Modelling of Driver and Pedestrian Behaviour – A Historical Review

Babojelić, Karlo; Novačko, Luka

doi:10.7307/ptt.v32i5.3524

Cited by 15 publications

(11 citation statements)

References 77 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In terms of human resource management ideas and human resource management models, the theoretical results of strategic human resource management based on national conditions are presented, and the formulation and selection of human resource strategies are thoroughly analysed and discussed, drawing on foreign research results. e problems of (strategic) human resource management are analysed, and the current research in this field of strategic human resource management is sorted out, starting from identifying the meaning of strategic human resource management, putting forward the problems in theoretical construction and the selection and measurement of research objects, and making an in-depth analysis of possible future research directions [6]. A model of HR strategy improvement based on GREP is proposed; a model of HR strategy based on job qualifications is proposed [7].…”

Section: Related Workmentioning

confidence: 99%

Construction and Simulation of a Strategic HR Decision Model Based on Recurrent Neural Network

Zhang

et al. 2022

Journal of Mathematics

View full text Add to dashboard Cite

In this paper, RNN (Recurrent Neural Network) algorithm is used to conduct an in-depth analysis of HR strategic decision-making and an HR strategic decision model is constructed for simulation. The four evaluation dimensions of index screening are extracted, the generalized gray correlation analysis is applied to screen the initial selection indexes of HR strategic decision-making, and then the HR strategic decision-making index system of power supply enterprises is constructed. On this basis, the applicability of the BP neural network in HR strategic decision-making is analysed and demonstrated, a BP neural network-based HR strategic decision-making model for power supply enterprises is constructed, and the rationality of the model is illustrated through the model training and testing. Finally, an empirical study is conducted with S power supply company as an example to illustrate the operability of the BP network model for HR strategic decision-making. The results of this paper provide a scientific basis for human resource decision-making in power supply enterprises and provide theoretical support for promoting the healthy development of power supply enterprises. Improving the level of human resource management can make fuller use of human resources and realize the strategic goals of the enterprise. A strategy for optimizing the training of hybrid convolutional neural networks is proposed, using an exponential linear unit activation function to solve the problem of neuron dead zones, a hybrid pooling strategy is used to improve the problem of feature information loss in maximum pooling processing, and an improved cross-entropy loss function is used to solve the problem of insufficient learning of difficult classification samples. The optimization of the model training process is finally completed, and the recommendation quality is improved. The Bayesian probability distribution table is learned to be filled in the expert data set; finally, the accuracy and effectiveness of the model are tested on the experimental platform. The results of the experiments show that the established Bayesian model beats the platform’s built-in intelligent method with a 78.2% win rate. That is, the model can make intelligent recommendations for strategies in staffed and unmanned platform decision-making and command-and-control combat units to execute tactical actions to achieve the best operational effectiveness.

show abstract

Section: Related Workmentioning

confidence: 99%

Construction and Simulation of a Strategic HR Decision Model Based on Recurrent Neural Network

Zhang

et al. 2022

Journal of Mathematics

View full text Add to dashboard Cite

show abstract

“…The gathering of large crowds gathering is common in different public spaces. They may be subject to unexpected incidents and many studies have sought to improve the efficiency of evacuation planning to effective measures for large-scale crowd management (Babojelić and Novacko, 2020). However, in order to further develop research on pedestrian flows there is a need to overcome a series of obstacles such as shortage of evaluation data and uncertain pedestrian-related incidents (Shirvani et al, 2020;Wi-jermans and Templeton, 2022).…”

Section: Purposementioning

confidence: 99%

“…To do this, much relevant theoretical research and field observations have been conducted so that regular patterns of pedestrian flow in different scenarios can be identified (Rozo et al, 2019;Feng et al, 2021). Despite of much research associated with individual behaviours, few systematic characteristics of pedestrian movement has been discovered (Babojelić and Novacko, 2020). One of the main barriers is the lack of experimental data that captures individual behaviours realistically, which may adversely affect the effectiveness of large-scale evacuation planning as well as crowd management.…”

Section: Purposementioning

confidence: 99%

An evacuation simulation model of pedestrian flow using Bayesian Nash equilibrium and a Multi-Agent System

Wang

Ge²,

Comber³

2022

AGILE GIScience Ser.

View full text Add to dashboard Cite

Abstract. The shortage of experimental data for individual behaviours has hampered systematic research on pedestrian behaviours and the refined development of evidence informed rules for pedestrian movement in simulation models. This research proposes an evacuation simulation model of pedestrian flow based on Bayesian Nash Equilibrium (BNE) and Multi-Agent System (MAS). In this paper, BNE was used to augment the logics of pedestrian decision-making processes in an evacuation MAS simulation and to improve evacuating agents’ movement and behaviours. A detailed introduction of the construction process and implementation details for the initial model as well as the visualization of experiment results are provided in this paper. Limitations and several potential future research directions are also identified.

show abstract

“…Microsimulation models are dynamic, stochastic, discrete modeling techniques that simulate the movement of individual vehicles based on car following, lane changing and gap acceptance algorithms that are updated several times each second [32]. Authors in [33] analyzed majority of existing car-following and lane changing models in simulation tools. These interactions between vehicles provide a basis for calculating vehicle delay times and other parameters important for evaluation.…”

Section: Development Of Microsimulation Modelmentioning

confidence: 99%

Simulation-Based Public Transport Priority Tailored to Passenger Conflict Flows: A Case Study of the City of Zagreb

Novačko

Babojelić

Dedić³

et al. 2021

Applied Sciences

Self Cite

View full text Add to dashboard Cite

Prioritizing public transport is one of the most effective measure to increase the attractiveness and competitiveness of public transport in relation to individual vehicles. The main goal of this study was to examine the possibilities for reducing the travel time of tram vehicles by giving priority at signalized intersections in terms of sharing the traffic lane with personal vehicles and under conditions of strong conflict flows with private transport. For this purpose, we used the simulation tool VISSIM and its module EPICS. A methodology for determining weighting factors for prioritizing public transport flows was developed based on conflicting passenger flows in public transport vehicles and passenger cars. Three scenarios were tested in the study area: (1) “do nothing”; (2) unconditional priority; and (3) conditional priority. The results showed that unconditional priority led to unsustainable traffic conditions for personal vehicles and public transport. In contrast, conditional priority reduced the travel time of public transport on certain corridors by between 7.64% and 18.76% in the morning peak period, and 5.60% to 22.50% in the afternoon peak period.

show abstract

Modelling of Driver and Pedestrian Behaviour – A Historical Review

Cited by 15 publications

References 77 publications

Construction and Simulation of a Strategic HR Decision Model Based on Recurrent Neural Network

Construction and Simulation of a Strategic HR Decision Model Based on Recurrent Neural Network

An evacuation simulation model of pedestrian flow using Bayesian Nash equilibrium and a Multi-Agent System

Simulation-Based Public Transport Priority Tailored to Passenger Conflict Flows: A Case Study of the City of Zagreb

Contact Info

Product

Resources

About