Reducing Synchronization Overhead with Computation Replication in Parallel Agent-Based Road Traffic Simulation

Xu, Yadong; Viswanathan, V.; Cai, Wentong

doi:10.1109/tpds.2017.2714165

Cited by 6 publications

(1 citation statement)

References 22 publications

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“…In the research performed by Xu et al [106] optimisation is done by decreasing the number of synchronisations needed to create parallel agent simulations. The authors introduced redundancy into their computations which allowed them to reduce the time necessary for evaluating the planned scenario.…”

Section: Literature Analysismentioning

confidence: 99%

Recent advances in traffic optimisation: systematic literature review of modern models, methods and algorithms

Rydzewski¹,

Czarnul²

2020

IET intell. transp. syst

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Over the past few decades, the increasing number of vehicles and imperfect road traffic management have been sources of congestion in cities and reasons for deteriorating health of its inhabitants. With the help of computer simulations, transport engineers optimise and improve the capacity of city streets. However, with an enormous number of possible simulation types, it is difficult to grasp valuable, innovative solutions which are of the greatest value to city citizens. In this work, the authors expose various problems within this area having reviewed and analysed over 130 papers selected out of 1200 works in the field of urban simulations. The study describes the selection process of important papers and highlights characteristics of microsimulations, macrosimulations, computation optimisations and other approaches found in the literature which are especially useful and should be further built on in the future. They present and compare results provided in reviewed works in terms of throughput improvement, queue, waiting and travel time reduction, vehicle speed increase, speed‐ups as well as assumed simulation parameters. Finally, they focus on research gaps, such as a small number of works considering crisis simulations, few real‐world scale simulations as well as on software architectural changes and low‐level optimizations.

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Section: Literature Analysismentioning

confidence: 99%