A Study on the Coordination of Urban Traffic Control and Traffic Assignment

Qu, Zhaowei; Xing, Yan; Song, Xianmin; Duan, Yuzhou; Fan, Wei

doi:10.1155/2012/367468

Cited by 11 publications

(4 citation statements)

References 18 publications

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“…Given their integral role in urban transportation networks and their significant contribution to urban traffic flows, data on trajectories from all types of cars are commonly used for such calculations. Gühnemann et al [16] used GPS data from a fleet of vehicles to estimate traffic NOx emissions using an averagespeed-dependent estimating technique. Researchers used taxi GPS trajectory data to examine trends in fuel consumption and emissions in Beijing.…”

Section: Related Workmentioning

confidence: 99%

Controlling Traffic Congestion in a Residential Area via GLOSA Development

Jawad,

Nitulescu

2024

Applied Sciences

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The phenomenon of traffic congestion started in the second half of the twentieth century. This arose because of our society’s constant increase in demand for mobility. The excessive traffic of vehicles attempting to use the same infrastructure at the same time is what causes congestion. The consequences are well-known: delays, air pollution, reduced speed, and dissatisfaction (which may lead to risky maneuvers, reducing pedestrian and other driver safety). Our objective is to simulate the change in traffic patterns brought about by app users in residential areas (using navigational tools like Google Maps and Apple Maps), where the majority of navigational tools provide shortcuts that go through residential areas. In addition to discouraging navigation apps from directing drivers through residential areas during peak hours to mitigate pollution levels, by developing an algorithm based on the technology of Green Light Optimized Speed Advisory (GLOSA) and implementing it in a simulated environment (VISSIM), we can see the effect of changing the duration of red lights while keeping green lights constant. Overall, this solution can be implemented to change the times of traffic lights without the need for supplies, additional equipment, or warning signs because most cities’ traffic lights are already remotely controlled. In addition, this procedure is temporary to provide some freedom and does not adhere to the speed specified for drivers who wish to pass through residential areas outside of rush hour.

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Section: Related Workmentioning

confidence: 99%

Controlling Traffic Congestion in a Residential Area via GLOSA Development

Jawad,

Nitulescu

2024

Applied Sciences

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“…And it is a measurement that expresses the magnitude of the accessibility and smoothness of the vehicle in running. Traffic impedance is the basic element of path impedance, which directly affects travelers' path choice behavior [2] and is of great significance to traffic allocation of urban road network [3].…”

Section: Introductionmentioning

confidence: 99%

“…Sun et al [17] estimated the road impedance in real time by analyzing the dynamic changes of the intersection period. Qu et al [18], in order to improve the coordination of traffic signal settings and distribution, considered the effect of the dynamic impedance path for people travel plan. The existing dynamic impedance model has a single structure and cannot adapt to the road impedance estimation needs under different traffic flow distributions.…”

Section: Introductionmentioning

confidence: 99%

Microscopic Estimation of Road Impedance by Decomposing Traffic Delay into Individual Road Segments: An Analytical Approach

Bai

Luo

et al. 2019

Mathematical Problems in Engineering

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Urban road dynamic impedance calculation is the important basis of dynamic traffic assignment and real-time traffic management and control scheme. The current impedance calculation is mostly based on BPR function, and the BPR function is derived from macroscopic statistical laws, in which the microscopic characteristics of traffic flow are insufficiently described. In order to more accurately express the change laws of traffic impedance at the microscopic level, a stochastic dynamic traffic assignment algorithm based on road impedance function is designed to analyze the time impedance of congested roads under random dynamic traffic assignment under different conditions of road network saturation. Compared with the current model, the comprehensiveness and portability are greatly improved. The results show that the impedance calculation error of this method is less than 10% when the load degree of the road is lower than 0.85, which proves that the method has good precision under unsaturated flow conditions.

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“…Most traditional traffic assignment models assume that the travelers have the same value of time (VOT), namely, the homogeneity condition [20][21][22][23]. In fact, however, the transportation network has its heterogeneity as the travelers have different requirement for travel time due to the social status, economic income, and the nature of work.…”

Section: Introductionmentioning

confidence: 99%

A Multiclass, Multimodal Dynamic Traffic Assignment Model with Departure Time

Meng

Shao

Wong

et al. 2014

Mathematical Problems in Engineering

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The paper develops a multiclass, multimodal dynamic traffic equilibrium model with consideration of the departure time choice problem. Travelers choose the departure time and the route simultaneously with a Logit-based structure. The route travel cost is a summation of travel time and schedule delay which is associated with arrival time at destination. In addition, the travelers are classified into three groups according to their value of time. A variational inequality (VI) formulation is proposed based on the equilibrium conditions. Two examples are given to testify the effectiveness of the model and the solution algorithm. The model can give the optimal travel route as well as the best departure time, which would contribute to traffic control and dynamic route guidance.

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A Study on the Coordination of Urban Traffic Control and Traffic Assignment

Cited by 11 publications

References 18 publications

Controlling Traffic Congestion in a Residential Area via GLOSA Development

Controlling Traffic Congestion in a Residential Area via GLOSA Development

Microscopic Estimation of Road Impedance by Decomposing Traffic Delay into Individual Road Segments: An Analytical Approach

A Multiclass, Multimodal Dynamic Traffic Assignment Model with Departure Time

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