Car-Following-Models/ACC

generated on 2019-05-22 00:18:48.987025 from the wiki page for Car-Following-Models/ACC for SUMO git

Overview

The integrated ACC car-following model is based on the work of Milanés & Shladover [1] and Xiao, Wang & van Arem [2], 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 preceding vehicles exist in a spacing larger of 120 m.

Gap control mode

The gap control mode aims to maintain a constant time gap between the ACC-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 spacing to the preceding vehicle is smaller than 100 m. If the spacing is between 100 m and 120 m, the ACC-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 spacing to the preceding vehicle is smaller than 100 m and the gap deviation is negative.

Notes

  • The implemented model can be found in <SUMO_HOME>/src/microsim/cfmodels/MSCFModel_ACC.cpp.
  • Literature on the developed ACC driving model and its implementation can be found here.
  • This part of SUMO was developed and extended within the project TransAID.
  • The model is primarily intended for use in specific traffic situations.

References

  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. https://doi.org/10.1016/j.trc.2014.09.001
  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. https://doi.org/10.3141/2623-01