Intersection Management for Autonomous Vehicles Using Cooperative Adaptive Cruise Control Systems
01 Jan 2013-
TL;DR: In this article, the authors presented a new tool for optimizing the movements of autonomous vehicles through intersections, iCACC, which can control vehicle trajectories entering an intersection to avoid collisions while minimizing the intersection delay.
Abstract: One of the expected features for the automated vehicles in the near future is Cooperative Adaptive Cruise Control (CACC) systems. CACC systems are one of the main applications for the connected vehicles initiative of the USDOT for providing better connectivity, safety and efficient mobility in transportation. It is expected in the future that many (or most) of the vehicles will be fully automated; thus the movements of these vehicles can be optimized. Accordingly, this paper presents a new tool for optimizing the movements of autonomous vehicles through intersections: iCACC. The iCACC controller controls vehicle trajectories entering an intersection to avoid collisions while minimizing the intersection delay. In order to validate the proposed algorithm, four intersection control scenarios were analyzed, namely: a traffic signal, an all-way stop control (AWSC), a roundabout, and the iCACC controller, considering different traffic demand levels ranging from a volume-to-capacity ratio of 0.27 to 0.91. Two measures of effectiveness were considered: average vehicle delay and fuel consumption. The simulated results showed savings in delay and fuel consumption of the order of 90 and 45 percent, respectively compared to AWSC and traffic signal control. Delays for the roundabout and the iCACC controller were comparable. The simulation results showed that fuel consumption for the iCACC controller was, on average, 33%, 45% and 11% lower than the fuel consumption for the traffic signal control, AWSC and roundabout scenarios, respectively.
Citations
More filters
TL;DR: In this article, the authors proposed a coordination control algorithm, assuming stochastic models for the arrival times of the vehicles and provided provable guarantees on safety, no collisions occur surely, and performance, rigorous bounds on the expected delay.
Abstract: As autonomous vehicle technology advances rapidly, the design and operation of networks composed of fully autonomous vehicles have attracted immense interest. It is widely anticipated that fully autonomous vehicle networks will drastically improve performance. In this paper, we consider a widely studied problem, in which autonomous vehicles arriving at an intersection adjust their speeds to traverse the intersection as rapidly as possible, while avoiding collisions. We propose a coordination control algorithm, assuming stochastic models for the arrival times of the vehicles. The proposed algorithm extends the widely studied polling systems analysis to the case involving customers subject to second-order differential constraints. We provide provable guarantees on 1) safety, no collisions occur surely, and 2) performance, rigorous bounds on the expected delay. We also provide a stability analysis for the resulting queueing system. We demonstrate the algorithm in an extensive simulation study, providing one to two orders of magnitude improvement in delays over the traditional traffic light.
67 citations
TL;DR: The study shows that the impact of CACC is positive and not only limited to a high market penetration and by giving CACC vehicles priority access to high-occupancy vehicle (HOV) lanes, the highway capacity could be significantly improved with a CACC penetration as low as 20%.
Abstract: Cooperative adaptive cruise control (CACC) vehicles are intelligent vehicles that use vehicular ad hoc networks (VANETs) to share traffic information in real time. Previous studies have shown that CACC could have an impact on increasing highway capacities at high market penetration. Since reaching a high CACC market penetration level is not occurring in the near future, this study presents a progressive deployment approach that demonstrates to have a great potential of reducing traffic congestions at low CACC penetration levels. Using a previously developed microscopic traffic simulation model of a freeway with an on-ramp -- created to induce perturbations and trigger stop-and-go traffic, the CACC system's effect on the traffic performance is studied. The results show significance and indicate the potential of CACC systems to improve traffic characteristics which can be used to reduce traffic congestion. The study shows that the impact of CACC is positive and not only limited to a high market penetration. By giving CACC vehicles priority access to high-occupancy vehicle (HOV) lanes, the highway capacity could be significantly improved with a CACC penetration as low as 20%.
46 citations
01 Oct 2013
TL;DR: A paradigm shift based upon self-organizing and cooperative control framework is proposed, which has proved its safety, user comfort, and efficiency functional requirements, and several recommendations for further research are presented.
Abstract: Development of in-vehicle computer and sensing technology, along with short-range vehicle-to-vehicle communication has provided technological potential for large-scale deployment of autonomous vehicles. The issue of intersection control for these future driverless vehicles is one of the emerging research issues. Contrary to some of the previous research approaches, this paper is proposing a paradigm shift based upon self-organizing and cooperative control framework. Distributed vehicle intelligence has been used to calculate each vehicle's approaching velocity. The control mechanism has been developed in an agent-based environment. Self-organizing agent's trajectory adjustment bases upon a proposed priority principle. Testing of the system has proved its safety, user comfort, and efficiency functional requirements. Several recommendations for further research are presented.
38 citations
Cites background from "Intersection Management for Autonom..."
...In addition, another recent research approach focused on controlling the approach speed of driverless vehicles under the goal of minimizing total delay of users [14]....
[...]
Posted Content•
TL;DR: The proposed coordination control algorithm extends the widely studied polling systems analysis to the case involving customers subject to second-order differential constraints, providing provable guarantees on 1) safety, no collisions occur surely, and 2) performance, rigorous bounds on the expected delay.
Abstract: The rapid development of autonomous vehicles spurred a careful investigation of the potential benefits of all-autonomous transportation networks. Most studies conclude that autonomous systems can enable drastic improvements in performance. A widely studied concept is all-autonomous, collision-free intersections, where vehicles arriving in a traffic intersection with no traffic light adjust their speeds to cross safely through the intersection as quickly as possible. In this paper, we propose a coordination control algorithm for this problem, assuming stochastic models for the arrival times of the vehicles. The proposed algorithm provides provable guarantees on safety and performance. More precisely, it is shown that no collisions occur surely, and moreover a rigorous upper bound is provided for the expected wait time. The algorithm is also demonstrated in simulations. The proposed algorithms are inspired by polling systems. In fact, the problem studied in this paper leads to a new polling system where customers are subject to differential constraints, which may be interesting in its own right.
30 citations
Dissertation•
06 May 2014
TL;DR: The dissertation develops an integrated framework for the control of autonomous vehicle movements through intersections using a multi-objective optimization algorithm integrated within an existing framework that minimizes vehicle delay while ensuring vehicles do not collide.
Abstract: Vehicle stops and speed variations account for a large percentage of vehicle fuel losses especially at signalized intersections. Recently, researchers have attempted to develop tools that reduce these losses by capitalizing on traffic signal information received via vehicle connectivity with traffic signal controllers. Existing state-of-the-art approaches, however, only consider surrogate measures (e.g. number of vehicle stops, time spent accelerating and decelerating, and/or acceleration or deceleration levels) in the objective function and fail to explicitly optimize vehicle fuel consumption levels. Furthermore, the majority of these models do not capture vehicle acceleration and deceleration limitations in addition to vehicle-to-vehicle interactions as constraints within the mathematical program. The connectivity between vehicles and infrastructure, as achieved through Connected Vehicles technology, can provide a vehicle with information that was not possible before. For example, information on traffic signal changes, traffic slow-downs and even headway and speed of lead vehicles can be shared. The research proposed in this dissertation uses this information and advanced computational models to develop fuel-efficient vehicle trajectories, which can either be used as guidance for drivers or can be attached to an electronic throttle controlled cruise control system. This fuel-efficient cruise control system is known as an Eco-Cooperative Adaptive Cruise Control (ECACC) system. In addition to the ECACC presented here, the research also expands on some of the key eco-driving concepts such as fuel-optimizing acceleration models, which could be used in conjunction with conventional vehicles and even autonomous vehicles, or assistive systems that are being implemented in vehicles. The dissertation first presents the results from an on-line survey soliciting driver input on public perceptions of in-vehicle assistive devices. The results of the survey indicate that useracceptance to systems that enhance safety and efficiency is ranked high. Driver–willingness to use advanced in-vehicle technology and cellphone applications is also found to be subjective on what benefits it has to offer and safety and efficiency are found to be in the top list. The dissertation then presents the algorithmic development of an Eco-Cooperative Adaptive Cruise Control system. The modeling of the system constitutes a modified state-of-the-art pathR.K. Kamalanathsharma iii finding algorithm within a dynamic programming framework to find near-optimal and near-realtime solutions to a complex non-linear programming problem that involves minimizing vehicle fuel consumption in the vicinity of signalized intersections. The results demonstrated savings of up to 30 percent in fuel consumption within the traffic signalized intersection vicinity. The proposed system was tested in an agent-based environment developed in MATLAB using the RPA car-following model as well as the Society of Automobile Engineers (SAE) J2735 message set standards for vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication. The results showed how multi-vehicle interaction enhances usability of the system. Simulation of a calibrated real intersection showed average fuel savings of nearly 30 percent for peak volumes. The fuel reduction was high for low volumes and decreased as the traffic volumes increased. The final testing of the algorithm was done in an enhanced Traffic Experimental Simulation tool (eTEXAS) that incorporates the conventional TEXAS model with a new web-service interface as well as connected vehicle message set dictionary. This testing was able to demonstrate model corrections required to negate the effect of system latencies as well as a demonstration of using SAE message set parsing in a connected vehicle application. Finally, the dissertation develops an integrated framework for the control of autonomous vehicle movements through intersections using a multi-objective optimization algorithm. The algorithm integrated within an existing framework that minimizes vehicle delay while ensuring vehicles do not collide. A lower-level of control is introduced that minimizes vehicle fuel consumption subject to the arrival times assigned by the upper-level controller. Results show that the ecospeed control algorithm was able to reduce the overall fuel-consumption of autonomous vehicles passing through an intersection by 15 percent while maintaining the 80 percent saving in delay when compared to a traditional signalized intersection control. R.K. Kamalanathsharma
10 citations