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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Safe Optimization of Highway Traffic With Robust Model Predictive Control-Based Cooperative Adaptive Cruise Control

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Author(s):
Massera Filho, Carlos [1] ; Terra, Marco H. [2] ; Wolf, Denis F. [1]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Inst Math & Comp Sci, Sao Paulo - Brazil
[2] Univ Sao Paulo, Sao Carlos Sch Engn, Sao Paulo - Brazil
Total Affiliations: 2
Document type: Journal article
Source: IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS; v. 18, n. 11, p. 3193-3203, NOV 2017.
Web of Science Citations: 15
Abstract

Road traffic crashes have been the leading cause of death among young people. Most of these accidents occur when the driver becomes distracted due to fatigue or external factors. Vehicle platooning systems, as cooperative adaptive cruise control, are one of the results of efforts devoted to the development of technologies for decreasing the number of road crashes and fatalities. Previous studies have suggested that such systems improve up to 273% highway traffic throughput and over 15% of fuel consumption if the clearance between vehicles in this class of roads can be reduced to 2 m. In this paper, we propose an approach that guarantees a minimum safety distance between vehicles taking into account the overall system delays and braking capacity of each vehicle. An l infinity-norm robust model predictive controller has been developed to guarantee the minimum safety distance is not violated due to uncertainties on the preceding vehicle behavior. A formulation for a lower bound clearance of vehicles inside a platoon is also proposed. Simulation results show the performance of the approach compared to a nominal controller when the system is subject to both modeled and unmodeled disturbances. (AU)

FAPESP's process: 13/24542-7 - Project CARINA: localization and control
Grantee:Denis Fernando Wolf
Support type: Regular Research Grants