scholarly journals Research on Urban Traffic Active Control in Cooperative Vehicle Infrastructure

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Li-li Zhang ◽  
Li Wang ◽  
Qi Zhao ◽  
Fang Wang ◽  
Yadongyang Zhu ◽  
...  
Keyword(s):  
Traffic Control ◽  
Optimization Method ◽  
Control Model ◽  
Urban Traffic ◽  
Advanced Technology ◽  
Traffic Demand ◽  
Traffic Efficiency ◽  
Dynamic Phase ◽  
Phase Sequence ◽  
Intersection Control

Urban intersection control mainly undertakes two tasks: traffic safety and traffic efficiency. Traditional intersection control models and methods have been insufficient in improving traffic efficiency, which is composed of the increase in traffic demand and the complexity of demand at present. In this paper, we propose a novel model and method called ATCM, which is based on the advanced technology of cooperative vehicle infrastructure. In this paper, a novel active traffic control model (ATCM) is proposed, which is based on the advanced technology of cooperative vehicle infrastructure. ATCM increases the intersection control model variables from the traditional two dimensions to five dimensions. It reshapes intersection control from the perspective of road designers and managers, so it can achieve more flexible and efficient traffic control. To this end, a multivariable active traffic control model is constructed, which includes road speed, lane control, sequence, phase, and green light time; a D-double layer optimization method is designed for this model. The first part of this optimization method combines speed control and dynamic phase sequence control. The second part is realized by the combination of lane control and dynamic phase sequence control. By conducting comprehensive experiments, the results demonstrate that the proposed approach is more flexible and efficient than traditional methods.

Traffic Microsimulation for Flexible Utilization of Urban Roadways

2019 ◽  
Vol 2673 (10) ◽  
pp. 92-104 ◽  
Author(s):  
Aleksandar Stevanovic ◽  
Nikola Mitrovic
Keyword(s):  
Traffic Control ◽  
Simulation Models ◽  
Current Method ◽  
Fixed Time ◽  
Urban Traffic ◽  
Future Research ◽  
Major Barrier ◽  
Urban Networks ◽  
Traffic Efficiency ◽  
Traffic Systems

The current method of organizing traffic flows in urban networks uses directional right-of-way links to move traffic between urban intersections. Conflict resolution between vehicles is almost exclusively exercised at the intersections, which turns them into bottlenecks of our urban traffic systems. Even an attempt to model a different organization of traffic hits a major barrier, because the traditional simulation models do not offer enough flexibility to model bidirectional traffic on individual links in the network. This paper presents flexible arterial utilization simulation modeling (FAUSIM), a novel microsimulation platform designed to address this deficiency of traditional tools. The outputs from this tool are validated, successfully, in comparison with a commonly utilized Vissim model. The paper then illustrates the ability of FAUSIM to model conventional and unconventional traffic control scenarios. A combined alternate-direction lane assignment and reservation-based intersection control (CADLARIC) scenario is where directional driving paths are altered between neighboring lanes to align vehicles for decreased conflict for left and right turns at intersections where a reservation-based algorithm is utilized to process conflicts. This is compared with a conventional fixed-time (FT) control. The results of the experiments, executed on a small three-intersection corridor, show that CADLARIC significantly outperforms conventional driving with the FT control in relation to traffic efficiency (delays and stops). While the FT control generates fewer (potential) conflicting events, the CADLARIC confidently handles conflicting situations inside and outside the intersections. Future research should further validate the FAUSIM platform and investigate several other unconventional traffic scenarios with connected and automated vehicles.

Optimizing Traffic Signal Timing through Network Decomposition

2005 ◽  
Vol 1925 (1) ◽  
pp. 167-175 ◽  
Author(s):  
Edward Lieberman ◽  
Jinil Chang
Keyword(s):  
Control Systems ◽  
Real Time ◽  
Traffic Control ◽  
Operating Conditions ◽  
Urban Traffic ◽  
Arterial System ◽  
Signal Timing ◽  
Network Decomposition ◽  
Traffic Demand ◽  
Grid Network

A signal control system named Real-Time/Internal Metering Policy to Optimize Signal Timing (RT/IMPOST) has been under development for several years. It is designed to compute signal timing plans for the entire range of operating conditions from under- to oversaturation for control systems ranging from first generation (GEN 1) to highly responsive advanced traffic management systems. The different flow regimes of urban traffic control are reviewed. Then the focus is on the treatment to develop cycle-based signal timing plans for inclusion in the data libraries referenced by GEN 1 real-time traffic control systems for the undersaturated-flow regime. This approach decomposes a grid network into its constituent arterial subsystems in a way that is responsive to user-specified priorities. The user may define and rank the arterial systems subsumed within a grid network so as to satisfy strategic objectives responsive to traffic demand patterns and local needs. The procedure computes optimal signal timing plans for all these arterial subsystems in a priority-ranked sequence and integrates these arterial-based timing plans to form a networkwide signal timing plan. Field and simulation test results are presented. The field tests confirm that the IMPOST timing plans improved the operational performance of traffic along an arterial system in New York State relative to a fine-tuned existing control. The simulation studies compared the performance of traffic responding to IMPOST signal timing plans with that responding to Synchro 6.0 signal timing plans. The benefits of network decomposition and of arterial priority ranking are also documented.

scholarly journals Deep Reinforcement Learning Model to Mitigate Congestion in Real-Time Traffic Light Networks

2021 ◽  
Vol 6 (10) ◽  
pp. 138
Author(s):  
Fábio de Souza Pereira Borges ◽  
Adelayda Pallavicini Fonseca ◽  
Reinaldo Crispiniano Garcia
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Traffic Control ◽  
High Volume ◽  
Urban Traffic ◽  
Traffic Data ◽  
Traffic Light ◽  
Urban Network ◽  
Traffic Demand ◽  
Traffic Lights

Urban traffic congestion has a significant detrimental impact on the environment, public health and the economy, with at a high cost to society worldwide. Moreover, it is not possible to continually modify urban road infrastructure in order to mitigate increasing traffic demand. Therefore, it is important to develop traffic control models that can handle high-volume traffic data and synchronize traffic lights in an urban network in real time, without interfering with other initiatives. Within this context, this study proposes a model, based on deep reinforcement learning, for synchronizing the traffic signals of an urban traffic network composed of two intersections. The calibration of this model, including training of its neural network, was performed using real traffic data collected at the approach to each intersection. The results achieved through simulations were very promising, yielding significant improvements in indicators measured in relation to the pre-existing conditions in the network. The model was able to deal with a broad spectrum of traffic flows and, in peak demand periods, reduced delays and queue lengths by more than 28% and 42%, respectively.

scholarly journals Pilot Implementation of Public Transport Priority in the City of Zagreb

2015 ◽  
Vol 27 (3) ◽  
pp. 257-265 ◽  
Author(s):  
Miroslav Vujić ◽  
Sadko Mandzuka ◽  
Martin Greguric
Keyword(s):  
Public Transport ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Urban Traffic ◽  
Control Measures ◽  
Traffic Demand ◽  
Public Transport System ◽  
Adaptive Traffic Control ◽  
The City

The problem with traffic congestion is particularly expressed in urban areas where possibilities for physical increment of capacity are limited or impossible. Significant in the approach to solving this problem is the usage of Public Transport (PT) and the implementation of various advanced control measures that can improve the quality of overall public transport system. The main objective of this research is to explore the possibilities of implementation of adaptive traffic control on signalized intersections giving priority to public transport vehicles through urban traffic network in the city of Zagreb. The possibilities of implementing public transport priority (PTP) technique in the city of Zagreb are analyzed because of specific traffic situations on defined corridors (location of stops, distance between intersections, etc.). With proper usage of PTP techniques (e.g. adequate detector positions, good estimation of PT vehicle arrival time at intersection) the total tram travel time can be significantly reduced. The Level of Service at intersection may be approximately retained because cross-street traffic demand was not ignored. According to technological level of traffic control system in the city of Zagreb, global implementation of PTP is not possible. So, for each intersection the PTP algorithm was developed separately, but mutual traffic influence of all intersections on the corridor was considered. The cooperative concept application within urban traffic control is considered as well.

scholarly journals Research on Key Technology of Signal Control Subarea Partition Based on Correlation Degree Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Huihui Lan ◽  
Xianyu Wu
Keyword(s):  
Traffic Control ◽  
Coordinated Control ◽  
Optimization Method ◽  
Analysis Method ◽  
Control Effect ◽  
Average Delay ◽  
Traffic Efficiency ◽  
Correlation Degree ◽  
Correlation Analysis Method ◽  
Division Model

In order to accurately divide the traffic control subarea and improve the regional coordination control effect, this paper studies the key technologies of traffic control subarea division from the influence of the discrete characteristics of the fleet on the coordinated control. Correlation analysis method and regression analysis method are used to construct the correlation model of adjacent intersections. The principle and process of transportation subarea division are designed by using analytic hierarchy process, and a new traffic subarea division model is proposed. Taking Gulou Street in Miyun District of Beijing as an example, combined with the green wave coordination optimization method, the new model was applied and simulated in SimTraffic. The simulation results show that the average delay of the intersection is reduced by 21.4%, the total number of stops is reduced by 9.62%, and the travel time is shortened by 8.75%. The new intersection degree model and the coordinated control scheme obtained by the traffic subarea division model make the highest traffic efficiency. That is, to verify the scientific research method of this paper, the research results are reliable and the practical application value is high.

A Dynamic Traffic Coordination Control Model of Congestion Based on Synergetics

2011 ◽  
Vol 480-481 ◽  
pp. 1039-1042
Author(s):  
Peng Gao ◽  
Zhao Sheng Yang
Keyword(s):  
Traffic Control ◽  
Traffic Congestion ◽  
Control Model ◽  
Urban Traffic ◽  
Guidance System ◽  
Coordination Control ◽  
Dynamic Traffic ◽  
Traffic Control System ◽  
Urban Traffic Control ◽  
Simulation Scheme

The cooperation of urban traffic control system and urban traffic flow guidance system may perform an important role in alleviating traffic congestion. To achieve this objective, a dynamic traffic coordination control model of traffic congestion based on synergetics is proposed in this paper. After that approach, a simulation scheme based on VISSIM 4.2 is carried to evaluate the reliability of the model. The results proved that the whole system could benefit a lot.

scholarly journals Simulation-Based Evaluation of a New Integrated Intersection Control Scheme for Connected Automated Vehicles and Pedestrians

2020 ◽  
Vol 2674 (11) ◽  
pp. 779-793
Author(s):  
Tanja Niels ◽  
Nikola Mitrovic ◽  
Nemanja Dobrota ◽  
Klaus Bogenberger ◽  
Aleksandar Stevanovic ◽  
...  
Keyword(s):  
Traffic Control ◽  
Control Strategies ◽  
Waiting Times ◽  
Urban Environments ◽  
Minor Role ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Lane Changing ◽  
Traffic Demand ◽  
Intersection Control

In a fully connected traffic environment with automated vehicles, new traffic control strategies could replace traditional traffic signals at intersections. In recent years, several studies about reservation-based intersection control strategies have been published, and a significant increase in capacity was shown. In the strategies presented so far, other road users usually play a minor role or are not considered at all. However, many use cases of automated driving occur in urban environments, where pedestrians and bicyclists play a major role. In this paper, a novel strategy for integrating pedestrians into automated intersection management is introduced and compared with a fully actuated traffic (AT) signal control. The presented control consists of a first-come, first-served strategy for vehicles in combination with an on-demand traffic signal for pedestrians. The proposed intersection control is explained, implemented, and tested on a four-leg intersection with several lanes coming from each direction. It dynamically assigns vehicles to lanes, and vehicles follow a protocol that enables cooperative lane-changing on the approach to the intersection. Demand-responsive pedestrian phases are included in such a way that predefined maximum pedestrian waiting times are not exceeded. A set of demand scenarios is simulated using a microsimulation platform. The evaluation shows that the presented control performs significantly better than the AT control when considering low, medium, and high traffic demand. Pedestrian waiting times are slightly improved and at the same time vehicle delays are substantially decreased. However, the control needs to be improved for scenarios with a very high vehicle demand.

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