Optimizing urban traffic flow using Genetic Algorithm with Petri net analysis as fitness function

Dezani, Henrique; Bassi, Regiane Denise Solgon; Marranghello, Norian; Gomes, Luís; Damiani, Ferruccio; Silva, Ivan Nunes da

doi:10.1016/j.neucom.2013.07.015

Cited by 35 publications

(21 citation statements)

References 11 publications

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“…They are used in personal Apps and they route drivers to their destination, usually by showing the shortest path and travel time. They provide traffic decision support for an individual driver, but they do not take into consideration where other drivers are going and may contribute to increasing congestion [53] In traffic decision making, drivers usually select the shortest route because they see it as an optimal solution. However, the authors of [54] claim that, by choosing a less selfish route, drivers can improve traffic flow: total congestion can be reduced by up to 30%.…”

Section: The Problemmentioning

confidence: 99%

Semantic Management of Urban Traffic Congestion

Shakil¹,

Juric

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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Urban traffic congestion is a problem which affects the world and is related to the massive urbanization and excessive number of cars on our streets. This causes a variety of problems, from economical/financial and health-related, to environmental warnings caused by high CO2 and NO2 emissions. This paper proposes a novel software engineering solution, which generates a software application aimed at individual drivers on urban roads, in order to help and ease overall congestion. The novelty is twofold. We target individual drivers in order to motivate them to re-think the purpose and goals of each journey they take. Consequently, the proposed software application enables reasoning upon various options an individual driver may have and helps in choosing the best possible solution for an individual. Our software application utilizes reasoning with SWRL enabled OWL ontologies, which can be hosted by any software application we run in our cars, ready to assist in driving, and implemented in Android / iOS environments.

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Section: The Problemmentioning

confidence: 99%

Semantic Management of Urban Traffic Congestion

Shakil¹,

Juric

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…Route planning based on Petri net is a new idea. Dezani et al combined Petri net model with Genetic Algorithm (GA) and applied it to urban traffic control [15][16][17]. The Petri net model was used as a fitness function and the urban traffic flow was optimized by analysing the number of vehicles in the traffic network at different moments.…”

Section: Airport Surface Static Modelmentioning

confidence: 99%

Airport Surface Modelling and Simulation Based on Timed Coloured Petri Net

2019

PROMET

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In order to satisfy the requirements of International Civil Aviation Organization (ICAO) for aircraft taxi route planning in Advanced Surface Movement Guidance and Control System (A-SMGCS), an airport surface operation modelling and simulation approach based on timed and coloured Petri net is presented. According to the layout of the airport surface and the features of surface operation units, a static Petri net model of the airport surface is established. On this basis, in line with the requirements on the aircraft taxiing velocity in ICAO DOC 9830, the dynamic Petri net model of the airport surface operation is established by adding the time attribute to the static model. Additionally, the method of defining the capacity of airport operation unit place is proposed and the constraints of the airport surface operation are incorporated using Petri net elements. Unlike other papers in the field, the airport surface Petri net model established in this paper can simulate conflict-free taxiing using a Petri net simulator without relying on other model-independent algorithms. Based on the CPN Tools software, taking Toulouse Airport as an example, the validity of the model has been verified by comparing the model running data with real flight data.

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“…This way, the computational time is reduced because the operations can be performed in parallel. Depending on the distance between the start and end point, the algorithm can use street layers to avoid taking into account small streets for routes traveling from a city to another; the algorithm can use a layer for the highways, one for European roads, national roads and so on [9].…”

Section: Related Workmentioning

confidence: 99%

A Personalized Multi-Path and Multi-User Traffic Analysis and Visualization Tool

Babau¹,

Marcu²,

Tihu³

et al. 2017

Acta Cybern

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Traffic optimization is a subject that has become vital for the world we live in. People these days need to get from a starting point to a destination point as fast and as safe as possible. Traffic congestion plays a key role in the frustration of people and it results in lost time, reduced productivity and wasted resources. In our study we seek to address these issues by proposing a real-time road traffic planning system based on mobile context and crowd sourcing efforts. The first step toward this goal is real-time traffic characterization using data collected from mobile sensors of drivers, pedestrians, cyclists, passengers, etc.. We started developing a data collection and analysis system composed of a mobile application in order to collect user context data and a Web application to view and analyze the data. This new system will eventually give the users an automatically optimized route to the destination and predict the users' traveling route based on live traffic conditions and historical data.

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Optimizing urban traffic flow using Genetic Algorithm with Petri net analysis as fitness function

Cited by 35 publications

References 11 publications

Semantic Management of Urban Traffic Congestion

Semantic Management of Urban Traffic Congestion

Airport Surface Modelling and Simulation Based on Timed Coloured Petri Net

A Personalized Multi-Path and Multi-User Traffic Analysis and Visualization Tool

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