Optimization of traffic flow at freeway sags by controlling the acceleration of vehicles equipped with in-car systems

Abstract

Sags are bottlenecks in freeway networks. According to previous research, the main cause is that most drivers do not accelerate enough at sags. Consequently, they keep longer headways than expected given their speed, which leads to congestion in high demand conditions. Nowadays, there is growing interest in the development of traffic control measures for sags based on the use of in-car systems. This paper aims to determine the optimal acceleration behavior of vehicles equipped with in-car systems at sags and the related effects on traffic flow, thereby laying the theoretical foundation for developing effective traffic management applications. We formulate an optimal control problem in which a centralized controller regulates the acceleration of some vehicles of a traffic stream moving along a single-lane freeway stretch with a sag. The control objective is to minimize total travel time. The problem is solved for scenarios with different numbers of controlled vehicles and positions in the stream, assuming low penetration rates. The results indicate that the optimal behavior involves performing a deceleration-accelerationdeceleration-acceleration (DADA) maneuver in the sag area. This maneuver induces the first vehicles located behind the controlled vehicle to accelerate fast along the vertical curve. As a result, traffic speed and flow at the end of the sag (bottleneck) increase for a time. The maneuver also triggers a stop-and-go wave that temporarily limits the inflow into the sag, slowing down the formation of congestion at the bottleneck. Moreover, in some cases controlled vehicles perform one or more deceleration-acceleration maneuvers upstream of the sag. This additional strategy is used to manage congestion so that inflow is regulated more effectively. Although we cannot guarantee global optimality, our findings reveal a potentially highly effective and innovative way to reduce congestion at sags, which could possibly be implemented using cooperative adaptive cruise control systems.

Using advanced adaptive cruise control systems to reduce congestion at sags: An evaluation based on microscopic traffic simulation

“…Therefore, the presence of these vehicle increases the sag capacity (both in free flow and congestion), even if the system's desired time gap is similar to that of human drivers. These findings are in line with those of previous studies (Ozaki, 2003;Goñi-Ros et al, 2016b).…”

“…This article aims to evaluate the effectiveness of a basic ACC system and two advanced ACC systems (a system with adaptive diving strategy and a cooperative system) in reducing congestion at freeway sags. Note that, in the case of sags, basic ACC systems are expected to increase the capacity of the bottleneck and, thus, to reduce congestion (Ozaki, 2003;Goñi-Ros et al, 2016b). The main reason is that the acceleration behavior of vehicles equipped with these systems is not affected by the freeway slope, unlike that of human-driven vehicles.…”

The impact of driving homogeneity due to automation and cooperation of vehicles on uphill freeway sections

“…When the demand is high they don't compensate for the speed loss and most importantly the perturbation of the platoon leader creates a flow disturbance that it is propagated upstream, leading in cases to a traffic jam. Optimization of traffic flow at freeway uphill sections by controlling the vehicle acceleration recently attracts a lot of interest [8,9]. Furthermore, in microsimulation studies regarding the impact assessment of connected and automated vehicles, the models used for simulation do not account for the reproduction of realistic vehicle dynamics [22,23,29].…”

“…Moreover, we propose a simple yet efficient control logic to showcase the impact of vehicle cooperation with the infrastructure (V2I). The control logic is motivated by the results presented by Goñi-Ros [8], identifying an acceleration maneuver uphill as the best strategy to minimize total delay and facilitate flow. Finally, the sensitivity of the results was tested using two different response times for AVs and CAVs, one equal to the reaction time of the human drivers and a second, reduced by 10% as it is empirically found in our previous work [18].…”

Lane‐changing and freeway capacity: A Bayesian inference stochastic model

“…On the other hand, vehicles’ sluggish acceleration has also been found to be related to the capacity drop (Chen, Ahn, Laval, & Zheng, ; Goñi‐Ros et al., ; Knoop, Hoogendoorn, & Adams, ; Laval & Daganzo, ; Leclercq, Laval, & Chiabaut, ; Yuan, Laval, Knoop, Jiang, & Hoogendoorn, ). Vehicles changing lanes near bottlenecks are observed to create larger gaps in the arriving lane due to their limited acceleration when moving from a slow to a faster lane.…”