Traffic Flow Characteristics and Lane Use Strategies for Connected and Automated Vehicles in Mixed Traffic Conditions

Abstract

Managed lanes, such as a dedicated lane for connected and automated vehicles (CAVs), can provide not only technological accommodation but also desired market incentives for road users to adopt CAVs in the near future. In this paper, we investigate traffic flow characteristics with two configurations of the managed lane across different market penetration rates and quantify the benefits from the perspectives of lane-level headway distribution, fuel consumption, communication density, and overall network performance. The results highlight the benefits of implementing managed lane strategies for CAVs: (1) A dedicated CAV lane significantly extends the stable region of the speed-flow diagram and yields a greater road capacity. As the result shows, the highest flow rate is 3400 vehicles per hour per lane at 90% market penetration rate with one CAV lane. (2) The concentration of CAVs in one lane results in a narrower headway distribution (with smaller standard deviation) even with partial market penetration. (3) A dedicated CAV lane is also able to eliminate duel-bell-shape distribution that is caused by the heterogeneous traffic flow. (4) A dedicated CAV lane creates a more consistent CAV density, which facilitates communication activity and decreases the probability of packet dropping.

Traffic Safety Sensitivity Analysis of Parameters Used for Connected and Autonomous Vehicle Calibration

“…Some studies have suggested lower values for CAVs than for HDVs [22,23], whereas others have considered higher values [15,19,29]. Furthermore, others have maintained the same behavioural pattern [1,18,24]. Karjanto et al [3] explained that the corresponding value should be related to the driving style.…”

“…Connected and autonomous vehicles (CAVs) fundamentally differ from human-driven vehicles (HDVs) in terms of their operational behaviour. CAVs can be adjusted to minimise emissions, improve fuel savings, and harmonise traffic flow due to their shorter reaction times [1][2][3][4][5]. Additionally, they are expected to change travel behaviour by generating new demand for very young, elderly, or disabled individuals, being utilized for freight transport, and impacting parking and ride-sharing patterns, thereby affecting the total vehicle miles travelled [6].…”

Autonomous Vehicles for Enhancing Expressway Capacity: A Dynamic Perspective

“…Furthermore, considering that unreasonable ROW management can decrease the capacity, the interaction between mixed traffic flow (MTF) and transportation infrastructure management should be carefully considered. In several studies, the MTF capacity has been investigated using methods such as analytical modeling [21,33] and simulation [34,35] as well as empirical approaches [15,36]. These studies have formed a consensus that as the MPR of AVs and CAVs increases, the MTF capacity significantly increases.…”

“…Most existing research assumed that there are two types of MTF: HDVs with AVs and HDVs with CAVs. It also did not sufficiently consider the complexity of heterogeneous traffic flow [24,30,32,36,37]. In fact, AVs and CAVs exhibit different characteristics that should be considered separately, because a CAV will generate much lower headway than that generated by an AV when forming a platoon.…”

An evaluation of lane management strategy for CAV priority in mixed traffic

“…For example, Talebpour et al evaluated three strategies and found that the throughput can be significantly improved at penetration rates of more than 50% for a two-lane highway and 30% for a four-lane highway [25]. However, the deployment of dedicated lanes can also cause a waste of road resources and worsen traffic conditions when the CAV penetration rate is low [26,27]. Hence, it may be best for dedicated lanes to be gradually deployed with an increase in CAV market penetration [28,29].…”