The rapidly growing traffic demand and the slowly increasing traffic supply have produced an mounting contradiction, which is mainly manifested in cities as road congestion and unbalanced bidirectional traffic flow. Most of the reversible lanes are implemented on fixed sections and fixed times and are mainly guided by ground markings, road signs, railings, and traffic police officer. It requires a lot of human and material costs. And, the control effect is lagging and inaccurate. Aiming at these problems, a real-time dynamic reversible lane scheme in the Intelligent Cooperative Vehicle Infrastructure System (CVIS) was proposed. Traffic information was collected in real time through the CVIS, and a reversible lane scheme was established based on the real-time service level V/C and BRP functions. A lane change control model was applied to determine the number of lanes and the timing of lane changes. Then, the reversible lanes were managed in real time through intelligent road stud lights and light curtain walls. Buffer sections and no-entry sections were set to ensure reversible lanes operating safely and efficiently. VISSIM simulation was used for case analysis, and the results showed that compared with the traditional time-controlled reversible lane scheme, the real-time dynamic reversible lane scheme could reduce the average vehicle delay by 27.4% and decrease the vehicle VOC, CO and NOX emissions by 13.5%.
The HOV carpooling lane offers a feasible approach to alleviate traffic congestion. The connected vehicle environment is able to provide accurate traffic data, which could optimize the design of HOV carpooling schemes. In this paper, significant tidal traffic flow phenomenon with severe traffic congestion was identified on North Beijing road (bidirectional four-lane) and South Huaihai road (bidirectional six-lane) in Huai’an, Jiangsu Province. The historical traffic data of the road segments were collected through the connected vehicle environment facilities. The purpose of this study is to investigate the effect of adopting two HOV schemes (regular HOV scheme and reversible HOV carpooling scheme) on the urban arterial road under connected vehicle environment. VISSIM was used to simulate the proposed two HOV carpooling schemes at the mentioned road segment. The simulation results showed that the reversible HOV carpooling scheme could not only mitigate the traffic congestion caused by traffic tidal phenomenon but also improve the average speed and traffic volume of the urban arterial road segment, while the regular HOV scheme may exert a negative impact on the average speed and traffic volume on the urban arterial road segment.
Urban road networks are often affected by natural disasters, such as rainstorms, with consequences spreading from partial failures to massive network-wide disruptions. The pattern of road network resilience is grasped by capturing the changes in the failure process of the road network cascade. This research presents a method for dynamic evaluation of road network resilience, with extreme rainstorm weather as the background. The fundamental diagram of traffic flow is adopted into the shock wave model to obtain the congestion propagation and dissipation model with speed as input quantity. Then, it is networked and applied to the road network to develop a cascading failure model. The model can be used to identify critical nodes, combining the Monte Carlo method and Dijkstra algorithm, as well as to construct time-varying evolution scenarios of road network resilience when critical nodes are broken. Furthermore, VA (the variations of all OD pairs in the road network) and RI (the resilience indicators of road network) indexes for dynamic evaluation of road network resilience are developed, that visualize the resilience of the road network for a specific region, a specific event, and a specific time. In the case study, the proposed method is employed to evaluate the resilience of the urban road network under a real case of the Zhengzhou 720 rainstorm in China, and its practicality is verified.
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