TY - GEN
T1 - RONIN
T2 - 22nd IEEE International Conference on High Performance Computing and Communications, 18th IEEE International Conference on Smart City and 6th IEEE International Conference on Data Science and Systems, HPCC-SmartCity-DSS 2020
AU - Saber, Takfarinas
AU - Cachard, Come
AU - Ventresque, Anthony
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - Road traffic prediction is a major challenge for urban operators and planners alike, as it is difficult to model (drivers' behaviours being complex). Different types of urban traffic simulators have been proposed in the past: macroscopic simulators, fast but not particularly accurate; microscopic simulators, accurate but slow; and mesoscopic simulators, a trade-off between macroscopic and microscopic simulators. The challenge is that a good simulator has to be both accurate and fast, as the prediction tasks required by traffic operators and planners often need to be done quickly. In this paper, we present RONIN, an open-source traffic simulator that is both orders of magnitude faster than the state-of-The-Art microscopic simulator (SUMO) while being more accurate than a typical macroscopic simulator. RONIN is designed as a mesoscopic urban traffic simulator and exploits the location of individual vehicles while also only estimating their trajectories. Besides, unlike most simulators, RONIN is interoperable with a microscopic simulator (i.e., SUMO) by design thus allowing the operators to mix microscopic and mesoscopic speed/accuracy in their traffic management.
AB - Road traffic prediction is a major challenge for urban operators and planners alike, as it is difficult to model (drivers' behaviours being complex). Different types of urban traffic simulators have been proposed in the past: macroscopic simulators, fast but not particularly accurate; microscopic simulators, accurate but slow; and mesoscopic simulators, a trade-off between macroscopic and microscopic simulators. The challenge is that a good simulator has to be both accurate and fast, as the prediction tasks required by traffic operators and planners often need to be done quickly. In this paper, we present RONIN, an open-source traffic simulator that is both orders of magnitude faster than the state-of-The-Art microscopic simulator (SUMO) while being more accurate than a typical macroscopic simulator. RONIN is designed as a mesoscopic urban traffic simulator and exploits the location of individual vehicles while also only estimating their trajectories. Besides, unlike most simulators, RONIN is interoperable with a microscopic simulator (i.e., SUMO) by design thus allowing the operators to mix microscopic and mesoscopic speed/accuracy in their traffic management.
KW - Load and Travel Time Estimation
KW - Mesoscopic Simulation
KW - Urban Traffic Simulation
UR - https://www.scopus.com/pages/publications/85105340514
U2 - 10.1109/HPCC-SmartCity-DSS50907.2020.00145
DO - 10.1109/HPCC-SmartCity-DSS50907.2020.00145
M3 - Conference Publication
T3 - Proceedings - 2020 IEEE 22nd International Conference on High Performance Computing and Communications, IEEE 18th International Conference on Smart City and IEEE 6th International Conference on Data Science and Systems, HPCC-SmartCity-DSS 2020
SP - 1104
EP - 1111
BT - Proceedings - 2020 IEEE 22nd International Conference on High Performance Computing and Communications, IEEE 18th International Conference on Smart City and IEEE 6th International Conference on Data Science and Systems, HPCC-SmartCity-DSS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 14 December 2020 through 16 December 2020
ER -
