Instability in car-following behavior: new Nagel–Schreckenberg type cellular automata model

Huang, Yong-Xian; Guo, Ning; Jiang, Rui; Hu, Mao-Bin

doi:10.1088/1742-5468/aad3f9

Cited by 5 publications

(2 citation statements)

References 19 publications

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“…Trac congestion seriously reduces people's quality of life. In order to alleviate trac congestion, many studies have been done over the years on various aspects of urban trac, such as optimization of trac flow and pedestrian flow [1,2], optimization of trac signals [3][4][5][6][7][8], advanced routing strategies [9][10][11][12] and ecient control measures [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Improve traffic efficiency with advanced travel time feedback in urban networks

Chen

Hao

et al. 2019

J. Stat. Mech.

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With the development of modern intelligent traffic system technology, the travel time information can be collected and processed to provide route-choice suggestions to travellers. However, due to the complex nature of a traffic system, the feedback of traffic information might lead to undesired congestion in some concerned areas (such as the central business district). In this paper, an improved time shortest path strategy (ITSP) based on advanced travel time information feedback is proposed and applied in a Manhattan-like urban traffic system. With the strategy, the link travel time in the concerned area is adjusted by a travel-cost-related coefficient before being sent to final users. We study the effects of ITSP on traffic performance based on cellular automaton model of urban traffic. What we found most interesting is that when providing the traffic time information with an slightly larger than 1.0 (typically ), the performance of the system will be enhanced as compared to the situations of no information feedback or providing the real travel time information. Simulation results show that, ITSP can increase the average arrival rate and the traffic flow in scenario of fixed total number of vehicles. Vehicle density decreases with ITSP strategy under scenario with varying total number of vehicles, which helps to avoid traffic gridlock and improve the system reliability. Furthermore, the effects of different size of core areas and different origin-destination patterns are also explored. All the results show that ITSP can improve the traffic performance of network systems.

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Section: Introductionmentioning

confidence: 99%

Improve traffic efficiency with advanced travel time feedback in urban networks

Chen

Hao

et al. 2019

J. Stat. Mech.

View full text Add to dashboard Cite

show abstract

“…As with the OV model, the NaSch model is also able to capture a wide range of traffic phenomenon such as the existence of a free-flowing and a congested phase. The simplicity of the rule-based evolution results in the NaSch model being highly popular in the traffic modelling community, from theoretically motivated studies [23,24] to studies with high practical applicability [25][26][27][28][29][30][31]. Most notably, the simplicity of the NaSch model -or discrete models in general -facilitates analytical predictions [32,33] on various macroscopic variables, which can provide valuable insights in understanding a complex system.…”

Section: Chapter 1 Introductionmentioning

confidence: 99%