Advanced formation and delivery of traffic information in intelligent transportation systems

Cheng, Hsu-Yung; Gau, Victor; Huang, Chih‐Wei; Hwang, Jenq‐Neng

doi:10.1016/j.eswa.2012.01.184

Cited by 34 publications

(13 citation statements)

References 29 publications

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“…Accurate and robust prediction of these parameters (i.e., speed, travel time (TT), flow, occupancy) is a critical problem that any improvement would yield more efficient transportation management and control strategies. For instance, better real-time dynamic routing can result in avoiding congestion or finding the fastest way to a destination for transporting people and goods (Cheng et al (2012)). On the contrary, traffic often exhibits unexpected or expected changes due to various external factors such as incidents, inclement weather, A C C E P T E D M A N U S C R I P T special events, and driver behaviors that adversely affect the performance and accuracy of prediction models.…”

Section: Introductionmentioning

confidence: 99%

Short-term freeway traffic parameter prediction: Application of grey system theory models

Bezuglov

Comert

2016

Expert Systems with Applications

177

106

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Section: Introductionmentioning

confidence: 99%

Short-term freeway traffic parameter prediction: Application of grey system theory models

Bezuglov

Comert

2016

Expert Systems with Applications

177

106

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“…The test bed of the proposed prototype of the "stop sign" depends on mean square error computations. The used dataset of this testing composed from 100 signs 5 . Figure 9 illustrates the recognition process (green rectangular) with the accuracy and execution of the recognition time of such signs in different locations.…”

Section: Sign Detectionmentioning

confidence: 99%

“…Steenbruggen and et al offered an article to manage and increase transportation safety [4] . Cheng and et al presented a smart system to increase roads safety and traffic efficiency based on video analysis [5] .…”

Section: Introductionmentioning

confidence: 99%

Intelligent Traffic Vehicles (ITV) and Road Sign Detection Systems

Al-Barhamtoshy¹,

Abdelatif²,

ElBarahamtoshy³

2018

مجلة جامعة الملك عبدالعزيز-علوم الحاسبات وتقنية المعلومات

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This paper monitors and detects the neighbor's activities in smart vehicle using computer vision technology and innovation of Internet of Things (IoT). These activities include vehicles monitoring, movement, and location status of vehicle. The proposed solution recognized vehicles neighbors and collects data from whole sensors of vehicle, vehicle engine, road info, mobile of the derivers, and analyze such data to make some decisions. The decision includes vehicles monitoring, automated accident, road safety, air pollution, and congestion reduction in road. Therefore, the paper suggests a data analysis method to model many devices and engines, based on ontology formulation and IoT technology. This in addition, modeling and managing over such places information from anywhere at any time. Accordingly, the current paper investigate and focus on ideation and assessing the potential of computer vision using vehicles and roads signs detections, to control traffic congestion in smart roads. Consequently, an intelligent traffic approach (vehicles and road signs recognitions) will be presented in real smart vehicles or drivers assistant system. Several scenarios to identify potential components of ITVS to recognize neighbor's vehicles based on ontology architecture and road signs issues will be analyzed and recognized. The paper sketches out and develops an ontology-based to represent vehicle, drivers, roads, traffic and weather, so five ontologies will be drawn and presented. Vehicle detection ontology-based with Haar features and computer vision library will be implemented and tested. Although, traffic detection is used to help and warn drivers for specific actions. Therefore, driving safety is increased and it will be comfort. The recognition task of the vehicles and the detection task of signs within the road will be developed and tested.

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“…Rather than counting solely on developing new roads or increasing road capacities, ITS utilizes advanced information and communication technologies such as real-time vehicle-tovehicle (V2V) [2] and vehicle to infrastructure (V2I) [3] communications to smooth out traffic flows and reduce road congestion. ITS provides drivers with the critical traffic information that would help improve road safety and traffic efficiency [4].…”

Section: Introductionmentioning

confidence: 99%

Optimizing Traffic Signal Settings in Smart Cities

Shahidehpour

Bahramirad

et al. 2017

IEEE Trans. Smart Grid

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Traffic signals play a critical role in smart cities for mitigating traffic congestions and reducing the emission in metropolitan areas. This paper proposes a bi-level optimization framework to settle the optimal traffic signal setting problem. The upper-level problem determines the traffic signal settings to minimize the drivers' average travel time, while the lower-level problem aims for achieving the network equilibrium using the settings calculated at the upper level. Genetic algorithm is employed with the integration of microscopic-traffic-simulation based dynamic traffic assignment (DTA) to decouple the complex bi-level problem into tractable single-level problems which are solved sequentially. Case studies on a synthetic traffic network and a real-world traffic subnetwork are conducted to examine the effectiveness of the proposed model and relevant solution methods. Additional strategies are provided for the extension of the proposed model and the acceleration solution process in large-area traffic network applications.Index Terms-Smart cities, traffic signal setting, bi-level optimization, dynamic traffic assignment.

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Advanced formation and delivery of traffic information in intelligent transportation systems

Cited by 34 publications

References 29 publications

Short-term freeway traffic parameter prediction: Application of grey system theory models

Short-term freeway traffic parameter prediction: Application of grey system theory models

Intelligent Traffic Vehicles (ITV) and Road Sign Detection Systems

Optimizing Traffic Signal Settings in Smart Cities

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