Missing Data Compensation Model in Real-Time Traffic Information Service System

2008 ◽  
Author(s):  
Bowen Du ◽  
Leishi Xu ◽  
Dianfu Ma ◽  
Weifeng Lv ◽  
Tongyu Zhu
Keyword(s):  
Missing Data ◽  
Real Time ◽  
Service System ◽  
Information Service ◽  
Traffic Information ◽  
Compensation Model ◽  
Real Time Traffic

Real Time Traffic Information Service Using Terrestrial Digital Multimedia Broadcasting System

2006 ◽  
Vol 52 (4) ◽  
pp. 550-556 ◽  
Author(s):  
Sammo Cho ◽  
Kim Geon ◽  
Youngho Jeong ◽  
Chung-Hyun Ahn ◽  
Soo In Lee ◽  
...  
Keyword(s):  
Real Time ◽  
Information Service ◽  
Traffic Information ◽  
Digital Multimedia ◽  
Real Time Traffic ◽  
Broadcasting System

Construction of Urban Traffic Information Service System Based on WebGIS

2013 ◽  
Vol 353-356 ◽  
pp. 3516-3519
Author(s):  
Fei Cai ◽  
Ning Ding ◽  
Xiao Xiao Qu
Keyword(s):  
Traffic Management ◽  
Service System ◽  
Information Service ◽  
Intelligent Transportation ◽  
Remote Sensing Image ◽  
Urban Traffic ◽  
Daily Activities ◽  
Traffic Information ◽  
Route Guidance ◽  
Real Time Traffic

In order to improve utilization of traffic information, this paper introduces the construction of urban traffic information service system based on SuperMap iServer for Java. Overall structure of urban traffic information service system is designed. The system uses the remote sensing image and electronic map of Jinan as basic data and implement functions including route guidance, parking guidance, real-time traffic information and statistical analysis. The system makes advantage of the superiority of Ajax in asynchronous transmission which enhances the user's browsing experience. Efficiency of traffic flow guidance and traffic management decisions increases by the system, which greatly facilitates the daily activities of city residents. Applications show that the system is a beneficial exploration of intelligent transportation with strong practicality and versatility.

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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