scholarly journals Effects of traffic signal coordination on the safety performance of urban arterials

2022 ◽  
Vol 2 (1) ◽  
Author(s):  
Rui Yue ◽  
Guangchuan Yang ◽  
Yichen Zheng ◽  
Yuxin Tian ◽  
Zong Tian

AbstractUrban traffic congestion and crashes have been considered by city planners as critical challenges to the economic development of the city. Traffic signal coordination, which connects a series of signals along an arterial by various coordination methodologies, has been proved as one of the most cost-effective means of reducing traffic congestion. In this regard, Metropolitan Planning Organizations (MPO) or Transportation Management Centers (TMC) have included signal timing coordination in their strategic plans. Nevertheless, concerns on the safety effects of traffic signal coordination have been continuously raised by both transportation agencies and the public. This is mainly because signal coordination may increase the travel speed along an arterial, which increases the risk and severity of traffic collisions. To date, there is neither solid evidence from the field to support the concern, nor theoretical-level models to analyze this issue. This research aims to investigate the effects of traffic signal coordination on the safety performance of urban arterials through microsimulation modeling of two traffic operational conditions: free signal operation and coordinated signals, respectively. Three urban arterials in Reno, Nevada were selected as the simulation testbed and were coded in the PTV VISSIM software. The simulated trajectory data were analyzed by the Surrogate Safety Assessment Model (SSAM) to estimate the number of traffic conflicts. Sensitivity analyses were conducted for various traffic demand levels. Results show that under unsaturated conditions, traffic signal coordination could reduce the number of conflicts in comparison with the free signal operation condition. However, under oversaturated conditions, no significant difference was found between coordinated and free signal operations. Findings from this research indicate that traffic signal coordination has the potential to reduce the risk of crashes on urban arterials under unsaturated conditions.

2020 ◽  
Vol 6 ◽  
pp. e319
Author(s):  
Haitao Xu ◽  
Zuozhang Zhuo ◽  
Jing Chen ◽  
Xujian Fang

As an effective method to alleviate traffic congestion, traffic signal coordination control has been applied in many cities to manage queues and to regulate traffic flow under oversaturated traffic condition. However, the previous methods are usually based on two hypotheses. One is that traffic demand is constant. The other assumes that the velocity of vehicle is immutable when entering the downstream section. In the paper, we develop a novel traffic coordination control method to control the traffic flow along oversaturated two-way arterials without both these hypotheses. The method includes two modules: intersection coordination control and arterial coordination control. The green time plan for all intersections can be obtained by the module of intersection coordination control. The module of arterial coordination control can optimize offset plan for all intersections along oversaturated two-way arterials. The experiment results verify that the proposed method can effectively control the queue length under the oversaturated traffic state. In addition, the delay in this method can be decreased by 5.4% compared with the existing delay minimization method and 13.6% compared with the traffic coordination control method without offset optimization. Finally, the proposed method can balance the delay level of different links along oversaturated arterial, which can directly reflect the efficiency of the proposed method on the traffic coordination control under oversaturated traffic condition.


IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 69481-69491 ◽  
Author(s):  
Zhenhua Chen ◽  
Yongjian Yang ◽  
Liping Huang ◽  
En Wang ◽  
Dawei Li

2020 ◽  
Vol 32 (2) ◽  
pp. 229-236
Author(s):  
Songhang Chen ◽  
Dan Zhang ◽  
Fenghua Zhu

Regional Traffic Signal Control (RTSC) is believed to be a promising approach to alleviate urban traffic congestion. However, the current ecology of RTSC platforms is too closed to meet the needs of urban development, which has also seriously affected their own development. Therefore, the paper proposes virtualizing the traffic signal control devices to create software-defined RTSC systems, which can provide a better innovation platform for coordinated control of urban transportation. The novel architecture for RTSC is presented in detail, and microscopic traffic simulation experiments are designed and conducted to verify the feasibility.


2018 ◽  
Vol 11 (3) ◽  
pp. 57
Author(s):  
Xiao-Yan Cao ◽  
Bing-Qian Liu ◽  
Bao-Ru Pan ◽  
Yuan-Biao Zhang

With the accelerating development of urbanization in China, the increasing traffic demand and large scale gated communities have aggravated urban traffic congestion. This paper studies the impact of communities opening on road network structure and the surrounding road capacity. Firstly, we select four indicators, namely average speed, vehicle flow, average delay time, and queue length, to measure traffic capacity. Secondly, we establish the Wiedemann car-following model, then use VISSIM software to simulate the traffic conditions of surrounding roads of communities. Finally, we take Shenzhen as an example to simulate and compare the four kinds of gated communities, axis, centripetal and intensive layout, and we also analyze the feasibility of opening communities.


2012 ◽  
Vol 209-211 ◽  
pp. 945-951
Author(s):  
Xue Zhong Zhang ◽  
Wei Shui Fei ◽  
Xiao Jun Ning

In the face of increasingly congested urban traffic caused by all sorts of harm, how to solve the traffic congestion problem in the urban is becoming the major hot spot which domestic and foreign experts and scholars pay close attention to and study. This paper in a microscopic angle to analyze the problem -- urban traffic intersection congestion,not in macroscopical city planning, transportation planning, urban traffic demand to discuss. Through exploring the urban road system structure and operational mechanism, development of the automobile overpass is to solve the intersection congestion.


2011 ◽  
Vol 97-98 ◽  
pp. 1032-1037
Author(s):  
Wei Kou ◽  
Lin Cheng

With the development and realization of industrialization and urbanization in the world, urban traffic volume grows rapidly; many big cities face more and more serious traffic problem. As a mean of traffic demand management, traffic congestion pricing has important significance in theory and practice. Traffic congestion pricing can counteract external diseconomy caused by network congestion, and the price of congestion is tantamount to the difference between social marginal cost and private marginal cost. This paper analyzes the economic theory of congestion pricing. Combined the effect of traffic congestion pricing that implemented in the developed countries, it researches the influence of urban transportation development in our country in the future based on the implementing congestion pricing.


2014 ◽  
Vol 513-517 ◽  
pp. 3160-3164
Author(s):  
Xue Li Zhang

Traffic congestion are prevalent in worldwide cities. The imbalance between demand and supply of urban traffic is the root cause of this problem. So taking effective measures to regulate traffic demand, and guiding the traffic problems of the supply and demand balance is the best way to solve traffic congestion. This paper improves the TDM measure, and combines with intelligent information platform for the design of a new urban transport demand management adaptability of dynamic traffic data analysis platform. The platform supported by the technology of wireless sensor communications, intelligent terminals, the Internet and cloud computing is facing with the dynamic needs of traffic flow and traffic congestion state to carry out the operations of spatiotemporal data mining, clustering, and track detection, and to apply it into the traffic hot spots, abnormal driving track, traffic congestion trends and traffic flow detection and analysis, which has a good reference value for the improvement of management and service level of traffic intelligent systems.


Author(s):  
Isaac K. Isukapati ◽  
Hana Rudová ◽  
Gregory J. Barlow ◽  
Stephen F. Smith

Transit vehicles create special challenges for urban traffic signal control. Signal timing plans are typically designed for the flow of passenger vehicles, but transit vehicles—with frequent stops and uncertain dwell times—may have different flow patterns that fail to match those plans. Transit vehicles stopping on urban streets can also restrict or block other traffic on the road. This situation results in increased overall wait times and delays throughout the system for transit vehicles and other traffic. Transit signal priority (TSP) systems are often used to mitigate some of these issues, primarily by addressing delay to the transit vehicles. However, existing TSP strategies give unconditional priority to transit vehicles, exacerbating quality of service for other modes. In networks for which transit vehicles have significant effects on traffic congestion, particularly urban areas, the use of more-realistic models of transit behavior in adaptive traffic signal control could reduce delay for all modes. Estimating the arrival time of a transit vehicle at an intersection requires an accurate model of dwell times at transit stops. As a first step toward developing a model for predicting bus arrival times, this paper analyzes trends in automatic vehicle location data collected over 2 years and allows several inferences to be drawn about the statistical nature of dwell times, particularly for use in real-time control and TSP. On the basis of this trend analysis, the authors argue that an effective predictive dwell time distribution model must treat independent variables as random or stochastic regressors.


2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Hongna Dai ◽  
Enjian Yao ◽  
Rui Zhao

Rapid development of urbanization and automation has resulted in serious urban traffic congestion and air pollution problems in many Chinese cities recently. As a traffic demand management strategy, congestion pricing is acknowledged to be effective in alleviating the traffic congestion and improving the efficiency of traffic system. This paper proposes an urban traffic congestion pricing model based on the consideration of transportation network efficiency and environment effects. First, the congestion pricing problem under multimode (i.e., car mode and bus mode) urban traffic network condition is investigated. Second, a traffic congestion pricing model based on bilevel programming is formulated for a dual-mode urban transportation network, in which the delay and emission of vehicles are considered. Third, an improved mathematical algorithm combining successive average method with the genetic algorithm is proposed to solve the bilevel programming problem. Finally, a numerical experiment based on a hypothetical network is performed to validate the proposed congestion pricing model and algorithm.


2021 ◽  
Author(s):  
Sharareh Shadbakhsh

The increasing volume of traffic in cities has a significant effect on road traffic congestion and the travel time it takes for road users to reach their destinations. Coordinating traffic signals, which is a system of light that cascade in sequence where a platoon of vehicles can travel through a continuous series of green light without stopping, can improve the driver's experience significantly. This report covers the development of a coordinated traffic signal system along Wellington Street West from Church Street to Blue Jays Way Street as part of a City of Toronto signal coordination project. The objective of this study is to improve coordination through modification of signal timing plans while maintaining reasonably minimal impacts to the side street levels of service and delays. The overall goal is to reduced travel times, delays, number of stops and fuel consumption, resulting in public benefit.


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