Genetic algorithm for solving dynamic simultaneous route and departure time equilibrium problem

We present a genetic algorithm for solving dynamic simultaneous route and departure time equilibrium problem. Not only can a flow‐swapping process in the algorithm guarantee the flow conservation constraints between OD pair, but also accelerate the convergence velocity of the algorithm. Finally, a simulation example shows feasibility and validity of genetic algorithm. First published online: 27 Oct 201

A Multi-mode, Multi-class Dynamic Network Model With Queues For Advanced Transportation Information Systems

In this paper we propose a composite Variational Inequality formulation for modeling multimode, multi-class stochastic dynamic user equilibrium problem in recurrent congestion networks with queues. The modes typically refer to different vehicle types such as passenger cars, trucks, and buses sharing the same road space. Each vehicle type has its own characteristics, such as free flow speed, vehicle size. We extend single mode deterministic point model to multimode deterministic point model for modeling the asymmetric interactions among various modes. Meanwhile, each mode of travelers is classified into two classes. Class 1 is equipped travelers following stochastic dynamic user-equilibrium with less uncertainty of travel cost, class 2 is unequipped travelers following stochastic dynamic user-equilibrium with more uncertainty of travel cost. A solution algorithm based on stochastic dynamic network loading for logit-based simultaneous route and departure time choices is adopted. Finally a numerical example is presented in a simple network

주행 중 충전 행태를 고려한 배터리 전기차의 동적 이용자 평형 모형

학위논문 (석사)-- 서울대학교 대학원 : 건설환경공학부, 2017. 2. 고승영.Facing with increasing demands on Battery Electric Vehicle (BEV), public interests of incorporating BEVs into existing operational and planning models of transportation systems are growing recently. Unlike gasoline vehicles, BEV users encounter range anxiety that comes from short driving range, long charging time, and insufficient charging infrastructures. BEV drivers who encounters the range anxiety problem are expected to have different route choice behaviors from the existing drivers and will resist being stuck in the middle of trips, for not having enough battery states. Several models have been developed to reflect this aspect in static traffic assignment models. However, Dynamic Traffic Assignment (DTA) incorporating BEVs on it have hardly been researched yet. In addition to generally researched static models, the temporal approach toward BEV can broaden analytical scopes in a temporal manner and can be used for analysis related to operational planning. Therefore, this research proposes a Dynamic User Equilibrium (DUE) model of BEVs that can reflect drivers behaviors incurred by range anxiety. In this research, a trip-based DTA model for BEVs is developed. It is because the usable paths of a BEV are completely determined by its remaining battery state, a path-based discrete time DTA model is formulated to track the battery states of BEVs at each time interval. The models objective function is composed of travel time and out-of-range penalty term induced from battery shortage for assigned path flows. A modified iterative flow swapping algorithm is adopted to gradually decrease the out-of-range penalty and travel time gap between shortest paths and non-shortest paths. The suggested model is applied to an example problem of Nguyen-Dupuis network with insufficient initial battery state. As a result, given with insufficient initial battery state, traffic flows of BEV detoured to maintain their batteries to be higher than minimal comfortable amount in a dynamic transportation system. The experienced travel time for traffic flows that had the same O-D and departing time interval showed identical value and traversed their paths without running out of batteries.1.Introduction 1 1.1.Background 1 1.2. Motivation 2 1.3. Objectives 5 1.4. Organization of Thesis 7 2.Literature Review 8 2.1. Static User Equilibrium Models 8 2.2. Dynamic User Equilibrium Models 13 2.3. Review result 16 3.Model Development 18 3.1.Problem Description 18 3.2.Mathematical Formulation 19 4.Algorithm 30 4.1.Flow Swapping algorithm 30 4.2. Modified algorithm 31 5.Numerical Example 35 5.1.Network properties 35 5.2.Assignment result 37 6.Conclusions 43 6.1.Summary and conclusion 43 국문 초록 49Maste

The nonlinear equation system approach to solving dynamic user optimal simultaneous route and departure time choice problems

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Control Theoretic Approaches to Congestion Pricing for High-occupancy Toll Lanes

The purpose of this study is to propose control theoretic approaches for high-occupancy toll (HOT) lanes operation. This dissertation considers different operation objectives, and provides pricing schemes for HOT lanes accordingly.To improve the system performance, the study first proposes a simultaneous estimation and control method for the same system as that in (Yin and Lou, 2009). An integral controller is applied to estimate the average value of time (VOT) of SOVs, and the dynamic prices are calculated based on the logit model. The closed-loop system is proved to be stable and guaranteed to converge to the optimal state both analytically and numerically. Two convergence patterns, Gaussian or exponential, are revealed. The effect of the scale parameter in the logit model is also examined.Then, a new lane choice model, i.e., the vehicle-based user equilibrium principle, is proposed to capture the lane choice of SOVs. A general lane choice model is derived based on the characteristics of the logit and the vehicle-based UE model. An insight regarding the dynamic price is obtained by analytically solving the optimal dynamic prices with constant demands of HOVs and SOVs, and then a feedback controller is designed to determine the dynamic prices without knowing SOVs’ lane choice models, but to satisfy the two control objectives: maximizing the flow-rate but not forming a queue on the HOT lanes. If the type of the lane choice model is given, the distribution of VOTs of the SOVs can be estimated.Next, an optimal control problem is proposed to examine the statement that revenue maximization should generally coincide with the optimization of freeway performances, such as maximizing overall travel-time savings or throughput. Results show that operators need to make different strategies based on the traffic demand. In order to maximize the revenue, operators should set a higher price to make the HOT lanes underutilized if the demand of HOVs is low. However, if the demand of HOVs is high, operators need to set a lower price to attract more SOVs to create congestion on the HOT lanes.It has long been known that drivers’ departure time choice behavior is one fundamental cause of congestion. In the last part of this dissertation, pricing schemes are proposed to consider both lane choice and departure time choice. In the study period, the demands for the HOT and GP lanes are higher than their capacities, which means the whole freeway is congested. However, the congestion period on the HOT lanes is short than that on the GP lanes. So, the HOT lanes are “underutilized”. It turns out that flat (instead of dynamic) pricing schemes are able to meet the following two constraints: (1) the total travel time and scheduling cost is minimized; and (2) the costs for each non-switching and switching SOV are the same. We show that different revenue and tolling constrains for certain type of vehicles lead to different pricing schemes

Dynamic traffic congestion pricing mechanism with user-centric considerations

Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 85-95).In this thesis, we consider the problem of designing real-time traffic routing systems in urban areas. Optimal dynamic routing for multiple passengers is known to be computationally hard due to its combinatorial nature. To overcome this difficulty, we propose a novel mechanism called User-Centric Dynamic Pricing (UCDP) based on recent advances in algorithmic mechanism design. The mechanism allows for congestion-free traffic in general road networks with heterogeneous users, while satisfying each user's travel preference. The mechanism first informs whether a passenger should use public transportation or the road network. In the latter case, a passenger reports his maximum accepted travel time with a lower bound announced publicly by the road authority. The mechanism then assigns the passenger a path that matches with his preference given the current traffic condition in the network. The proposed mechanism introduces a fairness constrained shortest path (FCSP) problem with a special structure, thus enabling polynomial time computation of path allocation that maximizes the sequential social surplus and guarantees fairness among passengers. The tolls of paths are then computed according to marginal cost payments. We show that reporting true preference is a weakly dominant strategy. The performance of the proposed mechanism is demonstrated on several simulated routing experiments in comparison to user equilibrium and system optimum.by Kim Thien Bui.S.M. in Transportatio

System optimal traffic assignment with departure time choice

This thesis investigates analytical dynamic system optimal assignment with departure time choice in a rigorous and original way. Dynamic system optimal assignment is formulated here as a state-dependent optimal control problem. A fixed volume of traffic is assigned to departure times and routes such that the total system travel cost is minimized. Although the system optimal assignment is not a realistic representation of traffic, it provides a bound on performance and shows how the transport planner or engineer can make the best use of the road system, and as such it is a useful benchmark for evaluating various transport policy measures. The analysis shows that to operate the transport system optimally, each traveller in the system should consider the dynamic externality that he or she imposes on the system from the time of his or her entry. To capture this dynamic externality, we develop a novel sensitivity analysis of travel cost. Solution algorithms are developed to calculate the dynamic externality and traffic assignments based on the analyses. We also investigate alternative solution strategies and the effect of time discretization on the quality of calculated assignments. Numerical examples are given and the characteristics of the results are discussed. Calculating dynamic system optimal assignment and the associated optimal toll could be too difficult for practical implementation. We therefore consider some practical tolling strategies for dynamic management of network traffic. The tolling strategies considered in this thesis include both uniform and congestion-based tolling strategies, which are compared with the dynamic system optimal toll so that their performance can be evaluated. In deriving the tolling strategies, it is assumed that we have an exact model for the underlying traffic behaviour. In reality, we do not have such information so that the robustness of a toll calculation method is an important issue to be investigated in practice. It is found that the tolls calculated by using divided linear traffic models can perform well over a wide range of scenarios. The divided linear travel time models thus should receive more attention in the future research on robust dynamic traffic control strategies design. In conclusion, this thesis contributes to the literature on dynamic traffic modelling and management, and to support further analysis and model development in this area