TY - GEN
T1 - Impact of the Entry Time Model on Connected and Automated Vehicle (CAV) Platoon Formation
AU - Hurtado-Beltran, Antonio
AU - Vakilzadian, Hamid
AU - Rilett, Laurence R.
N1 - Funding Information:
The authors would like to thank the Nebraska Transportation Center for providing the necessary technical tools used in this research. We would also thank the Fulbright Program for funding three years of the doctoral program of Antonio Hurtado-Beltran. The contents of this paper reflect the views of the authors, who are responsible for the facts and the accuracy of the information presented herein and are not necessarily representative of any group or agency.
PY - 2020/7
Y1 - 2020/7
N2 - One of the most important characteristics of a microsimulation is the ability to model the temporal and spatial nature of traffic demand. The majority of microsimulation packages use the exponential time headway model to introduce the driver-vehicle units in the network because it is easy to code, has low processing demand, and if there is no platooning effects in the network, it fits standard traffic flow theory. However, various empirical studies have shown that time headways can follow different statistical distributions depending on traffic conditions. The purpose of this paper is to analyze the effect of the entry time model used in the vehicle generation on connected and automated vehicle (CAV) platoon formation on highways. A comparison between the exponential and lognormal models was performed in which the stochastic attributes of the driver-vehicle units were controlled using the component object model (COM) interface of VISSIM 20. It was found that the effect that the entry time model had on platoon formation dissipated after a relatively short travel distance. In addition, it was found that the CAV platoon size and frequency is a function of underlying traffic conditions. Modelers may have to use longer than normal input links to achieve the appropriate platoon size and frequency metrics necessary to model CAV technology. This paper emphasizes the need to have a deep understanding of the underlying logic of traffic microsimulation models, and the effect of this logic on the reliability of the results when modeling traffic and disruptive technologies such as CAV platoons.
AB - One of the most important characteristics of a microsimulation is the ability to model the temporal and spatial nature of traffic demand. The majority of microsimulation packages use the exponential time headway model to introduce the driver-vehicle units in the network because it is easy to code, has low processing demand, and if there is no platooning effects in the network, it fits standard traffic flow theory. However, various empirical studies have shown that time headways can follow different statistical distributions depending on traffic conditions. The purpose of this paper is to analyze the effect of the entry time model used in the vehicle generation on connected and automated vehicle (CAV) platoon formation on highways. A comparison between the exponential and lognormal models was performed in which the stochastic attributes of the driver-vehicle units were controlled using the component object model (COM) interface of VISSIM 20. It was found that the effect that the entry time model had on platoon formation dissipated after a relatively short travel distance. In addition, it was found that the CAV platoon size and frequency is a function of underlying traffic conditions. Modelers may have to use longer than normal input links to achieve the appropriate platoon size and frequency metrics necessary to model CAV technology. This paper emphasizes the need to have a deep understanding of the underlying logic of traffic microsimulation models, and the effect of this logic on the reliability of the results when modeling traffic and disruptive technologies such as CAV platoons.
KW - arrival model
KW - CAV
KW - microsimulation
KW - platoon
KW - Time headway
KW - vehicle generation
KW - VISSIM
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U2 - 10.1109/EIT48999.2020.9208301
DO - 10.1109/EIT48999.2020.9208301
M3 - Conference contribution
AN - SCOPUS:85092505858
T3 - IEEE International Conference on Electro Information Technology
SP - 655
EP - 662
BT - 2020 IEEE International Conference on Electro Information Technology, EIT 2020
PB - IEEE Computer Society
T2 - 2020 IEEE International Conference on Electro Information Technology, EIT 2020
Y2 - 31 July 2020 through 1 August 2020
ER -