Traffic Flow maximization is one of the crucial problems in de-signing a city. It directly affects the daily life of the people living in that city. It is a complex problem, one that in most cases cannot be deterministically solved. This paper proposes us-ing evolutionary algorithms to solve that problem. This paper compares existing work and traffic flow with solutions yielded by evolutionary approach, and the results show that it is bene-ficial to adopt this strategy when designing traffic light timings. General Terms
A strategy to optimize traffic light signal parameters is presented for solving traffic congestion p...
This work applies evolutionary computation and machine learning methods to study the transportation ...
This work aims to minimize average delay for an urban signalized intersection under oversaturated co...
The Smart City as a concept of future cities anticipates the smart and efficient traffic management....
ABSTRACT: Maintaining efficient transportation systems has become a key goal for government-based tr...
Cities have become congested with traffic and changes to road network infrastructure are usually not...
We describe a learning tool for genetic algorithms. We implemented it as a web site where genetic al...
The growth of vehicles’ fleet circulating on urban streets constitutes a very strong tendency in rec...
Traffic flow is considered as a stochastic process in road traffic modeling. Computer simulation is ...
Abstract Traffic congestion is a major concern in urban centers, as it can affect society, the envir...
In this article a dynamic system-optimal traffic assignment model is formulated for a congested urba...
In this article we present a strategy based on an evolutionary algorithm to calculate the real vehic...
This paper describes a new methodology adopted for urban traffic stream optimization. By using Petri...
It is well known that coordinated, area-wide traffic signal control provides great potential for imp...
International audienceFinding optimal traffic light timings at road intersections is a mandatory ste...
A strategy to optimize traffic light signal parameters is presented for solving traffic congestion p...
This work applies evolutionary computation and machine learning methods to study the transportation ...
This work aims to minimize average delay for an urban signalized intersection under oversaturated co...
The Smart City as a concept of future cities anticipates the smart and efficient traffic management....
ABSTRACT: Maintaining efficient transportation systems has become a key goal for government-based tr...
Cities have become congested with traffic and changes to road network infrastructure are usually not...
We describe a learning tool for genetic algorithms. We implemented it as a web site where genetic al...
The growth of vehicles’ fleet circulating on urban streets constitutes a very strong tendency in rec...
Traffic flow is considered as a stochastic process in road traffic modeling. Computer simulation is ...
Abstract Traffic congestion is a major concern in urban centers, as it can affect society, the envir...
In this article a dynamic system-optimal traffic assignment model is formulated for a congested urba...
In this article we present a strategy based on an evolutionary algorithm to calculate the real vehic...
This paper describes a new methodology adopted for urban traffic stream optimization. By using Petri...
It is well known that coordinated, area-wide traffic signal control provides great potential for imp...
International audienceFinding optimal traffic light timings at road intersections is a mandatory ste...
A strategy to optimize traffic light signal parameters is presented for solving traffic congestion p...
This work applies evolutionary computation and machine learning methods to study the transportation ...
This work aims to minimize average delay for an urban signalized intersection under oversaturated co...