A channel awareness vehicle detector
IEEE Transactions on Intelligent Transportation Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A situation-adaptive lane-keeping support system: overview of the SAFELANE approach
IEEE Transactions on Intelligent Transportation Systems
Intelligent automatic overtaking system using vision for vehicle detection
Expert Systems with Applications: An International Journal
Distributed wireless sensing-based routing and adaptive least-travel-time navigation in VANET
International Journal of Ad Hoc and Ubiquitous Computing
Recent progress in road and lane detection: a survey
Machine Vision and Applications
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In this paper, an intelligent automated lane-keeping system is proposed and implemented on our vehicle platform, i.e., TAIWAN i TS-1. This system challenges the online integrating heterogeneous systems such as a real-time vision system, a lateral controller, in-vehicle sensors, and a steering wheel actuating motor. The implemented vision system detects the lane markings ahead of the vehicle, regardless of the varieties in road appearance, and determines the desired trajectory based on the relative positions of the vehicle with respect to the center of the road. To achieve more humanlike driving behavior such as smooth turning, particularly at high levels of speed, a fuzzy gain scheduling (FGS) strategy is introduced to compensate for the feedback controller for appropriately adapting to the SW command. Instead of manual tuning by trial and error, the methodology of FGS is designed to ensure that the closed-loop system can satisfy the crossover model principle. The proposed integrated system is examined on the standard testing road at the Automotive Research and Testing Center (ARTC)1 and extra-urban highways.