Algorithms and models for signal coordination

2020 ◽  
pp. 207-233
Keyword(s):  
Signal Coordination

scholarly journals PENGARUH KEMACETAN DI SIMPANG CILIWUNG TERHADAP DERAJAD PELAYANAN DI SIMPANG PROGRESIF

2018 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
Supiyono, Dwi Ratnaningsih, Rudy Ariyanto
Keyword(s):  
Degree Of Saturation ◽  
Traffic Density ◽  
Density Level ◽  
Signal Coordination ◽  
The Road ◽  
Vehicle Density ◽  
Arterial Road ◽  
Intersection Area ◽  
Light Signals ◽  
The City

Abstract Highway in Malang there that needs to be analyzed is Intersections Letjend S. Parman Street – Ciliwung Street and Letjend Sutoyo Street – Letjend Selorejo. The road is an arterial road in the city of Malang with a high vehicle density level (Saputra, 2013). The Street was a high traffic flow led to queues or long saturated flow that is not supported by the settings of the light signals in accordance with the conditions in the field so often causes congestion. From finding a solution the traffic density in the study Letjend S Parman Street – Ciliwung Street and Letjend Sutoyo Street – Letjend Selorejo with Indonesia Highway Capasity Manual (IHCM). After stages 3-signal coordination calculation in Ciliwung Intersection of Malang, Intersection obtained time peak hours at the intersection area occurred at 11.00 – 12.00 GMT. Performance 3-waay junction on the Ciliwung Malang at this time has not met the target. Seen from there is still a Degree of Saturation (DS) which do not meet the targets ( ≤ 0,75), namely 0,83. After having don e engineering into 3 phases and cycle time 100 minutes Degree of Saturation (DS) be 0,77. Keywords: intersection, peak hours, capacity and degree saturation

scholarly journals Efficient Original-Destination Bandwidth: A Novel Model for Arterial Traffic Signal Coordination

2020 ◽  
Vol 53 (5) ◽  
pp. 609-616
Author(s):  
Ying Wang ◽  
Zongzhong Tian
Keyword(s):  
Lag Phase ◽  
Band Model ◽  
Time Dynamic ◽  
Signal Coordination ◽  
Dynamic Matrix ◽  
Phase Sequence ◽  
The Matrix ◽  
Arterial Traffic ◽  
The Relationship

This paper proposes an efficient origin-estimation bandwidth (OD band) model, which provides dedicated progression bands for arterial traffic based on the real-time dynamic matrix of their estimated OD pairs. The innovations of the OD band model are as follows: First, the dynamics of through and turning-in/out traffics are analyzed based on the matrix of their estimated OD pairs, and used to generate the traffic movement sequence at continuous intersections; Second, the end-time of green interval for lag-lag phase sequence at continuous intersections is determined according to the relevant constraints, the relationship between the start/end-time of green interval and the minimum/maximum green intervals; Third, the bandwidths of the two directions of the artery ware produced, after being weighted by their traffic demands. The intuitiveness, convenience, and feasibility of the OD band model were fully demonstrated through a case study. Overall, the OD band model helps to produce bi-directional progression bands for traffic with many turning movements on the artery, and enables the through and turning-in/out traffics to proceed through continuous intersections, when the signals at those intersections are green.

Evaluating the Operational Efficiency of Two Versions of Super Diverging Diamond Interchange Design: A Case Study in Denver, Colorado

2021 ◽  
pp. 036119812110372
Author(s):  
Muhammad Tahmidul Haq ◽  
Amirarsalan Mehrara Molan ◽  
Khaled Ksaibati
Keyword(s):  
Research Effort ◽  
Traffic Signals ◽  
Operational Efficiency ◽  
Traffic Demand ◽  
Operational Analysis ◽  
Signal Coordination ◽  
Traffic Volumes ◽  
Microsimulation Models ◽  
Better Than

This paper aims to advance the current research on the new super diverging diamond interchange (super DDI) design by evaluating the operational efficiency using real-world locations. As part of a comprehensive research effort on improving the performance of failing service interchanges in the mountain-plains region, the study identified three interchanges (Interstate 225 and Mississippi Avenue, Interstate 25 and 120th Avenue, and Interstate 25 and Hampden Avenue) at Denver, Colorado as the potential candidates to model for future retrofit. Four interchange designs (i.e., existing CDI [conventional diamond interchange], DDI, super DDI-1, and super DDI-2) were tested in this study. The operational analysis was conducted using VISSIM and Synchro. Several microsimulation models (120 scenarios with 600 runs in total) were created with three peak hours (a.m., noon, and p.m.) for existing (the year 2020) and projected (the year 2030) traffic volumes. The study considered two simulation networks: (1) when no adjacent traffic signal exists, to determine how the four interchange designs would perform if there were no adjacent signals or they were far away from the interchange; and (2) when there are two adjacent traffic signals, to evaluate the performance of the four interchanges in a bigger corridor with signal coordination needed. An important finding is that super DDI designs outperformed DDI with adjacent signals and higher traffic demand, while DDI performed similarly to or sometimes insignificantly better than super DDI if no adjacent intersections were located in the vicinity and if the demand was lower than the DDI’s capacity.

A joint control model for connected vehicle platoon and arterial signal coordination

2019 ◽  
Vol 24 (1) ◽  
pp. 81-92 ◽  
Author(s):  
Pangwei Wang ◽  
Yilun Jiang ◽  
Lin Xiao ◽  
Yi Zhao ◽  
Yinghong Li
Keyword(s):  
Control Model ◽  
Joint Control ◽  
Connected Vehicle ◽  
Signal Coordination ◽  
Vehicle Platoon

Signal Coordination and Arterial Capacity in Oversaturated Conditions

2000 ◽  
Vol 1727 (1) ◽  
pp. 68-76 ◽  
Author(s):  
Ghassan Abu-Lebdeh ◽  
Rahim Benekohal
Keyword(s):  
Queue Length ◽  
Processing Capability ◽  
Signal Coordination ◽  
Capacity Loss ◽  
Explicit Function ◽  
Queue Lengths ◽  
Input Variables ◽  
Intersection System ◽  
Critical Subsystems ◽  
Critical Subsystem

Models for estimation of the capacities of oversaturated arterials were developed. The input variables in these models are capacities of individual intersections, offsets, and vehicle queue lengths. Models for quantification of capacity loss due to blockage caused by downstream queues are also presented. The proposed models show that when arterial capacity is determined in oversaturated conditions, it is not sufficient to consider only the capacities of critical intersections; instead, the capacities of critical subsystems must be considered. A critical subsystem is any two intersections plus the link that joins them where traffic processing capability is the lowest. This traffic processing capability, or critical subsystem capacity, determines the arterial capacity. It is a function of the capacities of the respective intersections, the offset between them, and the queue length on the link joining them. It is shown that a critical subsystem is not unique in that it may change location over the course of the study period. To minimize capacity loss, it is shown that offsets must be an explicit function of queue lengths. The practical use of the models was demonstrated for an oversaturated two-intersection system. The results show that improper setting of offsets can lead to significant capacity loss. In extreme cases all capacity in a given cycle may be lost if the offsets are not set properly.

scholarly journals Transit-Based Emergency Evacuation with Transit Signal Priority in Sudden-Onset Disaster

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Ciyun Lin ◽  
Bowen Gong
Keyword(s):  
Arrival Time ◽  
Time Estimation ◽  
Emergency Evacuation ◽  
Sudden Onset ◽  
Traffic Signal ◽  
Traffic Signal Control ◽  
Transit Signal Priority ◽  
Signal Coordination ◽  
Arterial Traffic ◽  
Evacuation Route

This study presents methods of transit signal priority without transit-only lanes for a transit-based emergency evacuation in a sudden-onset disaster. Arterial priority signal coordination is optimized when a traffic signal control system provides priority signals for transit vehicles along an evacuation route. Transit signal priority is determined by “transit vehicle arrival time estimation,” “queuing vehicle dissipation time estimation,” “traffic signal status estimation,” “transit signal optimization,” and “arterial traffic signal coordination for transit vehicle in evacuation route.” It takes advantage of the large capacities of transit vehicles, reduces the evacuation time, and evacuates as many evacuees as possible. The proposed methods were tested on a simulation platform with Paramics V6.0. To evaluate and compare the performance of transit signal priority, three scenarios were simulated in the simulator. The results indicate that the methods of this study can reduce the travel times of transit vehicles along an evacuation route by 13% and 10%, improve the standard deviation of travel time by 16% and 46%, and decrease the average person delay at a signalized intersection by 22% and 17% when the traffic flow saturation along an evacuation route is0.8<V/C≤1.0andV/C>1.0, respectively.

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