Approximately Orchestrated Routing and Transportation Analyzer: Large-scale traffic simulation for autonomous vehicles
作者： Dustin Carlino , Mike Depinet , Piyush Khandelwal , Peter Stone
DOI: 10.1109/ITSC.2012.6338701
关键词: Engineering 、 Embedded system 、 Mobile robot 、 Traffic optimization 、 Digital mapping 、 Traffic simulation 、 Data modeling 、 Multi-agent system 、 Intersection (aeronautics) 、 Routing (electronic design automation) 、 Real-time computing
摘要: Autonomous vehicles have seen great advancements in recent years, and such are now closer than ever to being commercially available. The advent of driverless cars provides opportunities for optimizing traffic ways not possible before. This paper introduces an open source multiagent microscopic simulator called AORTA, which stands Approximately Orchestrated Routing Transportation Analyzer, designed autonomous at a city-wide scale. AORTA creates scale simulations the real world by generating maps using publicly available road data from OpenStreetMap (OSM). allows be set up through desired region anywhere matter minutes. optimization creating intelligent behaviors individual driver agents intersection policies followed these agents. These define how interact with one another, control when they cross intersections, route their destination. demonstrates simple application experiment testing
sci-hub.se 参考文章(14)
Daniel Krajzewicz, Michael Behrisch, Jakob Erdmann, Laura Bieker, SUMO - Simulation of Urban MObility An Overview international conference on advances in system simulation. pp. 55- 60 ,(2011)
Georg Hertkorn, Daniel Krajzewicz, Julia Ringel, Peter Wagner, Preparation of Digital Maps for Traffic Simulation; Part 1: Approach and Algorithms EUROSIS-ETI. ,(2005)
Peter Hart, Nils Nilsson, Bertram Raphael, A Formal Basis for the Heuristic Determination of Minimum Cost Paths IEEE Transactions on Systems Science and Cybernetics. ,vol. 4, pp. 100- 107 ,(1968) , 10.1109/TSSC.1968.300136
Zhen Shen, Kai Wang, Fenghua Zhu, Agent-based traffic simulation and traffic signal timing optimization with GPU international conference on intelligent transportation systems. pp. 145- 150 ,(2011) , 10.1109/ITSC.2011.6083080
K Nagel, A Schleicher, Microscopic traffic modeling on parallel high performance computers parallel computing. ,vol. 20, pp. 125- 146 ,(1994) , 10.1016/0167-8191(94)90117-1
José L. F. Pereira, Rosaldo J. F. Rossetti, An integrated architecture for autonomous vehicles simulation acm symposium on applied computing. pp. 286- 292 ,(2012) , 10.1145/2245276.2245333
Vikram Manikonda, Renato Levy, Goutam Satapathy, David J. Lovell, Peter C. Chang, Anna Teittinen, Autonomous agents for traffic simulation and control Transportation Research Record. ,vol. 1774, pp. 1- 10 ,(2001) , 10.3141/1774-01
Peter Hidas, MODELLING LANE CHANGING AND MERGING IN MICROSCOPIC TRAFFIC SIMULATION Transportation Research Part C-emerging Technologies. ,vol. 10, pp. 351- 371 ,(2002) , 10.1016/S0968-090X(02)00026-8
Mark Brackstone, Mike McDonald, Car-following: a historical review Transportation Research Part F-traffic Psychology and Behaviour. ,vol. 2, pp. 181- 196 ,(1999) , 10.1016/S1369-8478(00)00005-X
Tsz-Chiu Au, Neda Shahidi, Peter Stone, Enforcing liveness in autonomous traffic management national conference on artificial intelligence. pp. 1317- 1322 ,(2011)