Large cities have been facing serious problems in the management of traffic, owing to the increasing number of vehicles and pedestrians. Traffic engineering is essential in managing traffic and improving urban mobility. This paper deals with the problem of fixed-time signal programming on traffic networks. A new bi-objective optimization model is proposed to maximize the average and minimize the variance of the vehicle speeds in the network. Although the first function is commonly discussed in the literature, the second one is novel, and its aim is to provide flow balance along the network. This combination of functions is optimized by the Memory-Based Variable-Length Nondominated Sorting Genetic Algorithm 2 (MBVL-NSGA2), which avoids the revaluation of candidate solutions. This approach was validated through experiments using the microscopic simulator GISSIM, in a multi-intersection real network, using measured data from Belo Horizonte traffic engineering company (BHTRANS). The practical results of MBVL-NSGA2 were compared with four approaches: (1) current BHTRANS solutions; (2) a genetic algorithm optimizing the first function; (3) a genetic algorithm optimizing the second function, and; (4) the traditional NSGA2. Analysis showed that this proposal is able to generate better traffic signal plans, at the same time that it generates a diversified set of efficient candidate solutions.
In a context of growing concerns about space debris, new regulations such as the French Space Act restrict the disposal of space objects after end of their operational life in order to mitigate the risks of collision in populated space regions. As a consequence, future underdevelopment European launchers have to meet these requirements, which can significantly impact their designs. As a result, Astrium Space Transportation has developed a fast and reliable long-term orbit propagator to integrate the natural fallout of upper stages into the design process of next-generation launchers. Based on semi-analytical solving of the Gauss equations, this propagator integrates so far the third-body force, the atmospheric drag, solar radiation pressure and a fourth-order zonal model (J2-J4) of the Earth gravitational field. Inter-validation against in-house numerical integrator and COTS software reveal the semianalytical approach leads to similar computational accuracy levels while significantly reducing the simulation time. Several application cases are presented to illustrate the tool capabilities and applications into the launcher design process.
NomenclatureG = Gravitational constant a = Semi-major axis β = Ballistic coefficient γ = Velocity slope e = Eccentricity i = Inclination Ω = Right ascension of ascending node ω = Perigee argument r = Radius R eq = Earth equatorial radius n = Keplerian orbit pulsation M obj = Object mass λ = Longitude φ = Geocentric latitude Φ = Solar radiation power μ = Earth standard gravitational parameter K diff = Surface diffusion coefficient θ = True anomaly E = Eccentric anomaly C D = Drag coefficient ρ atm = Atmospheric density c = Light speed S ref = Reference surface for drag formulation Σ ref = Reference surface for solar radiation pressure formulation 1 Aerospace Engineer
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