Towards large-scale what-if traffic simulation with exact-differential simulation

Hanai, Masahiro; Suzumura, Toyotaro; Theodoropoulos, Georgios; Perumalla, Kalyan S.

doi:10.1109/wsc.2015.7408212

Cited by 4 publications

(7 citation statements)

References 8 publications

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“…Hanai et al [109] described a module which is responsible for a distributed filtering algorithm for data gathered from a city network. This module is a part of a distributed system which optimises traffic in the Tokyo Bay area (Japan).…”

Section: Literature Analysismentioning

confidence: 99%

“…With a growing number of cloud computing solutions in the research world, we think that emerging cloud computing technologies could solve problems which need significant computational power as they can be scaled and adjusted to a problem. A prominent example of the HPC type of work is [128, 107, 109]. However, more extensive investigation in the cloud computing domain and fast accident‐solving is still needed.…”

Section: Observations and Open Areasmentioning

confidence: 99%

See 1 more Smart Citation

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%

Section: Observations and Open Areasmentioning

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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“…In our simulation, events received from other LPs are buffered before they are inserted to the event queues (line 1). If a newly received event has a receiving time smaller than the minimum loaded time (which is initialized to infinity), then the stored events, anti-messages, and states are loaded from the storage (lines 7-9) before they are inserted to the queues (lines [14][15][16][17][18][19][20][21]. After that, the minimum loaded time is updated to the new received time (line 22), and then the newly received event is inserted to the event queue as usual (line 25).…”

Section: Implementation Of Repeating Simulationmentioning

confidence: 99%

“…The difference from our proposal is that such techniques do not have a "differential" feature, namely, the cloning technique does not simulate a part of the entire state space but instead the entire simulation is replicated from the designated time. In our previous work, we have shown how cloning can be used with our exact-differential approach in traffic simulation scenarios [14].…”

Section: Related Workmentioning

confidence: 99%

Exact-Differential Simulation

Hanai

Suzumura

Liu

et al. 2019

ACM Trans. Model. Comput. Simul.

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Using computer simulation to analyze large-scale discrete event systems requires repeated executions with various scenarios or parameters. Such repeated executions can induce significant redundancy in event processing when the modification from a prior scenario to a new scenario is relatively minor, and when the altered scenario influences only a small part of the simulation. For example, in a city-scale traffic simulation, an altered scenario of blocking one junction may only affect a small part of the city for considerable length of time. However, traditional simulation approaches would still repeat the simulation for the whole city even when the changes are minor. In this article, we propose a new redundancy reduction technique for large-scale discrete event simulations, called exact-differential simulation, which simulates only the altered portions of scenarios and their influences in repeated executions while still achieving the same results as the re-execution of entire simulations. This article presents the main concepts of the exact-differential simulation, the design of its algorithm, and an approach to build an exact-differential simulation middleware that supports multiple applications of discrete event simulation. We also evaluate our approach by using two case studies, PHOLD benchmark and a traffic simulation of Tokyo.

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“…Chen et al [15,14] In recent works on simulation cloning, Hanai et al [36,37] The term "agent cloning" was also used in the literature, however, with a different meaning. In [89], an approach is proposed to replicate working agents to improve the efficiency of the system.…”

Section: Simulation Cloning Techniquesmentioning

confidence: 99%

Supporting agent-based simulations on GPU

Li¹

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First and foremost, I would like to express my earnest and deepest gratitude to my PhD supervisor, Professor Cai Wentong, for his remarkable guidance, constant help and support, and lots of caring and patience in the past five years. He is a mentor of a lifetime to me, and I am honored to be his student. I believe that his immense knowledge, passion, and rigorous attitude in research not only help me completing this thesis, but will also influence my career and life in the future. I would like to thank my parents, grandparents, Aunt Qing, Cousin Ruixu, and other family members for their love, encouragements and confidences in me. Especially, I would like to thank my girlfriend, Jingyi. We have been in a long distance relationship for over three years, and she has always been patient and supportive, and looking forward for the reunion. Taking a PhD is not easy. They give me the strength to carry on. I would like to acknowledge the help and support provided by the wonderful professors and staffs in School of Computer Science and Engineering. I appreciate Professor Stephen John Turner for his guidance as my co-supervisor in the first three and half years of my PhD study. I appreciate Professor Tang Xueyan for offering me a research assistant position to support my last year of the study. I have been also learning a lot from him in our weekly meetings. I appreciate Ms. Ng-Goh Siew Lai Irene for her great skills of building the experiment test bed. I also want to express my thanks to Professor Sun Chengzhen, Professor He Bingsheng, Professor Xing Zhenchang, and many other professors for their help in many aspects.

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Towards large-scale what-if traffic simulation with exact-differential simulation

Cited by 4 publications

References 8 publications

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

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

Exact-Differential Simulation

Supporting agent-based simulations on GPU

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