Assuring Accuracy on Low Penetration Rate Mobile Phone-Based Traffic State Estimation System

2011 ◽  
Author(s):  
Quang Tran Minh ◽  
Eiji Kamioka
Keyword(s):  
Mobile Phone ◽  
State Estimation ◽  
Penetration Rate ◽  
Traffic State ◽  
Traffic State Estimation ◽  
Estimation System

MC-TES: An Efficient Mobile Phone Based Context-Aware Traffic State Estimation Framework

2013 ◽  
Vol 21 (1) ◽  
pp. 76-89 ◽  
Author(s):  
Quang Tran Minh ◽  
Muhammad Ariff Baharudin ◽  
Eiji Kamioka
Keyword(s):  
Mobile Phone ◽  
State Estimation ◽  
Context Aware ◽  
Traffic State ◽  
Traffic State Estimation

scholarly journals Effect of Enhanced ADAS Camera Capability on Traffic State Estimation

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 1996
Author(s):  
Hoe Kyoung Kim ◽  
Younshik Chung ◽  
Minjeong Kim
Keyword(s):  
State Estimation ◽  
Traffic Engineering ◽  
Flow Density ◽  
Microscopic Simulation ◽  
Traffic Demand ◽  
Traffic System ◽  
Traffic Conditions ◽  
Traffic State ◽  
Vehicle Identification ◽  
Traffic State Estimation

Traffic flow data, such as flow, density and speed, are crucial for transportation planning and traffic system operation. Recently, a novel traffic state estimating method was proposed using the distance to a leading vehicle measured by an advanced driver assistance system (ADAS) camera. This study examined the effect of an ADAS camera with enhanced capabilities on traffic state estimation using image-based vehicle identification technology. Considering the realistic distance error of the ADAS camera from the field experiment, a microscopic simulation model, VISSIM, was employed with multiple underlying parameters such as the number of lanes, traffic demand, the penetration rate of ADAS vehicles and the spatiotemporal range of the estimation area. Although the enhanced functions of the ADAS camera did not affect the accuracy of the traffic state estimates significantly, the ADAS camera can be used for traffic state estimation. Furthermore, the vehicle identification distance of the ADAS camera and traffic conditions with more lanes did not always ensure better accuracy of the estimates. Instead, it is recommended that transportation planners and traffic engineering practitioners carefully select the relevant parameters and their range to ensure a certain level of accuracy for traffic state estimates that suit their purposes.

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