Intelligent Transportation Systems (ITS) have attracted the attention of researchers and the general public alike as a means to alleviate traffic congestion. Recently, the maturity of wireless technology has enabled a cost-efficient way to achieve ITS by detecting vehicles using Vehicle to Infrastructure (V2I) communications. Traditional ITS algorithms, in most cases, assume that every vehicle is observed, such as by a camera or a loop detector, but a V2I implementation would detect only those vehicles with wireless communications capability. We examine a family of transportation systems, which we will refer to as Partially Detected Intelligent Transportation Systems'. An algorithm that can act well under a small detection rate is highly desirable due to gradual penetration rates of the underlying wireless technologies such as Dedicated Short Range Communications (DSRC) technology. Artificial Intelligence (AI) techniques for Reinforcement Learning (RL) are suitable tools for finding such an algorithm due to utilizing varied inputs and not requiring explicit analytic understanding or modeling of the underlying system dynamics. In this paper, we report a RL algorithm for partially observable ITS based on DSRC. The performance of this system is studied under different car flows, detection rates, and topologies of the road network. Our system is able to efficiently reduce the average waiting time of vehicles at an intersection, even with a low detection rate.
Meanwhile, as Dedicated Short-Range Communications start to be installed on vehicles in the United States, traffic signal control schemes based on such technology have become a rising field, as the cost is significantly lower than a traditional ITS @cite_40 @cite_32 @cite_41 . Within these schemes, a system known as Virtual Traffic Lights (VTL) is very attractive, as it proposes an infrastructure-free DSRC-based solution, by installing traffic control devices in vehicles and having the vehicles decide the right-of-way at an intersection locally. Different aspects of VTL technology, including algorithm design, system simulation, deployment policy, and carbon emission have been studied by different research groups in the last few years @cite_40 @cite_64 @cite_15 @cite_58 @cite_1 @cite_54 @cite_34 @cite_11 @cite_29 @cite_51 @cite_72 @cite_20 . However, a VTL system requires all vehicles in the road network to be equipped with DSRC device, therefore, a transition scheme for the current transportation systems to smoothly transition to VTL system is needed.
@cite_64 @cite_41 @cite_54 @cite_29 @cite_1 @cite_32 @cite_34 @cite_40 @cite_72 @cite_15 @cite_58 @cite_51 @cite_20 @cite_11
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Traffic congestion is a daunting problem that is affecting the daily lives of billions of people across the world. Recently, a promising new traffic control scheme known as Virtual Traffic Lights (VTL) has been proposed for mitigating traffic congestion. VTL is an infrastructure free traffic control scheme that leverages the presence of Vehicle-to-Vehicle (V2V) communications. Such infrastructure free scheme has several benefits, such as alleviating traffic congestion; reducing the large cost of traffic lights and traffic control systems; reducing carbon emission, etc. This paper reports a DSRC-based prototype design effort on VTL using Dedicated Short Range Communications (DSRC) technology. The experiments performed show the feasibility of implementing VTL with DSRC technology. Preliminary results of the field tests conducted in Pittsburgh with vehicles using VTL equipment indicate that VTL is capable of coordinating traffic at intersections and reducing the commute time of people. A new technology known as Virtual Traffic Lights (VTL) was recently proposed as a self-organizing new paradigm for traffic management. This new technology uses the vehicle-to-vehicle (V2V) communications as its premise. VTL can revolutionize traffic management in urban areas as it can substantially reduce commute time of urban workers, increase productivity, and lead to a greener environment. In a VTL environment, vehicles self-organize to elect a leader which serves as a virtual traffic light to decide the right of way at that intersection, thus replacing the current physical traffic lights. Implementing VTL technology with partial penetration, however, is an outstanding issue that needs to be addressed. This paper addresses this issue by proposing a co-existence model whereby VTL equipped vehicles can co-exist with vehicles that do not have VTL. Simulation results show that the transition model proposed here could provide drivers with strong incentives to adopt the VTL technology. Considering that the transport sector is responsible for an increasingly important share of current environmental problems, we look at Intelligent Transportation Systems (ITS) as a feasible means of helping in solving this issue. In particular, we evaluate the impact in terms of Carbon Dioxide (CO2)emissions of Virtual Traffic Light (VTL), which is a recently proposed infrastructureless traffic control system solely based on Vehicle-to-Vehicle (V2V) communication. Our evaluation uses a real-city scenario in a complex simulation framework, involving microscopic traffic, wireless communication, and emission models. Compared with an approximation of the physical traffic light system deployed in the city, our results show a significant reduction on CO2 emissions when using VTLs, reaching nearly 20 under high-density traffic. The correct and prompt definition of priorities at intersections is one of the key issues for vehicular safety and efficient traffic management. Traffic lights currently control only a limited number of intersections and increasing their number is clearly infeasible due to the high costs of deployment and maintenance. A new solution will be possible in a near future, when vehicles will be equipped with wireless technologies. Their capability of communicating and coordinating to each other will create the conditions for the implementation of a virtual traffic light (VTL) architecture, where priorities are autonomously defined by the involved vehicles. With this scenario in mind, we describe a novel VTL algorithm aiming at defining the priorities of the intersections in a distributed and controlled way. Besides the algorithm description, the main related issues are thoroughly discussed. In addition, a real implementation is detailed and the validation of the algorithm is provided. The testbed, based on the IEEEź802.11p short range wireless technology, has been reproduced in a controlled laboratory environment and in a field trial with equipped vehicles.