scholarly journals Rhythmic Control of Automated Traffic—Part II: Grid Network Rhythm and Online Routing

2021 ◽  
Author(s):  
Xi Lin ◽  
Meng Li ◽  
Zuo-Jun Max Shen ◽  
Yafeng Yin ◽  
Fang He
Keyword(s):  
Real Time ◽  
Operations Management ◽  
Traffic Control ◽  
Control Method ◽  
Superior Performance ◽  
Mixed Integer ◽  
Computational Time ◽  
Linear Programming Relaxation ◽  
Online Routing ◽  
Time Space

Connected and automated vehicle (CAV) technology is providing urban transportation managers tremendous opportunities for better operation of urban mobility systems. However, there are significant challenges in real-time implementation as the computational time of the corresponding operations optimization model increases exponentially with increasing vehicle numbers. Following the companion paper (Chen et al. 2021), which proposes a novel automated traffic control scheme for isolated intersections, this study proposes a network-level, real-time traffic control framework for CAVs on grid networks. The proposed framework integrates a rhythmic control method with an online routing algorithm to realize collision-free control of all CAVs on a network and achieve superior performance in average vehicle delay, network traffic throughput, and computational scalability. Specifically, we construct a preset network rhythm that all CAVs can follow to move on the network and avoid collisions at all intersections. Based on the network rhythm, we then formulate online routing for the CAVs as a mixed integer linear program, which optimizes the entry times of CAVs at all entrances of the network and their time–space routings in real time. We provide a sufficient condition that the linear programming relaxation of the online routing model yields an optimal integer solution. Extensive numerical tests are conducted to show the performance of the proposed operations management framework under various scenarios. It is illustrated that the framework is capable of achieving negligible delays and increased network throughput. Furthermore, the computational time results are also promising. The CPU time for solving a collision-free control optimization problem with 2,000 vehicles is only 0.3 second on an ordinary personal computer.

scholarly journals Sustainable Traffic Management in an Urban Area: An Integrated Framework for Real-Time Traffic Control and Route Guidance Design

2020 ◽  
Vol 12 (2) ◽  
pp. 726 ◽  
Author(s):  
Stefano de Luca ◽  
Roberta Di Pace ◽  
Silvio Memoli ◽  
Luigi Pariota
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Traffic Congestion ◽  
Network Performance ◽  
Impact Analysis ◽  
Control Method ◽  
Choice Model ◽  
Route Guidance ◽  
Modeling Framework ◽  
Integrated Framework

This paper focuses on the presentation of an integrated framework based on two advanced strategies, aimed at mitigating the effect of traffic congestion in terms of performance and environmental impact. In particular, the paper investigates the “operational benefits” that can be derived from the combination of traffic control (TC) and route guidance (RG) strategies. The framework is based on two modules and integrates a within-day traffic control method and a day-to-day behavioral route choice model. The former module consists of an enhanced traffic control model that can be applied to design traffic signal decision variables, suitable for real-time optimization. The latter designs the information consistently with predictive user reactions to the information itself. The proposed framework is implemented to a highly congested sub-network in the city center of Naples (Italy) and different scenarios are tested and compared. The “do nothing” scenario (current; DN) and the “modeled compliance” (MC) scenario, in which travelers’ reaction to the information (i.e., compliance) is explicitly represented. In order to evaluate the effectiveness of the proposed strategy and the modeling framework, the following analyses are carried out: (i) Network performance analysis; (ii) system convergence and stability analysis, as well as the compliance evolution over time; (iii) and emissions and fuel consumption impact analysis.

Data Infrastructure for Connected Vehicle Applications

2020 ◽  
Vol 2674 (5) ◽  
pp. 85-96
Author(s):  
Xingmin Wang ◽  
Shengyin Shen ◽  
Debra Bezzina ◽  
James R. Sayer ◽  
Henry X. Liu ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Transportation Systems ◽  
Connected Vehicle ◽  
Performance Measurements ◽  
Trajectory Data ◽  
Test Environment ◽  
Data Infrastructure ◽  
Time Space ◽  
Wide Range

Ann Arbor Connected Vehicle Test Environment (AACVTE) is the world’s largest operational, real-world deployment of connected vehicles (CVs) and connected infrastructure, with over 2,500 vehicles and 74 infrastructure sites, including intersections, midblocks, and highway ramps. The AACVTE generates a massive amount of data on a scale not seen in the traditional transportation systems, which provides a unique opportunity for developing a wide range of connected vehicle (CV) applications. This paper introduces a data infrastructure that processes the CV data and provides interfaces to support real-time or near real-time CV applications. There are three major components of the data infrastructure: data receiving, data pre-processing, and visualization including the performance measurements generation. The data processing algorithms include signal phasing and timing (SPaT) data compression, lane phase mapping identification, trajectory data map matching, and global positioning system (GPS) coordinates conversion. Simple performance measures are derived from the processed data, including the time–space diagram, vehicle delay, and observed queue length. Finally, a web-based interface is designed to visualize the data. A list of potential CV applications including traffic state estimation, traffic control, and safety, which can be built on this connected data infrastructure is discussed.

scholarly journals Novo método de cálculo das frações de verde para controle semafórico em tempo real

TRANSPORTES ◽  
2011 ◽  
Vol 19 (1) ◽  
pp. 87
Author(s):  
Werner Kraus Junior ◽  
José Dolores Vergara Dietrich ◽  
Felipe Augusto De Souza ◽  
Eduardo Camponogara
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Original Method ◽  
New Method ◽  
Superior Performance ◽  
Control Parameters ◽  
Real Time Traffic ◽  
Simulation Results

<p><strong>Resumo:</strong> Apresenta-se um método de cálculo de frações de verde a ser usado em sistemas de controle de tráfego em tempo real por amostragem cíclica. A base do método origina-se da estratégia TUC, brevemente revisada neste trabalho. O objetivo é substituir um procedimento empírico de ajuste de parâmetros auxiliares do controle por uma metodologia que seja facilmente entendida e utilizável na prática. Resultados de simulação indicam o desempenho superior do método quando comparado com os ajustes empíricos do método original.</p><p><em>Palavras-chave:</em> controle semafório em tempo real; amostragem cíclica; método TUC.</p><p><strong>Abstract:</strong> A new method for the computation of splits for real-time traffic control with cyclic sampling is presented. The method is based on the TUC strategy, which is briefly reviewed in this paper. The goal is to replace an empirical tuning procedure of auxiliary control parameters by a method that is easy to understand and implement. Simulation results indicate the superior performance of the method when compared to the empirical adjustments of the original method.</p><p><em>Keywords:</em> real-time traffic control; cyclic sampling; TUC method.</p>

scholarly journals Performance Evaluation of Heuristics and Meta-Heuristics Traffic Control Strategies Using the UTNSim Traffic Simulator

2021 ◽  
Vol 29 (3) ◽  
Author(s):  
Ng Kok Mun ◽  
Mamun Ibne Reaz
Keyword(s):  
Traffic Control ◽  
Control Strategies ◽  
Research Question ◽  
Computation Time ◽  
Urban Traffic ◽  
Superior Performance ◽  
Computational Time ◽  
Performance Indices ◽  
Different Types ◽  
Real Time Application

In the past few decades, intelligent traffic controllers have been developed to responsively cope with the increasing traffic demands and congestions in urban traffic networks. Various studies to compare and evaluate the performance of traffic controllers have been conducted to investigate its effect on traffic performances such as its ability to reduce delay time, stops, throughputs and queues within a traffic network. In this paper, the authors aim to present another comparative study on heuristics versus meta-heuristics traffic control methods. To our knowledge, such comparison has not been conducted and could provide insights into a purely heuristic controller compared to meta-heuristics. The study aims to answer the research question “Can heuristics traffic control strategies outperformed meta-heuristics in terms of performance and computational costs?” For this purpose, a heuristics model-based control strategy (MCS) which was previously developed by the authors is compared to genetic algorithms (GA) and evolution strategy (ES) respectively on a nine intersections symmetric network. These control strategies were implemented via simulations on a traffic simulator called UTNSim for three different types of traffic scenarios. Performance indices such as average delays, vehicle throughputs and the computational time of these controllers were evaluated. The results revealed that the heuristic MCS outperformed GA and ES with superior performance in average delays whereas vehicle throughputs were in close agreement. The computation time of the MCS is also feasible for real-time application compared to GA and ES that has longer convergent time.

Formulation of Real-Time Control Policy for Oversaturated Arterials

2000 ◽  
Vol 1727 (1) ◽  
pp. 77-88 ◽  
Author(s):  
Edward B. Lieberman ◽  
Jinil Chang ◽  
Elena Shenk Prassas
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Storage Capacity ◽  
Control Policy ◽  
Mixed Integer ◽  
System Throughput ◽  
Real Time Control ◽  
Mixed Integer Linear Program ◽  
Real Time Traffic ◽  
Queue Lengths

The formulation of a real-time traffic control policy designed expressly for oversaturated arterials is presented, and the operating protocol is described. Its objectives are to ( a) maximize system throughput, ( b) fully use storage capacity, and ( c) provide equitable service. This control policy, known as RT/IMPOST (real-time/internal metering policy to optimize signal timing), is designed to control queue growth on every saturated approach by suitably metering traffic to maintain stable queues. Consistent with this approach, bounds on queue lengths and signal offsets are determined. A mixed-integer linear program (MILP) tableau is formulated to yield optimal values of signal offsets and queue length for each approach. A nonlinear (quadratic) programming formulation adjusts the arterial green-phase durations of each signal cycle so that the actual arterial queue lengths on each saturated approach will continually closely approximate the optimal queue lengths computed by the MILP formulation. The policy principles are as follows: ( a) the signal phase durations “meter” traffic at intersections servicing oversaturated approaches to control and stabilize queue lengths and to provide equitable service to competing traffic streams; and ( b) the signal coordination (i.e., offsets) controls the interaction between incoming platoons and standing queues in a way that fully uses the available storage capacity, keeps intersections clear of queue spillback, and maximizes throughput.

scholarly journals A Timetable Rescheduling Approach and Transition Phases for High-Speed Railway Traffic during Disruptions

2017 ◽  
Vol 2607 (1) ◽  
pp. 82-92 ◽  
Author(s):  
Peijuan Xu ◽  
Francesco Corman ◽  
Qiyuan Peng ◽  
Xiaojie Luan
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
High Speed ◽  
Job Shop ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Solution Quality ◽  
High Speed Railway ◽  
Railway Traffic ◽  
Train Speed

Research focused on the real-time rescheduling of high-speed railway traffic with a quasi-moving blocking system and transition process affected by the entrance delays and disruptions determining speed limitation. A mixed-integer linear program model related to a job shop model of operations is formulated to reduce the final delay (tardiness) of trains, where three objective functions combine different manners related to traffic control and speed management. The dynamic interaction between train speed and distance headway is considered in the model. Through experiments on a real-world high-speed line in China, the solution quality of the model is assessed by the delay distribution of trains or the smooth degree of train speed profile. The model manages to optimize traffic in the transition from a disordered condition (when disruptions appear) to a normal condition (after disruptions) for real-time operations. In conclusion, there are two and three transition phases for the cases without and with entrance delays, respectively, seen by analyzing the deviation between the rescheduled and planned timetables.

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