Browsing by Author "Acarman, Tankut"

Now showing 1 - 2 of 2

Citation Count: 81
Extremum-Seeking Control of ABS Braking in Road Vehicles With Lateral Force Improvement
(Ieee-inst Electrical Electronics Engineers inc, 2014) Dincmen, Erkin; Guvenc, Bilin Aksun; Acarman, Tankut
An ABS control algorithm based on extremum seeking is presented in this brief. The optimum slip ratio between the tire patch and the road is searched online without having to estimate road friction conditions. This is achieved by adapting the extremum-seeking algorithm as a self-optimization routine that seeks the peak point of the tire force-slip curve. As an additional novelty, the proposed algorithm incorporates driver steering input into the optimization procedure to determine the operating region of the tires on the "tire force"-"slip ratio" characteristic-curve. The algorithm operates the tires near the peak point of the force-slip curve during straight line braking. When the driver demands lateral motion in addition to braking, the operating regions of the tires are modified automatically, for improving the lateral stability of the vehicle by increasing the tire lateral forces. A validated, full vehicle model is presented and used in a simulation study to demonstrate the effectiveness of the proposed approach. Simulation results show the benefits of the proposed ABS controller.
Citation Count: 7
Prediction of Risk Generated by Different Driving Patterns and Their Conflict Redistribution
(Ieee-inst Electrical Electronics Engineers inc, 2018) Gunduz, Gultekin; Yaman, Cagdas; Peker, Ali Ufuk; Acarman, Tankut
In this paper, risk level correlation and classification using belief functions based on driving activities' data about sharp transient maneuvering tasks, legal speed exceeding, and average speed ensuing with the human being who is controlling the technical system, i.e., the car, is presented. A dataset is constituted by time stamped and geographically referenced driving maneuver information, which is exceptionally reported when an acceleration exceeds the given threshold in both longitudinal and lateral direction. Risk level is labeled in terms of the change in total vehicle collision property damage cost for the analyzed time period, and long term driving activities' magnitude and frequency is divided into two equal time periods, which are used to predict risk levels. Redistribution of conflicts generated by driving activities is used to predict the future risk level of involvement in an accident. Using fuzzy approach a microaveraged F-measure 90.98% is achieved by Dubois-Parade and PCR6 conflict redistribution methods.