Self-organized traffic control

Ferreira, Michel; Fernandes, Ricardo; Conceição, Hugo; Viriyasitavat, Wantanee; Tonguz, O.K.

doi:10.1145/1860058.1860077

Cited by 172 publications

(153 citation statements)

References 9 publications

Supporting

Mentioning

143

Contrasting

Unclassified

Order By: Relevance

“…Epipolar e a and e b can be used to eliminate those objects that are not occluded by vehicle B. The blending method is similar to [14]. The blending weight is adjusted to use more color from the front image B close to fusion center and more color from the back image A away from center toward the edge of the circle.…”

Section: Object-based Data Fusionmentioning

confidence: 99%

“…In Figure 9, red box is the groundtruth bounding box, yellow box is the result of [14] method, and green box is the result of our method. Figure 10 reveals the projection results based on different fusion methods.…”

Section: Affine Transformationmentioning

confidence: 99%

“…As to the collaborative method, [12,13] employed location information of vehicles which is periodically exchanged to prevent potential danger in advance. Similarly, [14,15] adopted the route data coming from a conventional navigation system. But drivers are not sensitive to digital information.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Occluded Street Objects Perception Algorithm of Intelligent Vehicles Based on 3D Projection Model

Liu

Wei

2018

Journal of Advanced Transportation

View full text Add to dashboard Cite

We present a super perception system of intelligent vehicles for perceiving occluded street objects by collecting images from neighbor front vehicles V2V (vehicle to vehicle) video streams based on 3D projection model. This super power can avoid some serious accidents of driver-assistant systems or automatic driving systems which can only detect visible objects. Our street perception system can "see through" the front vehicles to realize detecting of the occluded street objects only by analyzing the pair images received from front and host (back) vehicles. Upon the 3D projection model based on the pair images, the system uses affine transformation to achieve augmented reality method to increase the visibility perspective of driver system. Experimental results on different datasets are shown to validate our approach. Evaluation method was first introduced into our perception system.

show abstract

Section: Object-based Data Fusionmentioning

confidence: 99%

Section: Affine Transformationmentioning

confidence: 99%

See 1 more Smart Citation

Occluded Street Objects Perception Algorithm of Intelligent Vehicles Based on 3D Projection Model

Liu

Wei

2018

Journal of Advanced Transportation

View full text Add to dashboard Cite

show abstract

“…Priority management scheme proposed in this paper is based on the self-organized traffic control paradigm first proposed in [1]. It was shown later that this self-organized traffic control paradigm is an instance or example of biologically-inspired solutions to several fundamental transportation problems [2].…”

Section: Introductionmentioning

confidence: 99%

“…Main objective of these applications is to direct normal traffic around an accident area; but not to assist emergency response team to the scene of accident. Using the self-organized traffic control paradigm first proposed in [1], we propose the use of DSRC and VANET technologies to enable an active and post-incident safety application that aims at facilitating and prioritizing the motion of emergency vehicles (EVs) through traffic in urban areas. It has been shown that in the case of fire incidents, a reduction in response time by minutes or even seconds (e.g., time after the fire is detected and reported until the time the firefighters arrive at the scene) is very critical.…”

Section: Introductionmentioning

confidence: 99%

Priority Management of Emergency Vehicles at Intersections Using Self-Organized Traffic Control

Viriyasitavat

Tonguz

2012

2012 IEEE Vehicular Technology Conference (VTC Fall)

Self Cite

View full text Add to dashboard Cite

Abstract-Biologically inspired approaches have the potential to solve many of the difficult networking problems awaiting practical solutions. The recently proposed Virtual Traffic Lights (VTL) is an example (or instance) of this powerful approach for solving some fundamental transportation problems[1], [2]. The successful operation of VTL scheme ultimately depends on the local rules used by vehicles approaching an intersection for establishing a leader which manages the traffic at that intersection by serving as a virtual traffic light. In this paper, it is shown that by using a different set of local rules at intersections, one can support priority management of emergency vehicles in a self-organized manner. The proposed VTL-Priority Intersection Control (VTL-PIC) protocol can detect the presence of an emergency vehicle and assign priority to the emergency vehicle at an intersection. Large-scale simulation results show that while the travel time of emergency vehicles can be reduced significantly, the impact of the proposed algorithm on the travel time of other vehicles is negligible.

show abstract

Energy Saving Potentials of CAVs

Sciarretta¹,

Vahidi

2019

Energy-Efficient Driving of Road Vehicles

View full text Add to dashboard Cite

Self-organized traffic control

Cited by 172 publications

References 9 publications

Occluded Street Objects Perception Algorithm of Intelligent Vehicles Based on 3D Projection Model

Occluded Street Objects Perception Algorithm of Intelligent Vehicles Based on 3D Projection Model

Priority Management of Emergency Vehicles at Intersections Using Self-Organized Traffic Control

Energy Saving Potentials of CAVs

Contact Info

Product

Resources

About