Yao et al., 2013 - Google Patents
Developing operating mode distribution inputs for MOVES with a computer vision–based vehicle data collectorYao et al., 2013
View PDF- Document ID
- 9324406108022891967
- Author
- Yao Z
- Wei H
- Li Z
- Ma T
- Liu H
- Yang Y
- Publication year
- Publication venue
- Transportation research record
External Links
Snippet
Acquisition of reliable vehicle activity inputs to the US Environmental Protection Agency's MOVES (Motor Vehicle Emission Simulator) model is necessary for maximizing modeling capacity and helping federal and state officials improve the quality of transportation …
- 230000000694 effects 0 abstract description 23
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/015—Detecting movement of traffic to be counted or controlled with provision for distinguishing between two or more types of vehicles, e.g. between motor-cars and cycles
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
- G06K9/00791—Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR
- G01M17/00—Testing of vehicles
- G01M17/007—Testing of vehicles of wheeled or endless-tracked vehicles
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Moers et al. | The exid dataset: A real-world trajectory dataset of highly interactive highway scenarios in germany | |
Peng et al. | Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures | |
Morris et al. | Real-time video-based traffic measurement and visualization system for energy/emissions | |
CN103559791B (en) | A kind of vehicle checking method merging radar and ccd video camera signal | |
CN103714363B (en) | A kind of motor vehicle exhaust smoke video identification system | |
JP6713505B2 (en) | Pavement information collection and inspection system, pavement information collection and inspection method, and program | |
CN111179300A (en) | Method, apparatus, system, device and storage medium for obstacle detection | |
Yao et al. | Developing operating mode distribution inputs for MOVES with a computer vision–based vehicle data collector | |
CN102013159A (en) | High-definition video detection data-based region dynamic origin and destination (OD) matrix acquiring method | |
CN105608431A (en) | Vehicle number and traffic flow speed based highway congestion detection method | |
Lv et al. | Automatic vehicle-pedestrian conflict identification with trajectories of road users extracted from roadside LiDAR sensors using a rule-based method | |
CN103456172A (en) | Traffic parameter measuring method based on videos | |
CN103325255A (en) | Regional traffic condition detection method based on photogrammetric technology | |
CN103679214B (en) | Vehicle checking method based on online Class area estimation and multiple features Decision fusion | |
CN103528531A (en) | Intelligent Internet of Things image detection system for small vehicle parameters | |
CN114771548A (en) | Data logging for advanced driver assistance system testing and verification | |
Tarko et al. | Tscan: Stationary lidar for traffic and safety studies—object detection and tracking | |
JP3816747B2 (en) | Vehicle type discriminating apparatus, car type discriminating method, and storage medium storing computer readable program stored therein | |
Refai et al. | The study of vehicle classification equipment with solutions to improve accuracy in Oklahoma. | |
Chen et al. | A framework for real-time vehicle counting and velocity estimation using deep learning | |
CN112037536A (en) | Vehicle speed measuring method and device based on video feature recognition | |
Viti et al. | Speed and acceleration distributions at a traffic signal analyzed from microscopic real and simulated data | |
Scora et al. | Real-time roadway emissions estimation using visual traffic measurements | |
Anderson-Trocmé et al. | Performance evaluation and error segregation of video-collected traffic speed data | |
WO2022233099A1 (en) | Networked adas-based method for investigating spatial-temporal characteristics of road area traffic violation behavior |