Citation

Zhu H, Nakamura H, Alhajyaseen W, Iryo-Asano M. Transp. Res. Rec. 2020; 2674(5): 475-485.

Copyright

(Copyright © 2020, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/0361198120916477

PMID

unavailable

Abstract

Arterials are important transportation facilities, undertaking the two functions of mobility and accessibility. In the urban area, signalized intersections along arterials are usually closely spaced and bear heavy traffic pressure. Capacities of intersections can be reduced by downstream intersections even without having spillback. This effect will be accumulated and amplified back along the traffic direction and may lead to severe congestion in the upstream intersection which can be frequently observed, especially during peak hours. However, existing traffic simulators cannot capture this phenomenon accurately because they ignore the capacity drop before spillback happens. In this study, downstream influence is quantified by a virtual optimal speed (vop). vop is the speed by which the upstream platoon reaches the endpoint of the queue ahead when the last vehicle in the downstream queue just starts. Based on that, two piecewise regression models, for start-up lost time and saturation flow rate, are formulated to estimate the capacity reduction. These regression models are further introduced to improve the modified cell transmission model (CTM). The result of the simulation experiment shows that the proposed CTM model has better performance in simulating traffic flow on signalized arterials than the existing CTM, especially in reproducing the traffic congestion in upstream. The analysis emphasized the importance of considering the downstream influence when simulating the traffic on signalized arterials. Finally, a sensitivity analysis is designed to further reveal the causes of upstream congestion.

Language: en