Bus lane with intermittent priority (BLIP) is an innovative method to improve the reliability of bus services while promoting efficient usage of road resources. Vehicle-to-vehicle (V2V) communication is an advanced technology that can greatly enhance the vehicle mobility, improve traffic safety, and alleviate traffic jams. To explore the benefits of BLIP operation under a connected environment, this study proposed a three-lane cellular automata (CA) model under opening boundary condition. In particular, a mandatory BLIP lane-changing rule is developed to analyze special asymmetric lane-changing behaviors. To improve the simulation accuracy, a smaller cell size is used in the CA model. Through massive numerical simulations, the benefits and influences of BLIP are explored in this paper. They include impacts on neighborhood lanes such as traffic density increasing and average speed decreasing, lane-changing behaviors, lane usage, and the impacts of bus departure interval and clear distance on the road capacity of BLIP. Analysis of traffic flow characteristics of BLIP reveals that there is a strong relationship among bus departure interval, clear distance, and road capacity. Furthermore, setting conditions for deployment of BLIP under the V2V environment such as reasonable departure interval, clear distance, and traffic density are obtained.
This paper aims to analyze the impact of trucks on traffic flow and propose an improved cellular automaton model, which considers both the performance difference between passenger cars and trucks and the behaviour change of passenger cars under the impact of trucks. A questionnaire survey has been conducted to find out whether the impact of trucks exists and how the behaviour of passenger car drivers changes under the impact of trucks. The survey results confirm that the impact of trucks exists and indicate that passenger car drivers will enlarge the space gap, decelerate, and change lanes in advance when they are affected. Simulation results show that traffic volume is still affected by percentages of trucks in the congestion phase in the proposed model compared with traditional heterogeneous cellular automaton models. Traffic volume and speed decrease with the impact of trucks in the congestion phase. The impact of trucks can increase traffic congestion as it increases. However, it has different influences on the speed variance of passenger cars in different occupancies. In the proposed model, the relative relationship of the space gap between car-following-truck and car-following-car is changeable at a certain value of occupancy, which is related to the impact of trucks.
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