An agent-based cellular automaton cruising-for-parking simulation

Horni, Andreas; Montini, Lara; Waraich, Rashid A.; Axhausen, Kay W.

doi:10.1179/1942787513y.0000000004

Cited by 47 publications

(26 citation statements)

References 27 publications

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“…Its popularity gains partly due to its flexible framework to incorporate traffic control and many other interesting components. For example, Horni et al (2013) used CA model to conduct parking simulation, and they incorporated agent-based techniques as well [13]. Chai et al (2015) made use of CA model to simulate traffic streams at signalized intersections.…”

Section: Introductionmentioning

confidence: 99%

Micro-simulation model of two-lane freeway vehicles for obtaining traffic flow characteristics including safety condition

Yang

Luo

2016

J. Mod. Transport.

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Unidirectional two-lane freeway is a typical and the simplest form of freeway. The traffic flow characteristics including safety condition on two-lane freeway is of great significance in planning, design, and management of a freeway. Many previous traffic flow models are able to figure out flow characteristics such as speed, density, delay, and so forth. These models, however, have great difficulty in reflecting safety condition of vehicles. Besides, for the cellular automation, one of the most widely used microscopic traffic simulation models, its discreteness in both time and space can possibly cause inaccuracy or big errors in simulation results. In this paper, a micro-simulation model of two-lane freeway vehicles is proposed to evaluate characteristics of traffic flow, including safety condition. The model is also discrete in time but continuous in space, and it divides drivers into several groups on the basis of their preferences for overtaking, which makes the simulation more aligned with real situations. Partial test is conducted in this study and results of delay, speed, volume, and density indicate the preliminary validity of our model, based on which the proposed safety coefficient evaluates safety condition under different flow levels. It is found that the results of this evaluation coincide with daily experience of drivers, providing ground for effectiveness of the safety coefficient.

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Section: Introductionmentioning

confidence: 99%

Micro-simulation model of two-lane freeway vehicles for obtaining traffic flow characteristics including safety condition

Yang

Luo

2016

J. Mod. Transport.

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“…Further reading related to destination choice is: Horni et al (2013b),for parking, or , about coupling customers' and retailers' choices or, in other words, supply and demand.…”

Section: Further Readingmentioning

confidence: 99%

“…Beyond walking distance disutility, this scoring function could also include additional features like cost, or even estimated parking search times, using models like Horni et al (2013a).…”

Section: Parking Choice Modelmentioning

confidence: 99%

The Multi-Agent Transport Simulation MATSim

Axhausen¹

2016

499

123

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PrefaceDeveloping complex so ware for over a decade with a heterogeneous group of engineers and scientists, each with widely di erent skill levels and expertise across multiple locations around the world, requires dedication and mechanisms unusual for a university environment. This book is one of these mechanisms. It allows us, collectively, to take stock and present a coherent state-of-the-system: for us and anyone interested in this approach. It highlights basics for the student who wants to undertake a small rst research project as part of his or her degree, provides a description of the main functionalities, in detail, for the engineer setting up MATSim (MultiAgent Transport Simulation) to conduct a policy analysis and, nally, ts the approach into the theoretical background of complex systems in computer science and physics.The choice of the additional e-book format is an advantage, as it allows us to keep the book upto-date with future chapters, revisions and, if necessary, errata. Equally importantly it allows you, the readers, to select those sections relevant to your needs.The book comes at an important time for the system; for most of the rst decade, its use was limited to the original developers and users in Berlin and Zürich. It is now much more widely consulted around the world, as we document in the chapter summarizing contributions on scenarios so far.Scenario: This term will occur again and again. In MATSim context, it is de ned as the combination of speci c agent populations, their initial plans and activity locations (home, work, education), the network and facilities where, and on which, they compete in time-space for their slots and modules, i.e., behavioral dimensions, which they can adjust during their search for equilibrium. Within these scenarios, the user can experiment and explore with behavioral utility function parameters, with the sampling rate of the population between 1 % and 100 %, with algorithm parameters, e.g., the share of the sample engaged in replanning in any iteration, or behavioral dimensions or exact settings necessary to avoid gridlock due to the tra c ow dynamics. The creation of a scenario is a substantial e ort, and the framework makes a number of tools available to accelerate it: population synthesizers, network editors, network converters between popular formats and the MATSim representation, e.g., OSM (OpenStreetMap) or GTFS (General Transit Feed Speci cation), semi-automatic network matching to join information, among others.A large group of colleagues has been involved and many of them are contributors to this book; this is a list of those involved, other than ourselves, in Berlin, Singapore and Zürich. Additional contributors are mentioned as authors of their respective chapters in this book. We hope to acknowledge the contributions of more colleagues from other groups in future versions of this book and in the so ware.Special thanks go to a number of people who greatly helped improving this book beyond their own chapters. Benjamin Kickhöfer's deep knowledge of ...

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“…Alternative concepts include "smart vehicular technology" such as self-parking systems in which the technology is entirely vehicle-borne, "smart infrastructure" within the parking facility, to provide beyondline-of-sight (BLOS) information regarding parking space availability, and "parking information sharing," to provide parking variable message signs (parking VMS) (Sun et al [15], Ni and Sun [16]). One method frequently employed to analyze such information provision is via microscopic parking simulation (Horni et al [17], Dia [18], and Geng and Cassandras [19]). There are also examples of parking facilities in which the physical maneuvering of the vehicles is performed mechanically by the facility's "smart infrastructure."…”

Section: Introductionmentioning

confidence: 99%

Capacity Impacts and Optimal Geometry of Automated Cars’ Surface Parking Facilities

Kong

Vine

Liu

2018

Journal of Advanced Transportation

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The impact of Automated Vehicles (AVs) on urban geography has been widely speculated, though there is little quantitative evidence in the literature to establish the magnitude of such effects. To quantify the impact of the greater precision of automated driving on the spatial efficiency of off-street parking facilities, we develop a mixed integer nonlinear model (solved via a branch-and-cut approach) and present comparisons against industry-standard requirements for human-driving operation. We demonstrate that gains on the order of 40-50% in spatial efficiency (parking spaces per unit area) are in principle achievable while ensuring that each parked vehicle is independently accessible. We further show that the large majority of these efficiency gains can be obtained under current automotive engineering practice in which only the front two wheels pivot. There is a need for standardized methods that take the parking supply of a city as an input and calculate both the aggregate (citywide) efficiency impacts of automated driving and the spatial distribution of the effects. This study is intended as an initial step towards this objective.

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An agent-based cellular automaton cruising-for-parking simulation

Abstract: This paper reports on the development of an agent-based cruising-for-parking simulation using the cellular automaton approach. The software is ready for application in a realworld scenario and for calibration with empirical data currently surveyed at the authors' institute.

Cited by 47 publications

References 27 publications

Micro-simulation model of two-lane freeway vehicles for obtaining traffic flow characteristics including safety condition

Micro-simulation model of two-lane freeway vehicles for obtaining traffic flow characteristics including safety condition

The Multi-Agent Transport Simulation MATSim

Capacity Impacts and Optimal Geometry of Automated Cars’ Surface Parking Facilities

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