Negligence of a driver or a sudden stop of a forward vehicle can cause rear-end collision. In this paper, we propose a new situation assessment algorithm to determine collision probability to prevent the rear-end collision. The proposed algorithm consists of two phases: coarse assessment and fine assessment. In the coarse assessment, the algorithm selects a target vehicle with the highest possibility of collision by using fuzzy logic. In fine assessment, it determines collision probability based on a statistical approach considering driving maneuvers; it models the driving maneuvers to enable the driver to operate the vehicle in conditions toward the collision and calculates the collision probability as the ratio between the total driving maneuvers and the driving maneuvers in possible collisions. To reduce the simulation time complexity, we adapt a neural network. Since there exist variance of widths for different vehicles, we also apply neural network ensemble to cope with the variance. Numerical evaluation of the proposed method is provided through simulations and practical tests.
|Title of host publication||2016 IEEE Intelligent Vehicles Symposium, IV 2016|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|Publication status||Published - 2016 Aug 5|
|Event||2016 IEEE Intelligent Vehicles Symposium, IV 2016 - Gotenburg, Sweden|
Duration: 2016 Jun 19 → 2016 Jun 22
|Name||IEEE Intelligent Vehicles Symposium, Proceedings|
|Other||2016 IEEE Intelligent Vehicles Symposium, IV 2016|
|Period||16/6/19 → 16/6/22|
Bibliographical notePublisher Copyright:
© 2016 IEEE.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Automotive Engineering
- Modelling and Simulation