Developing Highway Capacity Manual Capacity Adjustment Factors for Connected and Automated Traffic on Roundabouts

Abstract

Connected and automated vehicles (CAVs) are expected to transform future transportation systems. Over time, these vehicles might enhance traffic efficiency and safety, especially at urban intersections. Therefore, it is essential to make adaptations to the traffic analysis models that are currently designed for human-driven vehicles only. This paper aims to assess the impact of CAVs on the entry capacity of roundabouts and develop an approach to adjust the capacity values calculated by the Highway Capacity Manual (HCM) for planning level analysis. Both single-and double-lane roundabouts are studied under various CAV market penetration rates and conflict flow rates in this paper. A specific CAVapplication, cooperative adaptive cruise control (CACC), is evaluated in this study because it enhances the car-following behavior at the roundabout entrance and has the best potential for improving the entry capacity. The simulation results indicate that the introduction of CAVs can substantially improve the entry capacity as the market penetration rate increases for both singleand double-lane roundabouts. The capacity improvement is more significant in the single-lane roundabout than in the double-lane roundabout. The capacities under different CAV market penetration rates and conflict flow rates are calculated and compared with the capacity results estimated from base models in the HCM to acquire the adjustment factors. Finally, a table of capacity adjustment factors is provided for the future implementation of HCM models.

Simulation-Based Analysis of “What-If” Scenarios with Connected and Automated Vehicles Navigating Roundabouts

“…Thus, the ordinary adaptive cruise control systems provide minimum time gaps comparable to those of HDVs, thus decreasing the roadway capacity especially when their use is widespread [2,38]. In turn, the digital connectivity between vehicles, between vehicles and transport infrastructure, and between vehicles and other road users, provides the automated driving systems with more information about the surrounding environment, and it also enables the cooperative element to enhance the detection capabilities of vehicles and the adaptation of drivers' behaviour while driving [3,23]. Compared to the conventional cruise control or adaptive speed control, the cooperative adaptive cruise control technology that is enabled by vehicle-to-vehicle communication, may safely permit a vehicle to travel more closely to a lead vehicle and may allow more vehicles to enter a lane, so as to reduce traffic jams and increase the overall average speed [2,23].…”

“…Whether connected and automated vehicles (CAVs as they are known) can negotiate efficiently or hesitate before entering the roundabouts is still an open issue [1][2][3]. The cooperative adaptive cruise control technology (CACC) for CAVs which combines the adaptive cruise control with the cooperative decision making enabled by vehicle-to-vehicle communication should bring novel opportunities to the digital community of road users concerning the exchange and sharing of data on the vehicles' dynamic states, the driving intentions and the surrounding context [4,5].…”

“…The cooperative adaptive cruise control technology (CACC) for CAVs which combines the adaptive cruise control with the cooperative decision making enabled by vehicle-to-vehicle communication should bring novel opportunities to the digital community of road users concerning the exchange and sharing of data on the vehicles' dynamic states, the driving intentions and the surrounding context [4,5]. The cooperative driving should enhance the car-following behaviour at roundabouts, thus improving the entry capacity, especially under balanced traffic flows from all entries [3,[6][7][8]. Although the transition towards increasingly high levels of connected and automated transportation should resolve the variability in human performance, the priority rule to vehicles circulating around the central island and the predominantly curved trajectories of the roundabouts may make the decision making by vehicles instead of human drivers even more challenging than at stopcontrolled or signalised intersections [9][10][11].…”

“…In this view, the adjustment factors for freeway elements, signalised intersections and roundabouts, recently presented by the Highway Capacity Manual (HCM) [2], are the only usable reference to determine the CAV-adjusted capacity relationships in heterogenous traffic. Given the absence of level 4 and 5 CAVs using the actual road infrastructures [9], the adjustment factors for CAVs were based on all the knowledge gained during the last years and were derived from microsimulation under the assumption that all communication elements required to provide their full cooperation were working with a high degree of reliability [2,3,23].…”

Roundabouts: Traffic Simulations of Connected and Automated Vehicles—A State of the Art

“…One of the configuration aspects that most affects the traffic operation in roundabouts is the number of lanes. In [59], the impact of the introduction of CAVs on traffic operations at roundabouts is studied, focusing in particular on capacity calculation. The Authors started from the model present in HCM and developed some Capacity Adjustment Factors (CAFs) in order to account for the presence of automated vehicles at the intersection.…”