scholarly journals Real time traffic information system-A step towards total traffic management at Kamakura

2001 ◽  
Vol 18 ◽  
pp. 887-894
Author(s):  
Shinji KAJITANI ◽  
Kunihiro SAKAMOTO ◽  
Hisashi KUBOTA ◽  
Youji Takahashi
Keyword(s):  
Information System ◽  
Real Time ◽  
Traffic Management ◽  
Traffic Information ◽  
Real Time Traffic ◽  
System A

scholarly journals Penerapan Teknologi GPS Tracker Untuk Identifikasi Kondisi Traffik Jalan Raya

2015 ◽  
Vol 14 (1) ◽  
Author(s):  
IM. O. Widyantara ◽  
I G.A.K. Warmayana ◽  
Linawati Linawati
Keyword(s):  
Information System ◽  
Real Time ◽  
Tracking System ◽  
Traffic Information ◽  
Dense Medium ◽  
Test Results ◽  
Process Data ◽  
Traffic Jam ◽  
Real Time Traffic ◽  
System A

Real time tracking system technology has been made possible by integrating three technologies, namely global positioning system (GPS), database technologies such as geographic information system (GIS) and mobile telecommunications technologies such as general packet radio service (GPRS). This paper has proposed a vehicle tracking mechanism based on GPS tracker to build a real-time traffic information system. A GPS server is built to process data of position and speed of the vehicle for further processed into vehicle traffic information. The Server and GPS tracker is designed to communicate using GPRS services in real time. Furthermore, the server processes the data from the GPS tracker into traffic information such as traffic jam, dense, medium and smoothly. Test results showed that the GPS server is able to visualize the real position of the vehicle and is able to decide the category of traffic information in real time.

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.  

scholarly journals Mobile Road Traffic Management System Using Weighted Sensor

2017 ◽  
Vol 11 (5) ◽  
pp. 147 ◽  
Author(s):  
Solomon Adegbenro Akinboro ◽  
Johnson A Adeyiga ◽  
Adebayo Omotosho ◽  
Akinwale O Akinwumi
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Urban Areas ◽  
Traffic Management ◽  
Management System ◽  
Road Traffic ◽  
Traffic Information ◽  
Traffic Light ◽  
Real Time Traffic ◽  
Traffic Management System

<p><strong>Vehicular traffic is continuously increasing around the world, especially in urban areas, and the resulting congestion ha</strong><strong>s</strong><strong> be</strong><strong>come</strong><strong> a major concern to automobile users. The popular static electric traffic light controlling system can no longer sufficiently manage the traffic volume in large cities where real time traffic control is paramount to deciding best route. The proposed mobile traffic management system provides users with traffic information on congested roads using weighted sensors. A prototype of the system was implemented using Java SE Development Kit 8 and Google map. The model </strong><strong>was</strong><strong> simulated and the performance was </strong><strong>assessed</strong><strong> using response time, delay and throughput. Results showed that</strong><strong>,</strong><strong> mobile devices are capable of assisting road users’ in faster decision making by providing real-time traffic information and recommending alternative routes.</strong></p>

Link Flow Evaluation Using Loop Detector Data: Traveler Response to Variable-Message Signs

1996 ◽  
Vol 1550 (1) ◽  
pp. 58-64 ◽  
Author(s):  
Youngbin Yim ◽  
Jean-Luc Ygnace
Keyword(s):  
Real Time ◽  
Traffic Management ◽  
Preliminary Investigation ◽  
Traffic Information ◽  
Mean Flow ◽  
Variable Message Signs ◽  
Real Time Traffic ◽  
Operational Test ◽  
Paris Region ◽  
Message Signs

Système d'Information Routière Intelligible aux Usagers (SIRIUS) is the largest urban field operational test of the advanced traveler information and automated traffic management system in Europe. With variable-message signs, SIRIUS has been in operation in the Paris region for 3 years. A preliminary investigation of the effectiveness of the SIRIUS system in traffic management is presented. The extent to which drivers respond to real-time traffic information and the consequential changes in link flow under SIRIUS is also presented. Time-series traffic data were analyzed to measure changes in mean flow rates at a selected link. It was found that variable-message signs influence drivers to choose less congested routes when drivers are provided with real-time traffic information, and that a driver's decision to divert is closely associated with the information pertaining to the level of congestion. In the Paris region, drivers received information on the length of the queue at the time of this study. As congestion becomes heavier, drivers are more likely to respond to variable-message signs. According to the data analysis, a queue length of 3 km seems to be a threshold at which a significant number of drivers choose to use an alternative route.

Artificial Intelligence-Based Architecture for Real-Time Traffic Flow Management

1998 ◽  
Vol 1651 (1) ◽  
pp. 53-58 ◽  
Author(s):  
Adel W. Sadek ◽  
Brian L. Smith ◽  
Michael J. Demetsky
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Traffic Flow ◽  
Traffic Management ◽  
Traffic Information ◽  
Case Based Reasoning ◽  
Flow Management ◽  
Real Time Traffic ◽  
Highway Network ◽  
Traffic Flow Management

Real-time traffic flow management has recently emerged as one of the promising approaches to alleviating congestion. This approach uses real-time and predicted traffic information to develop routing strategies that attempt to optimize the performance of the highway network. A survey of existing approaches to real-time traffic management indicated that they suffer from several limitations. In an attempt to overcome these, the authors developed an architecture for a routing decision support system (DSS) based on two emerging artificial intelligence paradigms: case-based reasoning and stochastic search algorithms. This architecture promises to allow the routing DSS to ( a) process information in real time, ( b) learn from experience, ( c) handle the uncertainty associated with predicting traffic conditions and driver behavior, ( d) balance the trade-off between accuracy and efficiency, and ( e) deal with missing and incomplete data problems.

RoadRank Algorithm – A Novel Method to Calculate Traffic Index for an Area

2014 ◽  
Vol 1079-1080 ◽  
pp. 769-775
Author(s):  
Fan Wang ◽  
Yu Fang
Keyword(s):  
Information System ◽  
Real Time ◽  
Traffic Information ◽  
Area Index ◽  
New Model ◽  
Real Time Traffic ◽  
Information Center ◽  
Novel Method ◽  
Definition Of

Traffic index hasbeen used to provide accurate traffic information to users. Many models havebeen developed to calculate the index for a road, but how to define andcalculate the index for an area still needs more investigation. Here we proposea new model for area index, including a definition of area index itself and a methodto calculate it. But this model can’t be widely used, for some innatelimitations. So we put forward another method based on well-known algorithmPageRank to calculate area index. To test the effectiveness, we apply ouralgorithmto conduct several experiments. Our experiments using standard trafficstatistics provided by ShanghaiTraffic Information Center (STIC), show our method have values for real-time traffic information system.

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