1,720,962 research outputs found
CALIBRATION AND VALIDATION OF A MACROSCOPIC TRAFFIC FLOW MODEL BASED ON PLATOON DISPERSION AND QUEUE PROPAGATION
This paper proposes a preliminary calibration and validation of a macroscopic traffic flow model for signalised junctions. In fact, on the network signal setting design problem, a reliable modelling approach must be adopted to acknowledge the traffic flow effects, considering two phenomena: queue dispersion and spillback. The proposed model is an extension of the space-time discrete Cell Transmission Model (CTM), which can simulate dispersion and horizontal queue. This preliminary calibration and validation use real-world data collected on an arterial of the city of Salerno (south of Italy). Results showed that the estimated parameters are consistent with the literature
A traffic responsive control framework for signalized junctions based on hybrid traffic flow representation
The paper proposes a traffic responsive control framework based on a Model Predictive Control (MPC) approach. The framework focuses on a centralized method, which can simultaneously compute the network decision variables (i.e., the green timings at each junction and the offset of the traffic light plans of the network). Furthermore, the framework is based on a hybrid traffic flow model operating as a prediction model and plant model in the control procedure. The hybrid traffic flow model combines two sub-models: an aggregate model (i.e., the Cell Transmission Model; CTM) and a disaggregate model (i.e., the Cellular Automata model; CA), using a transition cell to connect them. The whole framework is tested on a signalized arterial, performing several analyses to calibrate the MPC strategy and evaluate the traffic control approach using fixed and adaptive control strategies. All analyses are made in terms of total time spent, network total delay, queue lengths and degree of saturation
Signal setting design to reduce noise emissions in a connected environment
Traffic signal optimisation was tested on a network with signalised interacting junctions, comparing different approaches and scenarios based on short-range communication between the infrastructure and CVs approaching the junctions. The results show that the proposed traffic control method may be adopted to effectively reduce the impact of traffic noise and improve traffic performance
Adoption of electric vehicles by young adults in an emerging market: a case study from Argentina
The destiny of the electric vehicle (EV) marketplace will depend upon the behaviour of potential buyers and on how emerging markets allow EVs to be perceived as a mobility solution to the externalities generated by internal combustion (IC) vehicles. To this end it is important to ascertain the role played by psychological factors, along with instrumental attributes, especially among younger adults (future purchasers) in not yet mature markets. Our paper analyses and models the propensity to purchase an EV with respect to an equivalent IC vehicle. It contributes to the existing literature investigating younger adults’ behaviour in an emerging market, focusing on the role of attitudes and perceptions. A stated preferences survey, built on real commercial scenarios (Renault ZOE vs Renault Clio), was designed and disseminated at the University of Cordoba (Argentina). Respondent behaviour was modelled within the random utility paradigm. First, heterogeneity among users was investigated through mixed multinomial logit formulation; The role of psycho-attitudinal factors was then explored through the specification of hybrid choice models with latent variables. Estimation results indicate the significant role of attitudes and perceptions in emerging markets
Calibration and validation of a hybrid traffic flow model based on vehicle trajectory data from a field car-following experiment
The paper focuses on the calibration of the hybrid multi-scale modelling approach that incorporates multiple levels of traffic flow representation. This paper refers to a model already developed in the literature, the Hybrid Cellular Automata (CA) and Cell Transmission Model (CTM). We use vehicle trajectory data collected from a car-following field experiment on a circular road track to explore the calibration of the CA model concerning various cell lengths through two distinct approaches: simulating all vehicles within the closed loop and simulating each vehicle using data obtained from its respective follower. We also evaluate different methods for the CTM calibration with respect to the CA model. The major findings are: (1) the calibrated parameters obtained using the simulated leader approach display greater regularity across different cell lengths; (2) the Constrained Squared Error [CsqE] method for macroscopic calibrations yielded promising results, showcasing the lowest sum of squared errors between fundamental diagrams
Context-aware Nonlinear MPC for Automated Vehicles Embedding Newell's Car-Following Model
Automated Driving Systems equipping Connected and Automated Vehicles (CAVs) require a meticulous design to maximize the advantages of connectivity and automation. However, even the most widespread systems are not free from problems; for instance, the effectiveness of current Adaptive Cruise Control implementations in improving safety, traffic stability and energy consumption is questionable. Therefore, there is the need to develop solutions that avoid inadequate driving behaviours. To this end, in this work we design a Nonlinear Model Predictive Control (NMPC) strategy that resemble an ACC, embedding the Newell non-linear car-following model. The Newell model computes a reference speed profile over the prediction horizon, ensure string stability and anticipate speed oscillations. Then, using this speed as reference, the NMPC controller computes an optimal acceleration profile to drive the vehicle as fast as possible while ensuring comfort and safety. The proposed NMPC strategy is evaluated across various simulation scenarios, with several Key Performance Indicators (KPIs) related to safety, driving volatility and consumption. A conventional ACC system is employed for comparison. Through observation and comparison of the KPIs, the effectiveness of the proposed approach is demonstrated
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Unified network tRaffic management frAmework for fully conNected and electric vehicles energy cOnsumption optimization (URANO)
Cooperative control in the presence of connected and automated vehicles has attracted substantial attention due to its pronounced benefits on the network compared with human-driven vehicles. They make possible a significant reduction of travel time/waiting time, energy consumption and emissions. In this context of new emerging technologies, traffic lights are still recognized as one of the most effective strategies in terms of energy and environmental benefits, which can be further improved by considering the integration with greener powertrains. The paper proposes a cooperative network traffic management framework for Electric Vehicles (EVs) based on a multi-objective optimization aimed at minimizing the total time spent (TTS) and energy consumption (EC) of EVs. Such framework is composed of i) a traffic control model that incorporates traffic lights design, ii) a traffic flow model to estimate TTS as a network performance indicator, and iii) an EVs model to estimate EC at the intersections. The EC function has been derived from a VT-CPEM model to simulate consumptions and thoroughly calibrated based on real-world individual trajectories. The optimization framework was implemented on a nine-node network and the results of the multi-criteria optimization (aiming at minimizing the TTS and EC of EV) are compared with results of the benchmark mono - criterion optimization (aiming at minimizing the TTS) and the mono-criterion optimization combined with the speed advisory (GLOSA; Green Light Optimized Speed Advisory). All the proposed analyses were carried out for different powertrain vehicle categories; ICEVs, and EVs
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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