scholarly journals Network Traffic Flow Evolution Model Based on Disequilibrium Theory

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Zhongxiang Huang ◽  
Jianhui Wu ◽  
Ruqing Huang ◽  
Yan Xu
Keyword(s):  
Traffic Flow ◽  
Unique Solution ◽  
Network Traffic ◽  
User Equilibrium ◽  
Price Regulation ◽  
Evolution Model ◽  
Evolution Process ◽  
Multiple User ◽  
Flow Evolution ◽  
Disequilibrium Theory

The disequilibrium theory in economics is used to depict the network traffic flow evolution process from disequilibrium to equilibrium. Three path choice behavior criteria are proposed, and the equilibrium traffic flow patterns formed by these three criteria are defined as price regulation user equilibrium, quantity regulation user equilibrium, and price-quantity regulation user equilibrium, respectively. Based on the principle of price-quantity regulation user equilibrium, the method of network tatonnement process is used to establish a network traffic flow evolution model. The unique solution of the evolution model is proved by using Picard’s existence and uniqueness theorem, and the stability condition of the unique solution is derived based on stability theorem of nonlinear system. Through numerical experiments, the evolution processes of network traffic flow under different regulation modes are analyzed. The results show that all the single price regulation, single quantity regulation, and price-quantity regulation can simulate the evolution process of network traffic flow. Price-quantity regulation is the combination of price regulation user equilibrium and quantity regulation user equilibrium, which thus can simulate the evolution process of network traffic flow with multiple user class.

scholarly journals A Traffic Flow Evolution Process toward Mixed Equilibrium with Multicriteria of Route Choice Behaviour

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Xiangjun Jiang ◽  
Zhongxiang Huang ◽  
Zhenyu Zhao
Keyword(s):  
Equilibrium State ◽  
Traffic Flow ◽  
Complete Information ◽  
User Equilibrium ◽  
Evolution Model ◽  
Choice Behaviour ◽  
Flow Evolution ◽  
Quantity Adjustment ◽  
Mixed Equilibrium ◽  
Equilibrium Pattern

Based on the price-quantity adjustment behaviour principle of disequilibrium theory, the route choices of travellers are also affected by a quantity signal known as traffic flow, while the route cost is considered as a price signal in economics. Considering the quantity signal’s effect among travellers, a new route comfort choice behaviour criterion and its corresponding equilibrium condition are established. The network travellers are classified into three groups according to their route choice behaviour: travellers in the first group choose the shortest route following the route rapidity behaviour criterion with complete information forming the UE (user equilibrium) pattern, travellers in the second group choose the most comfortable route following the route comfort behaviour criterion with complete information forming the QUE (quantity adjustment user equilibrium) pattern, and travellers in the third group choose a route according to their perceived travel time with incomplete information forming the SUE (stochastic user equilibrium) pattern. The traffic flows of all three groups converge to a new UE-QUE-SUE mixed equilibrium flow pattern after interaction. To depict the traveller-diversified choice behaviour and the traffic flow interaction process, a mixed equilibrium traffic flow evolution model is formulated. After defining the route comfort indicator and the corresponding user equilibrium state, the equilibrium conditions of the three group flows are given under a mixed equilibrium pattern. In addition, an equivalent mathematical programming of the mixed equilibrium traffic flow evolution model is proposed to demonstrate that the developed model converges to the mixed equilibrium state. Finally, numerical examples are examined to evaluate the effect of route comfort proportions on the traffic network flow evolution and analyse the performance of the proposed model.

The impact of travelers’ rationality degree heterogeneity in the Advanced Traveler Information System on the network traffic flow evolution

SIMULATION ◽  
2017 ◽  
Vol 93 (6) ◽  
pp. 447-457 ◽  
Author(s):  
Jianqiang Wang ◽  
Shiwei Li
Keyword(s):  
Information System ◽  
Traffic Flow ◽  
Network Traffic ◽  
Mixed Logit ◽  
Evolution Model ◽  
Traffic Information ◽  
Traveler Information ◽  
Integrated Simulation ◽  
Advanced Traveler Information System ◽  
The Impact

The interplay between traffic information, which is normally distributed by the Advanced Traveler Information System (ATIS) and travelers’ decision behaviors, is prone to lead to high complexity in the evolution process of network traffic flow. Considering the obvious heterogeneity that is reflected in the numerous ways that travelers adopt ATIS information and choose routes, the lognormal distribution is adopted to describe the heterogeneity of travelers’ rationality degree. Introducing habitual factors of traveler route choice, modeling ideas of Multi-Agent and Mixed Logit are utilized to construct the day-to-day evolution model of network traffic flow, which is based on the value difference of travelers’ cognitive travel time. Furthermore, an integrated simulation algorithm based on the Monte Carlo method is specially designed to solve the previous evolution model. The simulation indicates that a lower individual difference and a higher rationality degree would lead to a more obvious aggregation phenomenon of network traffic flow and inefficiency of operation in road networks.

scholarly journals Distance-Based Congestion Pricing with Day-to-Day Dynamic Traffic Flow Evolution Process

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Qixiu Cheng ◽  
Jiping Xing ◽  
Wendy Yi ◽  
Zhiyuan Liu ◽  
Xiao Fu
Keyword(s):  
Robust Optimization ◽  
Traffic Flow ◽  
Adaptive Learning ◽  
Optimization Model ◽  
Congestion Pricing ◽  
Planning Horizon ◽  
Travel Cost ◽  
Evolution Process ◽  
Dynamic Traffic ◽  
Flow Evolution

This paper studies the distance-based congestion pricing in a network considering the day-to-day dynamic traffic flow evolution process. It is well known that, after an implementation or adjustment of a new congestion toll scheme, the network environment will change and traffic flows will be nonequilibrium in the following days; thus it is not suitable to take the equilibrium-based indexes as the objective of the congestion toll. In the context of nonequilibrium state, prior research proposed a mini–max regret model to solve the distance-based congestion pricing problem in a network considering day-to-day dynamics. However, it is computationally demanding due to the calculation of minimal total travel cost for each day among the whole planning horizon. Therefore, in order to overcome the expensive computational burden problem and make the robust toll scheme more practical, we propose a new robust optimization model in this paper. The essence of this model, which is an extension of our prior work, is to optimize the worst condition among the whole planning period and ameliorate severe traffic congestions in some bad days. Firstly, a piecewise linear function is adopted to formulate the nonlinear distance toll, which can be encapsulated to a day-to-day dynamics context. A very clear and concise model named logit-type Markov adaptive learning model is then proposed to depict commuters’ day-to-day route choice behaviors. Finally, a robust optimization model which minimizes the maximum total travel cost among the whole planning horizon is formulated and a modified artificial bee colony algorithm is developed for the robust optimization model.

An Improved Stacked Auto-Encoder for Network Traffic Flow Classification

IEEE Network ◽  
2018 ◽  
Vol 32 (6) ◽  
pp. 22-27 ◽  
Author(s):  
Peng Li ◽  
Zhikui Chen ◽  
Laurence T. Yang ◽  
Jing Gao ◽  
Qingchen Zhang ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Network Traffic ◽  
Flow Classification

scholarly journals Additional Riderships Estimation under Different Configurations of Bus Rapid Transit System

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Wu Lan ◽  
Chen Xuewu ◽  
Lu Tao
Keyword(s):  
Traffic Flow ◽  
Numerical Test ◽  
User Equilibrium ◽  
Bus Rapid Transit ◽  
Stochastic User Equilibrium ◽  
Rapid Transit ◽  
Traffic Equilibrium ◽  
Estimation Model ◽  
Transit System ◽  
Diagonalization Method

Different configurations of Bus Rapid Transit (BRT) system may cause different additional riderships. In this paper, in terms of network traffic equilibrium assignment principle, the additional riderships estimation model based on Variational Inequality (VI) model is presented. The bus frequency is related to variables including the travel time, the residence time in terminals, and the dwelling time at the stops. The additional riderships are translated into network additional traffic flow firstly. Given the bus frequency, VI model can be turned into Stochastic User Equilibrium (SUE) model to calculate the other variables. The similarity diagonalization method is used to calculate the elastic bus frequency and finally the network additional traffic flow can be computed. The additional riderships under different configurations of BRT system are compared in the numerical test. The results show that the additional riderships under different configurations have large differences and occupy a high percentage of the total ridership.

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