Wireless sensor networks: Traffic information providers for intelligent transportation system

2010 ◽  
Author(s):  
Chao Long ◽  
Meng Shuai
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Wireless Sensor ◽  
Traffic Information ◽  
Information Providers

scholarly journals 3D Digital Twin of Intelligent Transportation System based on Road-Side Sensing

2021 ◽  
Vol 2083 (3) ◽  
pp. 032022
Author(s):  
Yunpeng Guo ◽  
Kai Zou ◽  
Shengdong Chen ◽  
Feng Yuan ◽  
Fang Yu
Keyword(s):  
Virtual World ◽  
Intelligent Transportation System ◽  
Road Traffic ◽  
Intelligent Transportation ◽  
Physical World ◽  
Transportation System ◽  
Traffic Information ◽  
Digital Twin ◽  
Twin System ◽  
Infrastructure System

Abstract Cooperative vehicle-infrastructure is one of the most import developing direction of future intelligent transportation system, while digital twin system can record, reproduce, and even deduce the physical system, which could be helpful for the development of cooperative vehicle-infrastructure. In this study, we proposed a 3D digital twin platform of intelligent transportation system based on road-side sensing, a core component of cooperative vehicle-infrastructure system. This platform consists of real road-side sensing unit,3D virtual environment, and the ROS bridge between them, by receiving the sensing results of physical world in real-time, the virtual world can reproduce the compatible road traffic information, such as the type,3D position and orientation of traffic participants.

Fuel-optimal path finding algorithm using traffic information at urban intersection

2019 ◽  
Author(s):  
Jooin Lee ◽  
Hyeongcheol Lee
Keyword(s):  
Fuel Consumption ◽  
Intelligent Transportation System ◽  
Optimal Path ◽  
Intelligent Transportation ◽  
Transportation System ◽  
Traffic Model ◽  
Traffic Information ◽  
Traffic Condition ◽  
Decision Algorithm ◽  
The Road

Intelligent Transportation System (ITS) is actively studied as the sensor and communication technology in the vehicle develops. The Intelligent Transportation System collects, processes, and provides information on the location, speed, and acceleration of the vehicles in the intersection. This paper proposes a fuel optimal route decision algorithm. The algorithm estimates traffic condition using information of vehicles acquired from several ITS intersections and determines the route that minimizes fuel consumption by reflecting the estimated traffic condition. Simplified fuel consumption models and road information (speed limit, average speed, etc.) are used to estimate the amount of fuel consumed when passing through the road. Dynamic Programming (DP) is used to determine the route that fuel consumption can be minimized. This algorithm has been verified in an intersection traffic model that reflects the actual traffic environment (Korea Daegu Technopolis) and the corresponding traffic model is modeled using AIMSUN.

A New Data Aggregation Model for Intelligent Transportation System

2013 ◽  
Vol 671-674 ◽  
pp. 2855-2859
Author(s):  
Jun Wu ◽  
Luo Zhong
Keyword(s):  
Information System ◽  
Data Aggregation ◽  
Wireless Sensors ◽  
Intelligent Transportation System ◽  
Intelligent Transportation ◽  
Transportation System ◽  
System Model ◽  
Traffic Information ◽  
Real Time Traffic ◽  
Aggregation Problem

Intelligent Transportation System is a new kind of complicated information system which includes many different wireless sensors. With the development in sensor technologies and their applications, it is important to focus on how to find the useful and real-time traffic information from the Intelligent Transportation System. Using this method of building dynamical data system model for the Intelligent Transportation System is the way to solve the data aggregation problem and minimize the number of the multi-sources data.

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