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Review of Microscopic Traffic Model Using Artificial Intelligence Slides.pptx

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Review of Microscopic Traffic Model Using Artificial Intelligence Slides.pptx

  1. 1. Review of Microscopic Traffic Model Using Artificial Intelligence
  2. 2. BAYERO UNIVERSITY KANO DEPATMENT OF CIVIL ENGINEERING FACULTY ENGINEERING TECHNOLOGY PRESENTATION ON REVIEW OF MICROSCOPIC TRAFFIC MODEL USING ARTIFICIAL INTELLIGENCE PRESENTED BY PWAVIRON KENEDY GAMBIYE SPS/20/MCE/00028 NOVEMBER, 2022
  3. 3. Introduction Today, the problem of cities urban transportation is becoming something we have to face in our daily life. Typical traffic simulation models can be classified as either microscopic, mesoscopic, or macroscopic. Microscopic models predict the state of individual vehicles; typical measures are individual vehicle speeds and locations. Definitions of microscopic simulation was assorted, but in general microscopic simulation can be determined as an effort to develop a driver behaviour and vehicle models in order to produce a more realistic simulation. Artificial intelligence (AI) is the ability of a computer or a robot controlled by a computer to do tasks that are usually done by humans because they require human intelligence and discernment. AI refers to methods and approaches that mimic biologically intelligent behaviour in order to solve problems that so far have been difficult to solve by classical mathematics (Sadek, 2007).
  4. 4. Background of Microscopic Traffic Model Using Artificial Intelligence  Microscopic traffic flow modelling specialized on the minute aspects of traffic stream like vehicle-to-vehicle interaction and individual vehicle behaviour  Traffic simulation is the mathematical modelling of traffic dynamics with the use of computer software and application to support the planning, operation, and development of transportation systems  Microscopic simulation is a model that describes the behaviour and interactions of each driver in a traffic system, which is made more detailed modelling for each movement of the vehicle.  Microscopic traffic models describe the details of traffic flow and the interaction taking place within it. Microscopic traffic models simulate single vehicle-driver units.
  5. 5. Advantages of Microscopic Model Using Artificial Intelligence 1. It can track a single vehicle on the road, 2. it can reflect the interaction between vehicles and also predict traffic performance indicators such as vehicle travel time, delay and emission while avoiding the impact on actual road traffic; 3. Through the microscopic model using artificial intelligence, the impact of a specific parameter on traffic can be reflected; through the animation interface of the simulator, 4. With microscopic model one can intuitively visualize the changes in road traffic, and provide a good platform for understanding the traffic operation status under different traffic demands.
  6. 6. Disadvantages of Microscopic Model Using Artificial Intelligence 1. High cost the ability to create a machine that can simulate human intelligence is high. 2. Increase rate of unemployment and make humans lazy. 3. It does not improve with experience and lack creativity 4. Cannot replace human
  7. 7. Review Of Microscopic Traffic Model Using Artificial Intelligence Microscopic traffic models describe the details of traffic flow and the interaction taking place within it. Studies found several models which are related to this study.
  8. 8. Simulation Based on Intelligent Transport System Kesting (2008) developed an existing IDM using the new constant acceleration heuristic.To know the effect of influenced vehicle using ACC. Schinder (2010) Modeled traffic to explores the interaction between subsystem(driver, vehicle and infrastructure).To find an appropriate model use as a foundation for ADAS
  9. 9. Modeling Based Microscopic Car Following And Lane Changing DAS (2009) The research trying to develop a car following model for narrow roads using automata cell approach.  LU (2013) This research try to modeled the decision making of drivers using parameters desired using parameters desired safety margin(DSM) theory of homeostasis
  10. 10. Modeling Driver Behavior SONG (2000) His research tried to model driving behavior model of the existing simulation tools.The contributions is to build a database of knowledge formation’s driver and the development of cognitive processes modeling when the driver was doing driving activities
  11. 11. Other Reviews on Various Models Olayede et al (2020), in their research “Modelling of Urban Traffic System Using Artificial Intelligence” tying to solve the increasing traffic congestion in recent years created a new more efficient control solutions.
  12. 12. Raghuwanshi, Salunke, Hou and Hulume (2014), carried out a study on “Development of a Microscopic Artificially Intelligent Traffic Model for Simulation” evaluated numerous traffic simulation models for supporting next-generation ITS research applications. The survey justified the need for the design and development of a microscopic Artificially Intelligent Traffic Model (AITM) intended for civilian ground vehicle research applications. The research concludes that while traffic simulation models allow for capturing dynamics of full-scale traffic networks, they often lack behavioural realism.
  13. 13. Leal, Almeida & Ribeiro (2019) on the topic Calibrating Traffic Microscopic Simulation Model Parameters Using an Evolutionary approach” which aims at using Microscopic Simulation models to provide traffic management solutions. The paper presents a genetic algorithm-based microscopic simulation model to calibrate the parameters of AIMSUN simulator to a network of intersections in Belo Horizonte city, Brazil. Results obtained showed that calibration process is essential in the use of microscopic simulation models to define and predict traffic managements strategies
  14. 14. Conclusion In conclusion the objective of microscopic traffic model using artificial intelligence is to presents a real traffic situation in to dynamic model. Based on the literature that has been discussed ,there is no generic model that can be used to represent all traffic conditions characterized respectively(environmental Conditions. Infrastructure ,Traffic management etc)
  15. 15. Thank You for Listening

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