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.

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.

scholarly journals ROUTE PLANNING METHODOLOGY OF AN ADVANCED TRAVELLER INFORMATION SYSTEM IN VILNIUS CITY

Transport ◽  
2010 ◽  
Vol 25 (2) ◽  
pp. 171-177 ◽  
Author(s):  
Marius Jakimavičius ◽  
Marija Burinskienė
Keyword(s):  
Information System ◽  
Traffic Congestion ◽  
Intelligent Transportation System ◽  
Service Providers ◽  
Information Service ◽  
Route Planning ◽  
Traffic Information ◽  
Real Time Traffic ◽  
Driving Time ◽  
Planning Methodology

As a subsystem of an Intelligent Transportation System (ITS), an Advanced Traveller Information System (ATIS) disseminates real‐time traffic information to travellers. To help them with making better decisions on choosing their routes, a strong need to predict traffic congestion and to disseminate the predicted congestion information relating to travellers can be seen. This paper describes a methodology used by drivers for calculating an optimal driven route in Vilnius. The paper discusses how ATIS systems will likely evolve the experience of Information Service Providers (ISP) and optimal route planning calculations. A few methods of route planning have been taken into account. The paper presents the following types of route calculation: 1) the shortest route; 2) the quickest route; 3) the quickest forecasted route according to historical traffic information. Also, the paper deals with the architecture of the WEB based information system for drivers in Vilnius and analyzes data on traffic workflow. Furthermore, a comprehensive route planning procedure that forecasts data on driving time considering historical traffic is followed.

Evaluation of Effectiveness of Automated Work Zone Information Systems

2005 ◽  
Vol 1911 (1) ◽  
pp. 73-81 ◽  
Author(s):  
Lianyu Chu ◽  
Hee-Kyung Kim ◽  
Younshik Chung ◽  
Will Recker
Keyword(s):  
Information Processing ◽  
Information Systems ◽  
Traffic Flow ◽  
Intelligent Transportation System ◽  
Processing System ◽  
Intelligent Transportation ◽  
Work Zone ◽  
Traffic Information ◽  
Real Time Traffic ◽  
Pass Through

With the advancement of the intelligent transportation system technologies, some automated work zone information systems (AWISs) have been developed and deployed in the field. Their purpose is to provide useful real-time traffic information to motorists as they approach or pass through a work zone. Several studies have been conducted to evaluate AWIS, and most of those studies paid attention to the evaluation of system functionality and reliability. This paper focuses on the evaluation of the effectiveness of the computerized highway information processing system deployed in Southern California, pertaining to the aspects of safety and diversion effects, as well as travelers’ acceptance. Evaluation results showed most driver survey respondents liked the system, which was found to be effective in diverting traffic and promoting smoother traffic flow during congested periods.

PENGEMBANGAN ”REAL TIME TRAFFIC INFORMATION SYSTEM” BAGI PENGGUNA JALAN

2013 ◽  
Vol 12 (3) ◽  
Author(s):  
Rusmadi Suyuti
Keyword(s):  
Information System ◽  
Real Time ◽  
Travel Demand ◽  
Urban Traffic ◽  
Road User ◽  
Traffic Information ◽  
Estimation Methods ◽  
Traffic Counts ◽  
Real Time Traffic ◽  
Demand Models

Traffic information condition is a very useful  information for road user because road user can choose his best route for each trip from his origin to his destination. The final goal for this research is to develop real time traffic information system for road user using real time traffic volume. Main input for developing real time traffic information system is an origin-destination (O-D) matrix to represent the travel pattern. However, O-D matrices obtained through a large scale survey such as home or road side interviews, tend to be costly, labour intensive and time disruptive to trip makers. Therefore, the alternative of using traffic counts to estimate O-D matrices is particularly attractive. Models of transport demand have been used for many years to synthesize O-D matrices in study areas. A typical example of the approach is the gravity model; its functional form, plus the appropriate values for the parameters involved, is employed to produce acceptable matrices representing trip making behaviour for many trip purposes and time periods. The work reported in this paper has combined the advantages of acceptable travel demand models with the low cost and availability of traffic counts. Two types of demand models have been used: gravity (GR) and gravity-opportunity (GO) models. Four estimation methods have been analysed and tested to calibrate the transport demand models from traffic counts, namely: Non-Linear-Least-Squares (NLLS), Maximum-Likelihood (ML), Maximum-Entropy (ME) and Bayes-Inference (BI). The Bandung’s Urban Traffic Movement survey has been used to test the developed method. Based on several statistical tests, the estimation methods are found to perform satisfactorily since each calibrated model reproduced the observed matrix fairly closely. The tests were carried out using two assignment techniques, all-or-nothing and equilibrium assignment.  

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