Due to the increase in road transportation several projects concerning automated highway systems were initiated to optimize highway capacity. In the future, the developed techniques should be applicable in unstructured environment (e.g. desert) and adaptable for heterogeneous vehicles. But before, several challenges, i.e. independency of lane markings, have to be overcome. Our solution is to consider the back view of the preceding vehicle as a reference point for the lateral and longitudinal control of the following vehicle. This solution is independent from the environmental structure as well as additional equipment like infrared emitters. Thus, both the detection and tracking process of the back view are needed to provide automated highway systems with the distance and the deviation degree of the preceding vehicle. In this paper the first step, the detection and location of the back view on video streams, is discussed. For a definite detection in a heterogeneous platoon several features of the back view are detected. A method is proposed to run rejection cascades generated by the AdaBoost classifier theory on the video stream. Compared to other methods related to object detection, the proposed method reduces the running time for the detection of the back view to 0.03-0.08 s/frame. Furthermore, the method enables a more accurate detection of the back view.
Due to their low price and good quality, Stereo Vision Systems (SVS) are recently considered as a key factor to gather actual information about the object of interest. Today, automated highway systems (AHS) for urban and highway environment were developed without the use of a stereo vision system. In future, the application of AHS should be extended to unstructured environments (e.g. desert) and be adapted to heterogeneous vehicles. In this context, the stereo vision system could enable the platoon to be independent from environmental structure (e.g. lane markings) through its ability to detect, track, locate and recognize heterogeneous vehicles. So far, the need for high accuracy prevents SVS to be applied in automated heterogeneous platoon. In this paper a mechanism towards this is presented, where some behavioral properties have to be satisfied in terms of unstructured environment and heterogeneous platoons. Within a heterogeneous platoon, the back view of a preceding vehicle (BVPV) is considered as a reference point for the lateral and longitudinal control. The key idea of the proposed mechanism is to confirm that the distance of the BVPV can be extracted without depending on the movement of the preceding vehicle. Furthermore, the proposed mechanism has to ensure that features extracted from the back view are suitable to implement successfully the calibration process at around 10m distance. With the proposed SVS mechanism some of behavioral properties have to be satisfied in terms of unstructured environment and AHS. These properties are reliability, performance and robustness. Compared to other methods which use a SVS, the proposed mechanism distinguishes itself through adapting to dynamic environment and extracting the necessary features for the calibration process.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.