.10.008