Consensus-based local information coordination for the networked control of the autonomous intersection management

Chairit Wuthishuwong, Ansgar Traechtler
2016 Complex & Intelligent Systems  
Autonomous intersection management (AIM) will be a future method for improving traffic efficiency in the urban area. Instead of using the traffic signal control like nowadays, it uses wireless communication with autonomous vehicles to support the management of road traffic more safely and efficiently. A single AIM shows an exceptional performance in managing traffics at an intersection. However, it could not be represented a traffic in the real world, which is composed of multiple
more » ... We show that coordination of traffic information among vehicles and infrastructures is an essential part of macroscopic traffic management. Coordination of traffic information among the network of AIMs is the key to improve the overall traffic flow throughout the network not only has an optimal flow in some intersections and very heavy traffic in others. In this paper, we introduce the distributed control to a graph-based intersection network to control traffic in a macroscopic level. Vehicle to infrastructure and infrastructure to infrastructure communication are used to exchange the traffic information between a single autonomous vehicle to the network of autonomous intersections. We implement a discrete time consensus algorithm to coordinate the traffic density of an intersection with its neighborhoods and determine the control policy to maximize a traffic throughput of each intersection as well as stabilizing the overall traffic in the network. We use the Greenshields B Chairit Wuthishuwong traffic model to define the boundary condition of various traffic flows to the corresponded traffic density and velocity. Our proposed method represents the ability to maintain traffic flow rate of each intersection without having a back up traffic. As well, every intersection operates under the uncongested flow condition. The simulation results of the graph-based networked control of a multiple autonomous intersection showed that the overall traffic flow in the network achieves up to 20% higher than using traffic signal system. Keywords Autonomous intersection management · Autonomous vehicle · Vehicle to infrastructure communication · Infrastructure to infrastructure communication · Discrete time consensus algorithm · Traffic model Complex Intell. Syst. (2017) 3:17-32 controllers SCAT in [2] and SCOO in [3] proposed a different optimization method to minimize the queue length and maximize the throughput. Recently, the advance of wireless communication technology makes a huge contribution to road transportation. It breaks the limitation in transmitting data, flexibility, range, speed, and no hard wiring is required. Therefore, intelligent transportation systems uses the advantageous of wireless communication to improve the traffic safety and efficiency. The fully autonomous system of road transportation can be basically made in practice by integrating wireless communication with a current autonomous vehicle. With the fast development of autonomous driving, a work in [4] showed the first vehicle that drives itself throughout the dessert in 2005. A few years later in 2008, an autonomous vehicle in [5] showed the ability to drive in the urban environment with multiple modes e.g., parking and crossing an intersection. Many works contributed to the autonomous vehicle such as real-time motion planning in structured and unstructured environment [6, 7] , navigation and control algorithm [8-10] sensor fusion technique and localization system. In addition, an autonomous vehicle, Bertha in [11] has proved itself by running over 200 km throughout many cities in Baden Wuerttemberg, Germany without human driver. This shows a big step toward the future of intelligent transportation. Litman [12] predicts the effect of autonomous vehicle technology to the transport planning and [13] surveys of its impact to the vehicle demand and usage. Based on deployment of two core technologies above, the fully autonomous system on the road transport expects to achieve a secure traffic safety and a higher efficiency. To target to zero accident and enhance the traffic throughput, autonomous vehicle needs sufficient information for making a better decision. On-board sensors can typically provide the local information only where sensors' capacity can reach but a vehicle to be a part of managing a macroscopic traffic requires extra information of a traffic situation around it and its neighborhood. To obtain those interconnection data, vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication plays an important role in exchanging information between each other. The communication standard of IEEE 802.11p, dedicated short-range communication (DSRC) was presented in [14] . It allocates the specific communication frequency of spectrum 5.9 GHz band for using only with vehicle communication. Several research works used V2V for improving traffic safety, e.g., [15] demonstrated of exchanging the local information like position, orientation and speed among the adjacent vehicles to improve the vehicles' collision avoidance system, where a vehicle in the blind spot fails to detect using the line of sight sensor but it can be detected only using wireless communication. Another work [16] used V2V to coordinate vehicles driving through the roundabout-type intersection.
doi:10.1007/s40747-016-0032-6 fatcat:eb6y7xfxkjd3jhfea7vkyc6afi