"TRAVELLING. IT LEAVES YOU SPEECHLESS THEN TURN YOU INTO A STORYTELLER" - iBN BATTUTA.
ABSTRACT
Nowadays, the use of road networks are increasingly used, it is a must to be able predict travel times for spreading information to the road users and then it can help in decision and travel planning. The interesting fact is that the users of road usually will update any kind of information in their social network including the information of the road condition. Therefore, the data about road condition can be known from the social network itself and it can help to form a travel time prediction system using information from it. In this research, discusses a model of urban road journey on predicting travel time aiming at predicting the traffic by considering how vehicle behave, routes use or sudden occurrence of event. However, in some cases the traffic jam may occur without any apparent cause. It just spontaneously appears and might or might not last long time and then simply disappeared. In this paper the phenomenon will be illustrated by Monte Carlo theory and verify the result with the simulation of the road condition. The simulation, it will show how the Monte Carlo theory works on predicting the travel time from one point to another point. The data will be taken from the social network and it will be simulate and by considering the events that might happen and try to verify that Monte Carlo theory might improve the predictive travel time more accurate with the practical situation.
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Supervised by :
Dr Ahmad Faisal Amri Bin Abidin@Bharun |
INTRODUCTION
What is travel time ?
Time travel is the concept of movement between certain points in time.
... Eg; movement between different points in space, typically using a vehicle or of a portal connecting distant points in time. |
Why predict travel time ?
Because the predict travel-time information/data helps drives to understand the conditions of traffic, make decision or plan schedules. Users can predict the estimation of their expected arrival time more accurately based on predicted travel times using any route-guidance system. |
How to predict travel time ?
The main component use in this project are :
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OBJECTIVES
To study and explore Monte Carlo theory in predicting travel time
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To simulate road traffic in Simulator in Urban Mobility (SUMO) platform
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To integrate sumo with Monte Carlo in order to predict travel time
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To test the functionality of SUMO and Prediction travel time in Monte Carlo
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METHODOLOGY
In this project, the vehicular demand modelling was derived from TAPAS (Travel and Activity Patterns Simulation) in Cologne City, Germany. The Road traffic were constructed using TAPAS data on how traffic flow reacts over particular traffic incident
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The figures above show the SUMO output. The output has been utilised as input to Monte Carlo Model.to update the prediction based on the real-time trip.
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Linking SUMO and Monte Carlo Model. To link both component, we need to integrate the component in Matlab. The outcome will be the end result.
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RESULT
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Graph 1 and 2 shows the results from the incident free journey.
In Graph 2, shows that the data input to the Monte Carlo model, are actually almost similar to the prediction time.
In Graph 2, shows that the data input to the Monte Carlo model, are actually almost similar to the prediction time.
CONCLUSION
Therefore, the functionality of SUMO and Prediction travel time in Monte Carlo are proven and objective achieved.
Let me know your opinion !