Vehicle Schedule Simulation with AnyLogic

Merkuryeva, Galina; Bolshakovs, Vitalijs

doi:10.1109/uksim.2010.38

Cited by 34 publications

(14 citation statements)

References 5 publications

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“…Agents are autonomous entities within the model that are capable of making decisions given an external stimulus. This type of simulation has proven to be successful in modelling different activities for vehicles and pedestrians, including pedestrian movement (Zhang, Luo, Chen, & Bao, 2009), pedestrian emergency evacuation (Jin & Chen, 2013), vehicle's schedules (Merkuryeva & Bolshakovs, 2010) or new urban transport modes (Martinez, Correia, & Viegas, 2015;Scheltes & de Almeida Correia, 2017;Vasconcelos, Martinez, Correia, Guimarães, & Farias, 2017). In the following sections, we describe the model components developed in this work.…”

Section: Simulation Model and Environmentmentioning

confidence: 99%

Pedestrians’ road crossing behaviour in front of automated vehicles: Results from a pedestrian simulation experiment using agent-based modelling

Rad

Correia

Hagenzieker

2020

Transportation Research Part F: Traffic Psychology and Behaviou

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The objective of this research is to explore the relation between personal characteristics of pedestrians and their crossing behaviour in front of an automated vehicle (AV). For this purpose, a simulation experiment was developed using Agent-Based Modelling (ABM) techniques. Sixty participants were asked to cross the road in a virtual environment displayed on a computer screen, allowing to record their crossing behaviour when in the presence of AVs and conventional vehicles (CVs). In some experimental configurations, the AVs communicated their intention to continue or not to continue their trajectories through the use of lights. The ABM allowed controlling the behaviour of the vehicles when interacting with the simulated avatar of the respondents. The subjects of the experiment were also asked to fill in a questionnaire about usual behaviour in traffic, as well as attitudes and risk perceptions toward crossing roads. The questionnaire data were used to estimate individual specific behavioural latent variables by means of principal component analysis which resulted in three main factors named: violations, lapses, and trust in AVs. The results of generalized linear mixed models applied to the data showed that besides the distance from the approaching vehicle and existence of a zebra crossing, pedestrians' crossing decisions are significantly affected by the participants' age, familiarity with AVs, the communication between the AV and the pedestrian, and whether the approaching vehicle is an AV. Moreover, the introduction of the latent factors as explanatory variables into the regression models indicated that individual specific characteristics like willingness to take risks and violate traffic rules, and trust in AVs can have additional explanatory power in the crossing decisions.

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Section: Simulation Model and Environmentmentioning

confidence: 99%

Pedestrians’ road crossing behaviour in front of automated vehicles: Results from a pedestrian simulation experiment using agent-based modelling

Rad

Correia

Hagenzieker

2020

Transportation Research Part F: Traffic Psychology and Behaviou

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“…It was first introduced at the Winter Simulation Conference in 2000 [31]. AnyLogic is an object-oriented simulation software that employs Java programming language [32,33].…”

Section: Simulation Modelmentioning

confidence: 99%

Assessing the Environmental Benefits of Dry Port Usage: A Case of Inland Container Transport in Turkey

Kurtuluş

Çetin

2019

Sustainability

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Inland transportation of maritime freight conducted by trucks creates extensive emissions. These emissions can be mitigated by using intermodal-rail transport through dry ports. In that regard, this study evaluated the environmental benefits of dry port usage by using discrete event simulation modelling. The results show that the current level of dry port-based intermodal transportation decreases greenhouse gas (GHG) emissions by 5.79% compared to transportation of all containers on the road. Evaluating the impact of the electrified railway line on the GHG emissions revealed unexpected results; the electrification of the railway line would decrease GHG emissions only by 0.06%. The improvements in empty container movement and scheduling slightly reduced GHG emissions by 0.69% and 0.63% respectively, however, highest GHG emissions reduction resulted from modal shift by 6.56%. This study extended the previous literature by assessing not only the environmental benefits of dry port usage but also its effects on train capacity usage, while taking the empty container movement into account.

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“…This makes a solution search process non-efficient in terms of computational time. To increase optimisation efficiency, all constraints are converted into soft constraints (Merkuryeva, Bolshakovs 2010), and the objective function f is specified as follows:…”

Section: Problem Statementmentioning

confidence: 99%

“…To estimate fitness of potential vehicle schedule solutions, a discrete-event simulation model in AnyLogic simulation software is built (Merkuryeva, Bolshakovs 2010). The vehicle moving time between two points is defined by a normally distributed random variable.…”

Section: Fitness Evaluation and Analysis Through Simulationmentioning

confidence: 99%

Simulation-Based Fitness Landscape Analysis and Optimisation of Complex Problems

Merkuryeva

Большаков

2015

Technological and Economic Development of Economy

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Widespread hard optimisation problems in economics and logistics are characterised by large dimensions, uncertainty and nonlinearity and require more powerful methods of stochastic optimisation that traditional ones. Simulation optimisation is a powerful tool for solving these problems. Moreover, fitness landscape analysis techniques provide an efficient approach to better selection of a suitable optimisation algorithm. The concept and techniques of fitness landscape analysis are described. A formalised scheme for simulation optimisation enhanced with fitness landscape analysis is given. Benchmark fitness landscape analysis is performed to find relations between efficiency of an optimisation algorithm and structural features of a fitness landscape. Case study in simulation optimisation of vehicle routing and scheduling is described. Various optimisation scenarios with application of the fitness landscape analysis are discussed and investigated.

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Vehicle Schedule Simulation with AnyLogic

Cited by 34 publications

References 5 publications

Pedestrians’ road crossing behaviour in front of automated vehicles: Results from a pedestrian simulation experiment using agent-based modelling

Pedestrians’ road crossing behaviour in front of automated vehicles: Results from a pedestrian simulation experiment using agent-based modelling

Assessing the Environmental Benefits of Dry Port Usage: A Case of Inland Container Transport in Turkey

Simulation-Based Fitness Landscape Analysis and Optimisation of Complex Problems

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