1,720,971 research outputs found
Estimating and exploiting the capacity of urban street networks
Full text linkThe paper deals with the problem of estimating and exploiting traffic capacity of different road elements (link, nodes, network) and presents the results obtained by performing a systematic investigation of the role that the parameters of a microscopic simulation model play on the macroscopic representation of different road elements. An analysis of traffic parameters has been performed using a microsimulation software package to identify the most important parameters affecting the arterial capacity and to calibrate driver's behavior models through macroscopic traffic observations
Coherence analysis of road safe speed and driving behaviour from floating car data
No full textIn the Intelligent Transportation Systems, integration of different components of the classical driver-vehicleinfrastructure system is supported by advances in technology and communications. This study presents a general road safety analysis framework that exploits different types of data on traffic, geometry, and accidents to develop a Road Safety Analysis Center and an on-board Road Safety Driver Advisory. The Road Safety Analysis Center considers different sources of data: accident inventories, road geometry, and floating car data, which reveal drivers' behavior. Floating car data are also exploited to derive mathematically the longitudinal parameters of ancient roads, which are crucial to estimate safety conditions in curves. The critical points of the network are revealed by an aggregate analysis of accidents distribution on the roads, while the drivers' behaviour is addressed on a disaggregated level, by the evaluation of speeds distributions with a dense spatial detail. The comparison between speeds distributions, safety conditions, and accident occurrence is useful to individuate the portions of the network to be enforced with safety measures and support drivers with an advanced onboard speed advisory system. This methodology is applied to several extra-urban roads in the Latium region, Italy, to individuate roads with higher values of critical indices
Meta-heuristic aggregate calibration of transport models exploiting data collected in mobility
No full textThe wide diffusion of data collected in mobility led to an unprecedented amount of information about people's mobility behavior. While on one hand the availability of big data from multiple sources enables to calibrate complex models with a high number of parameters, on the other hand, the dimension of the problem increases, and computational efficiency becomes an important issue. The paper presents a general methodology for the aggregate calibration of transport system models that exploits data collected in mobility jointly with other data sources within a multi-step optimization procedure based on metaheuristic algorithms. The methodology is applied to two real large-scale case studies in two different contexts. The first concerns the aggregate calibration updating a national strategic 4-step demand model in use in a big European Country; the second deals with the calibration of link and node performance functions implemented in a traffic network model of a town of around 3 million inhabitants. The results demonstrate the effectiveness of the aggregate calibration methodology in significantly improving earlier models' estimations. The results also highlight that the errors are in the same order of magnitude as the intrinsic variation of the data collected in the field
Optimization of Traffic Signals on Urban Arteries through a Platoon-Based Simulation Model
No full textThe paper describes an optimization procedure to synchronize traffic signals along an urban road artery. The solution procedure applies first a genetic algorithm and then a hill climbing algorithm for local adjustments. The fitness function is evaluated by means of a traffic model that simulates platoon progression along the links, their combination and possible queuing at nodes. The potential benefits of the synchronization procedure have been assessed by simulating a real urban artery through the micro-simulation model Transmodeler
Validation of macro traffic relationship combining micro and macro data: experimental analysis
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Heuristic approaches to address vehicle routing problem in the Iot-based waste management system
No full textNowadays, population growth and urban development lead to having an efficient waste management system (WMS) based on recent advances and trends. Alongside all functions and procedures in these systems, the waste collection plays a significant role. This study proposes a two-echelon WMS to minimize operational costs and environmental impact by utilizing the industry 4.0 concept. Both models utilize modern traceability Internet of Thing-based devices to compare real-time information of waste level in bins and separation centers with the threshold waste level (TWL) parameter. The first model optimizes the operational cost and Co2 emission of collecting waste from bins to the separation center by considering the time windows. A capacitated vehicle routing problem is designed as a later model-based to minimize the cost of waste transferring to recycling centers. In addition, to find the optimal solution, recent meta-heuristic algorithms are employed, and several novel heuristics based on the problem's specifications are developed. Furthermore, the developed heuristics methods are utilized to generate the initial feasible solutions in meta-heuristics and compared with random ones. The performance of the proposed algorithms is probed, and Best Worst Method (BWM) is applied to rank the algorithms based on relative percentage deviation, relative deviation index and hitting time
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