TY - JOUR
T1 - Multiclass multilane model for freeway traffic mixed with connected automated vehicles and regular human-piloted vehicles
AU - Pan, Tianlu
AU - Lam, William H.K.
AU - Sumalee, Agachai
AU - Zhong, Renxin
N1 - Funding Information:
This work was supported by the Hong Kong Polytechnic University: [grant number 1-ZVBY and 1-ZVBZ]; Research Grants Council, University Grants Committee: [grant number PolyU 152074/14E]. The work described in this paper was jointly supported by a Postgraduate Studentship of the Hong Kong Polytechnic University, the Research Grants Council, University Grants Committee (Project No. PolyU 152074/14E) and the Research Institute for Sustainable Urban Development (RISUD) of the Hong Kong Polytechnic University (Project Nos. 1-ZVBY and 1-ZVBZ).
Publisher Copyright:
© 2019 Hong Kong Society for Transportation Studies Limited.
PY - 2021/1
Y1 - 2021/1
N2 - In view of the advantages and a promising market prospect of the emerging connected automated vehicles (CAVs), it will be very likely that the roadway is shared by CAVs and RHVs in the near future. To support traffic control design, this paper develops a multiclass multilane cell transmission model (CTM) to simulate traffic flow dynamics mixed with CAVs and RHVs by capturing the interaction between the two vehicle classes. First, headway distributions and variations in the fundamental diagram with respect to different penetration rates of CAVs are quantified. Then, the minimum headway acceptance criteria are determined for the lane changing (LC) maneuvers proposed by CAVs and RHVs with consideration on drivers’ anticipation. Finally, the cell-lane-specific multiclass flow conservation law is developed to propagate traffic flow and density considering the vehicle LC maneuvers. Numerical simulations explore the potential operational capacity increase, delay reduction, and traffic flow smoothing under several penetration scenarios.
AB - In view of the advantages and a promising market prospect of the emerging connected automated vehicles (CAVs), it will be very likely that the roadway is shared by CAVs and RHVs in the near future. To support traffic control design, this paper develops a multiclass multilane cell transmission model (CTM) to simulate traffic flow dynamics mixed with CAVs and RHVs by capturing the interaction between the two vehicle classes. First, headway distributions and variations in the fundamental diagram with respect to different penetration rates of CAVs are quantified. Then, the minimum headway acceptance criteria are determined for the lane changing (LC) maneuvers proposed by CAVs and RHVs with consideration on drivers’ anticipation. Finally, the cell-lane-specific multiclass flow conservation law is developed to propagate traffic flow and density considering the vehicle LC maneuvers. Numerical simulations explore the potential operational capacity increase, delay reduction, and traffic flow smoothing under several penetration scenarios.
KW - capacity variation
KW - connected automated vehicle (CAV)
KW - multiclass multilane cell transmission model
KW - penetration rate
KW - Vehicle automation and communication system (VACS)
UR - http://www.scopus.com/inward/record.url?scp=85061268004&partnerID=8YFLogxK
U2 - 10.1080/23249935.2019.1573858
DO - 10.1080/23249935.2019.1573858
M3 - Journal article
AN - SCOPUS:85061268004
SN - 2324-9935
VL - 17
SP - 5
EP - 33
JO - Transportmetrica A: Transport Science
JF - Transportmetrica A: Transport Science
IS - 1
ER -