TY - GEN
T1 - A Modified Pressure Model for Max-Pressure Traffic Signal Control
AU - Zoabi, Razi
AU - Haddad, Jack
N1 - Publisher Copyright: © 2024 EUCA.
PY - 2024
Y1 - 2024
N2 - In this paper, we advance the state-of-the-art of Max-Pressure traffic signal control by considering modeling aspect of enhancing the calculation of pressure function. First, we stress out that the conventional pressure model does not consider the distribution of the vehicles between the lanes, and it over-calculates the pressure function when multiplying with the saturation flow of the movement. We conducted a thorough analysis of the existing pressure calculation model. The model's inability to distribute pressure equitably could skew the controller's policy optimization, potentially leading to unfair decisions. Second, the impact of introduced modification is investigated through simulation case studies. The results indicate that the Max-Pressure control policy has been significantly improved. This underlines the importance of accurately characterizing the parameters within the Max-Pressure controller, which is crucial for improved outcomes and more effective decision-making processes.
AB - In this paper, we advance the state-of-the-art of Max-Pressure traffic signal control by considering modeling aspect of enhancing the calculation of pressure function. First, we stress out that the conventional pressure model does not consider the distribution of the vehicles between the lanes, and it over-calculates the pressure function when multiplying with the saturation flow of the movement. We conducted a thorough analysis of the existing pressure calculation model. The model's inability to distribute pressure equitably could skew the controller's policy optimization, potentially leading to unfair decisions. Second, the impact of introduced modification is investigated through simulation case studies. The results indicate that the Max-Pressure control policy has been significantly improved. This underlines the importance of accurately characterizing the parameters within the Max-Pressure controller, which is crucial for improved outcomes and more effective decision-making processes.
UR - http://www.scopus.com/inward/record.url?scp=85200562175&partnerID=8YFLogxK
U2 - https://doi.org/10.23919/ECC64448.2024.10590907
DO - https://doi.org/10.23919/ECC64448.2024.10590907
M3 - منشور من مؤتمر
T3 - 2024 European Control Conference, ECC 2024
SP - 3370
EP - 3377
BT - 2024 European Control Conference, ECC 2024
T2 - 2024 European Control Conference, ECC 2024
Y2 - 25 June 2024 through 28 June 2024
ER -