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Signalised intersection control in a connected vehicle environment: User throughput maximisation strategy
Author(s) -
Mohammadi Roozbeh,
Roncoli Claudio,
Mladenović Miloš N.
Publication year - 2021
Publication title -
iet intelligent transport systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.579
H-Index - 45
eISSN - 1751-9578
pISSN - 1751-956X
DOI - 10.1049/itr2.12038
Subject(s) - intersection (aeronautics) , throughput , real time computing , computer science , exploit , prioritization , maximization , simulation , automotive engineering , engineering , transport engineering , wireless , mathematical optimization , telecommunications , computer security , mathematics , management science
Connected vehicle (CV) technology is expected to bring additional opportunities to share, collect, and exploit various information on vehicles and their occupants. Assuming that CVs are able to transmit on‐board users and vehicle data, a user‐based signal timing optimisation (UBSTO) strategy is proposed, designed to optimise user throughput for signalised intersections. In the CV environment, the inputs of the proposed algorithm consist of position and speed of CVs, as well as the number of passengers travelling in each vehicle, while the output is the optimum green time duration for each signal phase. In addition, authors' proposed strategy is able to adapt the cycle length to the traffic volume condition. In case of missing users data, the same strategy can also operate in vehicle‐based mode, where the objective is vehicle‐throughput maximization. The performance of the proposed strategy is compared with a fully actuated controller (FAC) in microscopic simulation, for several scenarios, including different CV penetration rates. Authors' findings show that UBSTO can effectively increase user throughput and decrease average user delay in comparison with FAC, while also prioritising vehicles with higher number of users on‐board. These findings have implications for further development of prioritization strategies for public transport and ride‐sharing vehicles.

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