Efficiently solving the user equilibrium traffic assignment problem with elastic demand(UE-TAPED)for transportation networks is a critical problem for transportation studies.Most existing UE-TAPED algorithms are desig...Efficiently solving the user equilibrium traffic assignment problem with elastic demand(UE-TAPED)for transportation networks is a critical problem for transportation studies.Most existing UE-TAPED algorithms are designed using a sequential computing scheme,which cannot take advantage of advanced parallel computing power.Therefore,this study focuses on model decomposition and parallelization,proposing an origin-based formulation for UE-TAPED and proving an equivalent reformulation of the original problem.Furthermore,the alternative direction method of multipliers(ADMM)is employed to decompose the original problem into independent link-based subproblems,which can solve large-scale problems with small storage space.In addition,to enhance the efficiency of our algorithm,the parallel computing technology with optimal parallel computing schedule is implemented to solve the link-based subproblems.Numerical experiments are performed to validate the computation efficiency of the proposed parallel algorithm.展开更多
This paper investigates the dynamical behaviour of network traffic flow. Assume that trip rates may be influenced by the level of service on the network and travellers are willing to take a faster route. A discrete dy...This paper investigates the dynamical behaviour of network traffic flow. Assume that trip rates may be influenced by the level of service on the network and travellers are willing to take a faster route. A discrete dynamical model for the day-to-day adjustment process of route choice is presented. The model is then applied to a simple network for analysing the day-to-day behaviours of network flow. It finds that equilibrium is arrived if network flow consists of travellers not very sensitive to the differences of travel cost. Oscillations and chaos of network traffic flow are also found when travellers are sensitive to the travel cost and travel demand in a simple network.展开更多
A new travel time reliability-based traffic assignment model is proposed to investigate the effects of an advanced transportation information system (ATIS) on drivers' risk-taking path choice behaviours in transpo...A new travel time reliability-based traffic assignment model is proposed to investigate the effects of an advanced transportation information system (ATIS) on drivers' risk-taking path choice behaviours in transportation networks with demand uncertainty. In the model, drivers are divided into two classes. The first class is not equipped with ATIS, while the second class is equipped with ATIS. Different risk-taking path choice behaviours of the two classes are studied, respectively. A corresponding mixed equilibrium traffic assignment model is formulated as a variational inequality problem in terms of path flows, which is solved by a heuristic solution algorithm. Numerical results indicate that the ATIS can influence the drivers' risk-taking path choice behaviours and the total system travel time in transportation networks with demand uncertainty. It is also found that under higher demand levels, the benefits of ATIS for network performance enhancement may be more obvious.展开更多
基金supported by the National Natural Science Foundation of China(Nos.52302391,5202375,and 52131203)the Natural Science Foundation of Jiangsu Province,China(No.BK20210247)the Fundamental Research Funds for the Central Universities,China(No.2242022R40025).
文摘Efficiently solving the user equilibrium traffic assignment problem with elastic demand(UE-TAPED)for transportation networks is a critical problem for transportation studies.Most existing UE-TAPED algorithms are designed using a sequential computing scheme,which cannot take advantage of advanced parallel computing power.Therefore,this study focuses on model decomposition and parallelization,proposing an origin-based formulation for UE-TAPED and proving an equivalent reformulation of the original problem.Furthermore,the alternative direction method of multipliers(ADMM)is employed to decompose the original problem into independent link-based subproblems,which can solve large-scale problems with small storage space.In addition,to enhance the efficiency of our algorithm,the parallel computing technology with optimal parallel computing schedule is implemented to solve the link-based subproblems.Numerical experiments are performed to validate the computation efficiency of the proposed parallel algorithm.
文摘This paper investigates the dynamical behaviour of network traffic flow. Assume that trip rates may be influenced by the level of service on the network and travellers are willing to take a faster route. A discrete dynamical model for the day-to-day adjustment process of route choice is presented. The model is then applied to a simple network for analysing the day-to-day behaviours of network flow. It finds that equilibrium is arrived if network flow consists of travellers not very sensitive to the differences of travel cost. Oscillations and chaos of network traffic flow are also found when travellers are sensitive to the travel cost and travel demand in a simple network.
基金The National High Technology Research and Development Program of China (863 Program) (No.2006AA11Z209)Youth Science and Technology Foundation of China University of Mining and Technology (No.2007A028)Natural Science Foundation of Beijing (No.9073018)
文摘A new travel time reliability-based traffic assignment model is proposed to investigate the effects of an advanced transportation information system (ATIS) on drivers' risk-taking path choice behaviours in transportation networks with demand uncertainty. In the model, drivers are divided into two classes. The first class is not equipped with ATIS, while the second class is equipped with ATIS. Different risk-taking path choice behaviours of the two classes are studied, respectively. A corresponding mixed equilibrium traffic assignment model is formulated as a variational inequality problem in terms of path flows, which is solved by a heuristic solution algorithm. Numerical results indicate that the ATIS can influence the drivers' risk-taking path choice behaviours and the total system travel time in transportation networks with demand uncertainty. It is also found that under higher demand levels, the benefits of ATIS for network performance enhancement may be more obvious.
