scholarly journals A Multiagent Approach to Autonomous Intersection Management

2008 ◽  
Vol 31 ◽  
pp. 591-656 ◽  
Author(s):  
K. Dresner ◽  
P. Stone

Artificial intelligence research is ushering in a new era of sophisticated, mass-market transportation technology. While computers can already fly a passenger jet better than a trained human pilot, people are still faced with the dangerous yet tedious task of driving automobiles. Intelligent Transportation Systems (ITS) is the field that focuses on integrating information technology with vehicles and transportation infrastructure to make transportation safer, cheaper, and more efficient. Recent advances in ITS point to a future in which vehicles themselves handle the vast majority of the driving task. Once autonomous vehicles become popular, autonomous interactions amongst multiple vehicles will be possible. Current methods of vehicle coordination, which are all designed to work with human drivers, will be outdated. The bottleneck for roadway efficiency will no longer be the drivers, but rather the mechanism by which those drivers' actions are coordinated. While open-road driving is a well-studied and more-or-less-solved problem, urban traffic scenarios, especially intersections, are much more challenging. We believe current methods for controlling traffic, specifically at intersections, will not be able to take advantage of the increased sensitivity and precision of autonomous vehicles as compared to human drivers. In this article, we suggest an alternative mechanism for coordinating the movement of autonomous vehicles through intersections. Drivers and intersections in this mechanism are treated as autonomous agents in a multiagent system. In this multiagent system, intersections use a new reservation-based approach built around a detailed communication protocol, which we also present. We demonstrate in simulation that our new mechanism has the potential to significantly outperform current intersection control technology -- traffic lights and stop signs. Because our mechanism can emulate a traffic light or stop sign, it subsumes the most popular current methods of intersection control. This article also presents two extensions to the mechanism. The first extension allows the system to control human-driven vehicles in addition to autonomous vehicles. The second gives priority to emergency vehicles without significant cost to civilian vehicles. The mechanism, including both extensions, is implemented and tested in simulation, and we present experimental results that strongly attest to the efficacy of this approach.

Author(s):  
Muhammad Rusyadi Ramli ◽  
Riesa Krisna Astuti Sakir ◽  
Dong-Seong Kim

This paper presents fog-based intelligent transportation systems (ITS) architecture for traffic light optimization. Specifically, each intersection consists of traffic lights equipped with a fog node. The roadside unit (RSU) node is deployed to monitor the traffic condition and transmit it to the fog node. The traffic light center (TLC) is used to collect the traffic condition from the fog nodes of all intersections. In this work, two traffic light optimization problems are addressed where each problem will be processed either on fog node or TLC according to their requirements. First, the high latency for the vehicle to decide the dilemma zone is addressed. In the dilemma zone, the vehicle may hesitate whether to accelerate or decelerate that can lead to traffic accidents if the decision is not taken quickly. This first problem is processed on the fog node since it requires a real-time process to accomplish. Second, the proposed architecture aims each intersection aware of its adjacent traffic condition. Thus, the TLC is used to estimate the total incoming number of vehicles based on the gathered information from all fog nodes of each intersection. The results show that the proposed fog-based ITS architecture has better performance in terms of network latency compared to the existing solution in which relies only on TLC.


Author(s):  
Navin Kumar ◽  
Luis Nero Alves ◽  
Rui L. Aguiar

There is great concern over growing road accidents and associated fatalities. In order to reduce accidents, improve congestion and offer smooth flow of traffic, several measures, such as providing intelligence to transport, providing communication infrastructure along the road, and vehicular communication, are being undertaken. Traffic safety information broadcast from traffic lights using Visible Light Communication (VLC) is a new cost effective technology which assists drivers in taking necessary safety measures. This chapter presents the VLC broadcast system considering LED-based traffic lights. It discusses the integration of traffic light Roadside Units (RSUs) with upcoming Intelligent Transportation Systems (ITS) architecture. Some of the offered services using this technology in vehicular environment together with future directions and challenges are discussed. A prototype demonstrator of the designed VLC systems is also presented.


Information ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 32 ◽  
Author(s):  
Vanessa Martins ◽  
João Rufino ◽  
Luis Silva ◽  
João Almeida ◽  
Bruno Miguel Fernandes Silva ◽  
...  

Traffic control management at intersections, a challenging and complex field of study, aims to strike a balance between safety and efficient traffic control. Nowadays, traffic control at intersections is typically done by traffic light systems which are not optimal and exhibit several drawbacks, such as poor efficiency and real-time adaptability. With the advent of Intelligent Transportation Systems (ITS), vehicles are being equipped with state-of-the-art technology, enabling cooperative decision-making which will certainly overwhelm the available traffic control systems. This solution strongly penalizes users without such capabilities, namely pedestrians, cyclists, and other legacy vehicles. Therefore, in this work, a prototype based on an alternative technology to the standard vehicular communications, Bluetooth Low Energy (BLE), is presented. The proposed framework aims to integrate legacy and modern vehicular communication systems into a cohesive management system. In this framework, the movements of users at intersections are managed by a centralized controller which, through the use of networked retransmitters deployed at intersections, broadcasts alerts and virtual light signalization orders. Users receive the aforementioned information on their own smart devices, discarding the need for dedicated light signalization infrastructures. Field tests, carried out with a real-world implementation, validate the correct operation of the proposed framework.


Author(s):  
Navin Kumar ◽  
Luis Nero Alves ◽  
Rui L. Aguiar

There is great concern over growing road accidents and associated fatalities. In order to reduce accidents, improve congestion and offer smooth flow of traffic, several measures, such as providing intelligence to transport, providing communication infrastructure along the road, and vehicular communication, are being undertaken. Traffic safety information broadcast from traffic lights using Visible Light Communication (VLC) is a new cost effective technology which assists drivers in taking necessary safety measures. This chapter presents the VLC broadcast system considering LED-based traffic lights. It discusses the integration of traffic light Roadside Units (RSUs) with upcoming Intelligent Transportation Systems (ITS) architecture. Some of the offered services using this technology in vehicular environment together with future directions and challenges are discussed. A prototype demonstrator of the designed VLC systems is also presented.


2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Cristina Olaverri-Monreal ◽  
Javier Errea-Moreno ◽  
Alberto Díaz-Álvarez

Cooperative Intelligent Transportation Systems (C-ITS) make the exchange of information possible through cooperative systems that broadcast traffic data to enhance road safety. Traffic light assistance (TLA) systems in particular utilize real-time traffic light timing data by accessing the information directly from the traffic management center. To test the reliability of a TLA system based on networked intervehicular interaction with infrastructure, we present in this paper an approach to perform theoretical studies in a lab-controlled scenario. The proposed system retrieves the traffic light timing program within a range in order to calculate the optimal speed while approaching an intersection and shows a recommended velocity based on the vehicle’s current acceleration and speed, phase state of the traffic light, and remaining phase duration. Results show an increase in driving efficiency in the form of improvement of traffic flow, reduced gas emissions, and waiting time at traffic lights after the drivers adjusted their velocity to the speed calculated by the system.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1523
Author(s):  
Nikita Smirnov ◽  
Yuzhou Liu ◽  
Aso Validi ◽  
Walter Morales-Alvarez ◽  
Cristina Olaverri-Monreal

Autonomous vehicles are expected to display human-like behavior, at least to the extent that their decisions can be intuitively understood by other road users. If this is not the case, the coexistence of manual and autonomous vehicles in a mixed environment might affect road user interactions negatively and might jeopardize road safety. To this end, it is highly important to design algorithms that are capable of analyzing human decision-making processes and of reproducing them. In this context, lane-change maneuvers have been studied extensively. However, not all potential scenarios have been considered, since most works have focused on highway rather than urban scenarios. We contribute to the field of research by investigating a particular urban traffic scenario in which an autonomous vehicle needs to determine the level of cooperation of the vehicles in the adjacent lane in order to proceed with a lane change. To this end, we present a game theory-based decision-making model for lane changing in congested urban intersections. The model takes as input driving-related parameters related to vehicles in the intersection before they come to a complete stop. We validated the model by relying on the Co-AutoSim simulator. We compared the prediction model outcomes with actual participant decisions, i.e., whether they allowed the autonomous vehicle to drive in front of them. The results are promising, with the prediction accuracy being 100% in all of the cases in which the participants allowed the lane change and 83.3% in the other cases. The false predictions were due to delays in resuming driving after the traffic light turned green.


Author(s):  
S. Hosseinyalmdary ◽  
A. Yilmaz

Traffic lights detection and their state recognition is a crucial task that autonomous vehicles must reliably fulfill. Despite scientific endeavors, it still is an open problem due to the variations of traffic lights and their perception in image form. Unlike previous studies, this paper investigates the use of inaccurate and publicly available GIS databases such as OpenStreetMap. In addition, we are the first to exploit conic section geometry to improve the shape cue of the traffic lights in images. Conic section also enables us to estimate the pose of the traffic lights with respect to the camera. Our approach can detect multiple traffic lights in the scene, it also is able to detect the traffic lights in the absence of prior knowledge, and detect the traffics lights as far as 70 meters. The proposed approach has been evaluated for different scenarios and the results show that the use of stereo cameras significantly improves the accuracy of the traffic lights detection and pose estimation.


2020 ◽  
Vol 10 (18) ◽  
pp. 6306 ◽  
Author(s):  
Luke Butler ◽  
Tan Yigitcanlar ◽  
Alexander Paz

Transportation disadvantage is about the difficulty accessing mobility services required to complete activities associated with employment, shopping, business, essential needs, and recreation. Technological innovations in the field of smart mobility have been identified as a potential solution to help individuals overcome issues associated with transportation disadvantage. This paper aims to provide a consolidated understanding on how smart mobility innovations can contribute to alleviate transportation disadvantage. A systematic literature review is completed, and a conceptual framework is developed to provide the required information to address transportation disadvantage. The results are categorized under the physical, economic, spatial, temporal, psychological, information, and institutional dimensions of transportation disadvantage. The study findings reveal that: (a) Primary smart mobility innovations identified in the literature are demand responsive transportation, shared transportation, intelligent transportation systems, electric mobility, autonomous vehicles, and Mobility-as-a-Services. (b) Smart mobility innovations could benefit urban areas by improving accessibility, efficiency, coverage, flexibility, safety, and the overall integration of the transportation system. (c) Smart mobility innovations have the potential to contribute to the alleviation of transportation disadvantage. (d) Mobility-as-a-Service has high potential to alleviate transportation disadvantage primarily due to its ability to integrate a wide-range of services.


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