Research on the influence of multiple historical speed information with different weight distribution on traffic flow stability

Yiru Mei, Xiaoqun Zhao, Yeqing Qian, Shangzhi Xu and Zhipeng Li

Physica A: Statistical Mechanics and its Applications, 2021, vol. 563, issue C

Abstract: This paper attempts to study the use of multiple historical speed information of the target vehicle as an auxiliary control strategy for vehicle power output, which is different from other single-data self-stability control modes. We separately study the different weight distributions of historical data with using data completely recorded and part of the using data randomly lost. Then we compare the different coefficient distributions, and find that considering the reversed Poisson distribution of data in driving with complete data recorded is more beneficial to the stability of traffic flow than other distributions, but the traffic flow stability is most easily affected after the data is lost during driving operation. Furthermore, we try to fill the lost data with the remaining recorded data in the case of long-term defects in the use of data, trying to make up for the lack of reversed Poisson weight distribution.

Keywords: Traffic model; Multiple historical data; Different memory distribution modes; Numerical simulations (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:563:y:2021:i:c:s0378437120307639

DOI: 10.1016/j.physa.2020.125438

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