Controlling traffic jams on urban roads modeled in Coloured Petri net using Genetic Algorithm

Dezani, Henrique; Gomes, Luís; Damiani, Ferruccio; Marranghello, Norian

doi:10.1109/iecon.2012.6389412

Cited by 11 publications

(8 citation statements)

References 13 publications

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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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Section: Airport Surface Static Modelmentioning

confidence: 99%

Airport Surface Modelling and Simulation Based on Timed Coloured Petri Net

2019

PROMET

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“…So far, evolutionary algorithms have been widely used in the field of dynamic traffic distribution (e.g., [3], [4], and [5]). However, unlike our proposal, existing works do not focus on reducing the rescue time of the emergency services, or exploit the advantages of using vehicular communication capabilities to calculate vehicles routes.…”

Section: Introductionmentioning

confidence: 99%

Using Evolution Strategies to Reduce Emergency Services Arrival Time in Case of Accident

Barrachina

Garrido

Fogue

et al. 2013

2013 IEEE 25th International Conference on Tools With Artificial Intelligence

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Abstract-A critical issue, especially in urban areas, is the occurrence of traffic accidents, since it could generate traffic jams. Additionally, these traffic jams will negatively affect to the rescue process, increasing the emergency services arrival time, which can determine the difference between life or death for injured people involved in the accident. In this paper, we propose four different approaches addressing the traffic congestion problem, comparing them to obtain the best solution. Using V2I communications, we are able to accurately estimate the traffic density in a certain area, which represents a key parameter to perform efficient traffic redirection, thereby reducing the emergency services arrival time, and avoiding traffic jams when an accident occurs. Specifically, we propose two approaches based on the Dijkstra algorithm, and two approaches based on Evolution Strategies. Results indicate that the Density-Based Evolution Strategy system is the best one among all the proposed solutions, since it offers the lowest emergency services travel times.

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“…There are several works where intelligent systems are used to avoid traffic jams (e.g., Ohara et al (2006), Sanchez-Medina et al (2010), and Dezani et al (2012)). However, they do not focus on reducing the rescue time of the emergency services, or exploit the advantages of using vehicular communication capabilities.…”

Section: Introductionmentioning

confidence: 99%

Reducing emergency services arrival time by using vehicular communications and Evolution Strategies

Barrachina¹,

Garrido²,

Fogue³

et al. 2014

Expert Systems with Applications

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Nowadays, traffic jams in urban areas have become a problem that keeps growing every year since the number of vehicles in our cities is continuously increasing. One of the most common causes producing traffic jams are vehicle accidents. Moreover, the arrival time of the emergency services could be raised due to traffic congestion. Intelligent Transportation Systems (ITS) have a key role in order to reduce or mitigate this problem. In this paper, we propose four different approaches addressing the traffic congestion problem, comparing them to obtain the best solution. Using V2I communications, we are able to accurately estimate the traffic density in a certain area, which represents a key parameter to perform efficient traffic redirection, so reducing the emergency services arrival time, and avoiding traffic jams when an accident occurs. Specifically, we propose two approaches based on Dijkstra algorithm, and two approaches based on Evolution Strategies. Notice that, when an accident occurs, time is a critical issue, and strategies here proposed contribute to optimal solution within a short period of time.

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Controlling traffic jams on urban roads modeled in Coloured Petri net using Genetic Algorithm

Cited by 11 publications

References 13 publications

Airport Surface Modelling and Simulation Based on Timed Coloured Petri Net

Airport Surface Modelling and Simulation Based on Timed Coloured Petri Net

Using Evolution Strategies to Reduce Emergency Services Arrival Time in Case of Accident

Reducing emergency services arrival time by using vehicular communications and Evolution Strategies

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