Real time detection of the back view of a preceding vehicle for automated heterogeneous platoons in unstructured environment using video

Alfraheed, Mohammad; Dröge, Alicia; Kunze, Ralph; Klingender, Max; Schilberg, Daniel; Jeschke, Sabina

doi:10.1007/978-3-642-33389-7_45

Cited by 2 publications

(10 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this context, NClasses (0, 1, 2 or greater than 2) represents how many clusters are generated from the step Group rectangle. This step distinguishes itself from the similar step in the detection process [12] through the Automatic Confirmation Process. It is enabled automatically when the detected size is less than 80 pixels.…”

Section: G Group Rectanglementioning

confidence: 98%

“…In case the driver's response is negative the detection process is run again within 0. 03 to 0.089 seconds [12].…”

Section: A Detection Modulementioning

confidence: 99%

“…At the beginning, the BVPV is detected based on the agent introduced in [12]. Therein the two dimension coordinates of the detected back view are generated and sent to a manual confirmation process.…”

Section: A Detection Modulementioning

confidence: 99%

“…In an earlier publication [12], a detection method applicable for AHS was presented based on a machine learning algorithm (called AdaBoost [14]), taking the BVPV as a reference point for the longitudinal and lateral controls.The detection method distinguished itself from other available detection methods (discussed in section 3) through its ability to work under real time constraints. Moreover, the detection method can locate the BVPV even if it is not clearly visible due to environmental effects (i.e.…”

Section: Realization Of the Back View Detectionmentioning

confidence: 99%

“…Details about detection process, which runs prior to the tracking process, have already been published [12] , but will be discussed shortly in section 2, since the tracking process builds up on it. The developed method of the tracking process is presented in section 3 and a real test of both processes is described in section 4, concluding with a summary in section 5.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Automated heterogeneous platoons in unstructured environment: Real time tracking of a preceding vehicle using video stream

Alfraheed

Dröge

Schilberg

et al. 2014

2014 5th International Conference on Information and Communication Systems (ICICS)

Self Cite

View full text Add to dashboard Cite

In autonomous driving, object tracking is necessary to gather actual information about the object of interest. The longitudinal and lateral controls of automated highway systems need a target object not only to maintain the safety distance between vehicles but also to keep the following vehicle in the same track as the preceding vehicle. So far automated highway systems were only developed for urban and highway environment depending on lane markings. In future, their application should be extended to unstructured environments (e.g. desert) and be adapted for heterogeneous vehicles. In this paper an approach towards this is presented, where the back view of preceding vehicle is the target object. This solution is independent from the environmental structure as well as additional equipment like infrared emitters. In this paper, the tracking process of the back view is discussed using video streams recorded by a stereo vision system. For an accurate and fast tracking in unstructured environment and with heterogeneous platoons the proposed method is a supplement to the detection process. Therefore, the tracking process has to be a) applicable under real time constraints and b) adaptable in dynamic environments. Compared to other methods related to object detection and tracking, the proposed method reduces the running time for the tracking of the back view from reported 12 -30 to 16 -66 frame/s.

show abstract

Section: G Group Rectanglementioning

confidence: 98%

“…In case the driver's response is negative the detection process is run again within 0. 03 to 0.089 seconds [12].…”

Section: A Detection Modulementioning

confidence: 99%

Section: A Detection Modulementioning

confidence: 99%

Section: Realization Of the Back View Detectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Automated heterogeneous platoons in unstructured environment: Real time tracking of a preceding vehicle using video stream

Alfraheed

Dröge

Schilberg

et al. 2014

2014 5th International Conference on Information and Communication Systems (ICICS)

Self Cite

View full text Add to dashboard Cite

show abstract

A mechanism to improve Stereo Vision Systems in automated heterogeneous platoons

Alfraheed¹,

Droge²,

Klingender³

et al. 2012

2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Self Cite

View full text Add to dashboard Cite

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.

show abstract

Real time detection of the back view of a preceding vehicle for automated heterogeneous platoons in unstructured environment using video

Cited by 2 publications

References 12 publications

Automated heterogeneous platoons in unstructured environment: Real time tracking of a preceding vehicle using video stream

Automated heterogeneous platoons in unstructured environment: Real time tracking of a preceding vehicle using video stream

A mechanism to improve Stereo Vision Systems in automated heterogeneous platoons

Contact Info

Product

Resources

About