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Temelcan, Gizem, Hale Gonce Kocken, and Inci Albayrak. "System Optimum Fuzzy Traffic Assignment Problem." PROMET - Traffic&Transportation 31, no. 6 (December 16, 2019): 611–20. http://dx.doi.org/10.7307/ptt.v31i6.3210.
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This paper focuses on converting the system optimum traffic assignment problem (SO-TAP) to system optimum fuzzy traffic assignment problem (SO-FTAP). The SO-TAP aims to minimize the total system travel time on road network between the specified origin and destination points. Link travel time is taken as a linear function of fuzzy link flow; thus each link travel time is constructed as a triangular fuzzy number. The objective function is expressed in terms of link flows and link travel times in a non-linear form while satisfying the flow conservation constraints. The parameters of the problem are path lengths, number of lanes, average speed of a vehicle, vehicle length, clearance, spacing, link capacity and free flow travel time. Considering a road network, the path lengths and number of lanes are taken as crisp numbers. The average speed of a vehicle and vehicle length are imprecise in nature, so these are taken as triangular fuzzy numbers. Since the remaining parameters, that are clearance, spacing, link capacity and free flow travel time are determined by the average speed of a vehicle and vehicle length, they will be triangular fuzzy numbers. Finally, the original SO-TAP is converted to a fuzzy quadratic programming (FQP) problem, and it is solved using an existing approach from literature. A numerical experiment is illustrated.
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Liu, Henry X., Xuegang Ban, Bin Ran, and Pitu Mirchandani. "Formulation and Solution Algorithm for Fuzzy Dynamic Traffic Assignment Model." Transportation Research Record: Journal of the Transportation Research Board 1854, no. 1 (January 2003): 114–23. http://dx.doi.org/10.3141/1854-13.
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An issue that is always important in the development of traffic assignment models is how travelers' perceptions of travel time should be modeled. Because travelers rarely have perfect knowledge of the road network or of the travel conditions, they choose routes on the basis of their perceived travel times. Traditionally, travelers' perceived travel times are treated as random variables, leading to the stochastic traffic assignment problem. However, uncertain factors are also observed in the subjective recognition of travel times by travelers, and these can be illustrated as fuzzy variables. Therefore, a fuzzy dynamic traffic assignment model that takes into account the imprecision and the uncertainties in the route choice process is proposed. By modeling the expressions of perceived travel times as fuzzy variables, this model makes possible the description of a traveler's process of choosing a route that is more accurate and realistic than those from its deterministic or stochastic counter parts. The fuzzy perceived link travel time and fuzzy perceived path travel time are defined, and a fuzzy shortest path algorithm is used to find the group of fuzzy shortest paths and to assign traffic to each of them by using the so-called C-logit method. The results of the proposed model are also compared with those from the stochastic dynamic traffic assignment model, and it is demonstrated that the impact of advanced traveler information systems on the traveler's route choice process can be readily incorporated into the proposed model.
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van der Gun, Jeroen P. T., Adam J. Pel, and Bart van Arem. "Travel times in quasi-dynamic traffic assignment." Transportmetrica A: Transport Science 16, no. 3 (January 1, 2020): 865–91. http://dx.doi.org/10.1080/23249935.2020.1720862.
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Zhang, Kuilin, Hani S. Mahmassani, and Chung-Cheng Lu. "Probit-Based Time-Dependent Stochastic User Equilibrium Traffic Assignment Model." Transportation Research Record: Journal of the Transportation Research Board 2085, no. 1 (January 2008): 86–94. http://dx.doi.org/10.3141/2085-10.
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This study presents a time-dependent stochastic user equilibrium (TDSUE) traffic assignment model within a probit-based path choice decision framework that explicitly takes into account temporal and spatial correlation (traveler interactions) in travel disutilities across a set of paths. The TDSUE problem, which aims to find time-dependent SUE path flows, is formulated as a fixed-point problem and solved by a simulation-based method of successive averages algorithm. A mesoscopic traffic simulator is employed to determine (experienced) time-dependent travel disutilities. A time-dependent shortest-path algorithm is applied to generate new paths and augment a grand path set. Two vehicle-based implementation techniques are proposed and compared in order to show their impact on solution quality and computational efficiency. One uses the classical Monte Carlo simulation approach to explicitly compute path choice probabilities, and the other determines probabilities by sampling vehicles’ path travel costs from an assumed perception error distribution (also using a Monte Carlo simulation process). Moreover, two types of variance-covariance error structures are discussed: one considers temporal and spatial path choice correlation (due to path overlapping) in terms of aggregated path travel times, and the other uses experienced (or empirical) path travel times from a sample of individual vehicle trajectories. A set of numerical experiments are conducted to investigate the convergence pattern of the solution algorithms and to examine the impact of temporal and spatial correlation on path choice behavior.
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Li, Qing Yin, Rui Tang, and Zhang Lu Tan. "Based on Transcad of the Shortest Path Assignment Method." Advanced Materials Research 219-220 (March 2011): 1105–8. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.1105.
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Based on the Transcad all-or-nothing assignment model is a kind of static method; do not consider the travel time will be affected by traffic flow. The insufficient is that it does not conform to reality. In order to solve the all-or-nothing assignment model that to putting all of traffic flow on the shortest path, the text through the defining of the effective path and the traffic flow of the effective path to improve all-or-nothing assignment model. So the other road traffic flow can also assign and the results can reflect the assignment of urban traffic directly. It can be used to study the dynamic traffic assignment and traffic simulation analysis.
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Di, Shan, Changxuan Pan, and Bin Ran. "Stochastic Multiclass Traffic Assignment with Consideration of Risk-Taking Behaviors." Transportation Research Record: Journal of the Transportation Research Board 2085, no. 1 (January 2008): 111–23. http://dx.doi.org/10.3141/2085-13.
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A study of the problem of predicting traffic flows under traffic equilibrium in a stochastic transportation network is presented. Travelers’ risk-taking behaviors are explicitly modeled with respect to probabilistic travel times. Traveling risks are quantified from the travel time distributions directly and are embedded in the route choice conditions. The classification of risk-neutral, risk-averse, and risk-prone travelers is based on their preferred traveling risks. The formulation of the model clarifies that travelers with different risk preferences have the same objective–to save travel time cost–though they may make different route choices. The proposed solution algorithm is applicable for networks with normal distribution link travel times theoretically. Further simulation analysis shows that it can also be applied to approximate the equilibrium network flows for other frequently used travel time distribution families: gamma, Weibull, and log-normal. The proposed model was applied to a test network and a medium-sized transportation network. The results demonstrate that the model captures travelers’ risk-taking behaviors more realistically and flexibly compared with existing stochastic traffic equilibrium models.
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Shao, Hu, William H. K. Lam, Qiang Meng, and Mei Lam Tam. "Demand-Driven Traffic Assignment Problem Based on Travel Time Reliability." Transportation Research Record: Journal of the Transportation Research Board 1985, no. 1 (January 2006): 220–30. http://dx.doi.org/10.1177/0361198106198500124.
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Chen, Rongsheng, and Michael W. Levin. "Dynamic User Equilibrium of Mobility-on-Demand System with Linear Programming Rebalancing Strategy." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 1 (January 2019): 447–59. http://dx.doi.org/10.1177/0361198118821629.
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Mobility-on-demand (MoD) services are provided by multiple competing companies. In their competition for travelers, they need to provide minimum travel costs, or travelers will switch to competitors. This study developed a dynamic traffic assignment of MoD systems. A static traffic assignment (STA) model is first defined. When demand is asymmetric, empty rebalancing trips are required to move vehicles to traveler origins, and the optimal rebalancing flows are found by a linear program. Because of the time-dependent nature of traveler demand, the model was converted to dynamic traffic assignment (DTA). The method of successive averages, which is provably convergent for STA, was used to find dynamic user equilibrium (DUE). The simulation was conducted on two networks. The MoD system was simulated with different fleet sizes and demands. The results showed that the average total delay and travel distance decreased with the increase in fleet size whereas the average on-road travel time increased with the fleet size. The result of traffic assignment of one network with MoD system was compared with a network where all travelers use private vehicles. The results showed that the network with MoD system created more trips but less traffic congestion.
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Lu, Qiong, and Tamás Tettamanti. "Traffic Control Scheme for Social Optimum Traffic Assignment with Dynamic Route Pricing for Automated Vehicles." Periodica Polytechnica Transportation Engineering 49, no. 3 (September 1, 2021): 301–7. http://dx.doi.org/10.3311/pptr.18608.
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In transportation modeling, after defining a road network and its origin-destination (OD) matrix, the next important question is how to assign traffic among OD-pairs. Nowadays, advanced traveler information systems (ATIS) make it possible to realize the user equilibrium solution. Simultaneously, with the advent of the Cooperative Intelligent Transport Systems (C-ITS), it is possible to solve the traffic assignment problem in a system optimum way. As a potential traffic assignment method in the future transportation system for automated cars, the deterministic system optimum (DSO) is modeled and simulated to investigate the potential changes it may bring to the existing traditional traffic system. In this paper, stochastic user equilibrium (SUE) is used to simulate the conventional traffic assignment method. This work concluded that DSO has considerable advantages in reducing trip duration, time loss, waiting time, and departure delay under the same travel demand. What is more, the SUE traffic assignment has a more dispersed vehicle density distribution. Moreover, DSO traffic assignment helps the maximum vehicle density of each alternative path arrive almost simultaneously. Furthermore, DSO can significantly reduce or avoid the occurrence of excessive congestion.
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Kamel, Islam, Amer Shalaby, and Baher Abdulhai. "Integrated simulation-based dynamic traffic and transit assignment model for large-scale network." Canadian Journal of Civil Engineering 47, no. 8 (August 2020): 898–907. http://dx.doi.org/10.1139/cjce-2018-0706.
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Although the traffic and transit assignment processes are intertwined, the interactions between them are usually ignored in practice, especially for large-scale networks. In this paper, we build a simulation-based traffic and transit assignment model that preserves the interactions between the two assignment processes for the large-scale network of the Greater Toronto Area during the morning peak. This traffic assignment model is dynamic, user-equilibrium seeking, and includes surface transit routes. It utilizes the congested travel times, determined by the dynamic traffic assignment, rather than using predefined timetables. Unlike the static transit assignment models, the proposed transit model distinguishes between different intervals within the morning peak by using the accurate demand, transit schedule, and time-based road level-of-service. The traffic and transit assignment models are calibrated against actual field observations. The resulting dynamic model is suitable for testing different demand management strategies that impose dynamic changes on multiple modes simultaneously.
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Yu, Jiangbo Gabriel, and R. Jayakrishnan. "Multiclass, Multicriteria Dynamic Traffic Assignment with Path-Dependent Link Cost and Entropy-Based Risk Preference." Transportation Research Record: Journal of the Transportation Research Board 2667, no. 1 (January 2017): 108–18. http://dx.doi.org/10.3141/2667-11.
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Challenges arise in dynamic traffic assignment (DTA) when heterogeneous users evaluate choices on the basis of multiple interrelated criteria such as travel time and travel time uncertainty. This paper proposes a density-based formulation along with a stochastic quasigradient projection (SQGP) solution scheme with the aid of a traffic simulator. Path-dependent link cost is proposed to allow for the objective function formulation and more tractable analysis. The criteria in the discussion and the case study are travel time (link-additive), monetary cost (non additive), and travel time uncertainty (path-dependent link-additive). An information entropy-based uncertainty measure is proposed because of concerns about using conventional measures such as variability and reliability. The case study shows stochastic and efficient convergence, demonstrates the ability of SQGP to bypass local optima, and exemplifies the significant effect of using path-independent and path-dependent link costs to forecast traffic pattern and toll revenue. The results also suggest that a pricing strategy aimed at optimizing travel time and reliability for different user classes should consider travel time correlations between toll segments and the adjacent no-toll segments if enumerating paths is practically infeasible.
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Gupta, Samarth, Ravi Seshadri, Bilge Atasoy, A. Arun Prakash, Francisco Pereira, Gary Tan, and Moshe Ben-Akiva. "Real-Time Predictive Control Strategy Optimization." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 3 (February 24, 2020): 1–11. http://dx.doi.org/10.1177/0361198120907903.
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Urban traffic congestion has led to an increasing emphasis on management measures for more efficient utilization of existing infrastructure. In this context, this paper proposes a novel framework that integrates real-time optimization of control strategies (tolls, ramp metering rates, etc.) with the generation of traffic guidance information using predicted network states for dynamic traffic assignment systems. The efficacy of the framework is demonstrated through a fixed demand dynamic toll optimization problem, which is formulated as a non-linear program to minimize predicted network travel times. A scalable efficient genetic algorithm that exploits parallel computing is applied to solve this problem. Experiments using a closed-loop approach are conducted on a large-scale road network in Singapore to investigate the performance of the proposed methodology. The results indicate significant improvements in network-wide travel time of up to 9% with real-time computational performance.
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Chatterjee, Arun, P. Murali Reddy, Mohan M. Venigalla, and Terry L. Miller. "Operating Mode Fractions on Urban Roads Derived by Traffic Assignment." Transportation Research Record: Journal of the Transportation Research Board 1520, no. 1 (January 1996): 97–103. http://dx.doi.org/10.1177/0361198196152000112.
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The federal test procedure for vehicle emissions measurement treats the first 505 sec of engine operation as the transient mode. Using this definition as the basis, a special technique was developed and used to trace the elapsed time of vehicles from trip origins during the traffic assignment of zone-to-zone trips on a highway network and to determine the proportions of transient and stabilized operating modes on every link of the network. The travel models of the Sacramento (California) urban area were used to apply this technique and derive operating mode fractions for this urban area. The data from the Nationwide Personal Transportation Survey were used to distinguish between cold transient and hot transient modes. The operating mode fractions were stratified by functional class of roadways and the location within the urban area. The time of day of travel also was used for further stratification. The results show wide variations in the operating mode fractions among the different categories of roadway, location, and time of day.
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Dial, Robert B. "Bicriterion Traffic Equilibrium: T2 Model, Algorithm, and Software Overview." Transportation Research Record: Journal of the Transportation Research Board 1725, no. 1 (January 2000): 54–62. http://dx.doi.org/10.3141/1725-08.
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T2 is a rational and rigorous bicriterion traffic assignment model developed around a stochastic linear generalized cost model, which forecasts path choices and consequent equilibrium link volumes of trip makers with diverse values of time. Its path choice criterion minimizes a disutility equaling a stochastic sum of two link attributes—usually time and cost— both of which may be flow dependent. In contrast with the classical traffic assignment model, T2 permits different travelers to respond differently (as a result of factors such as travel time, tolls, congestion, taste, etc.) to the same path choices. This research provides an overview of T2’s mathematical model, solution algorithm, and implementing software.
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Ji, Xiangfeng, Xuegang (Jeff) Ban, Jian Zhang, and Bin Ran. "Subjective-utility travel time budget modeling in the stochastic traffic network assignment." Journal of Intelligent Transportation Systems 21, no. 6 (June 6, 2017): 439–51. http://dx.doi.org/10.1080/15472450.2017.1326116.
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Wei, Bangyang, and Daniel(Jian) Sun. "A Two-Layer Network Dynamic Congestion Pricing Based on Macroscopic Fundamental Diagram." Journal of Advanced Transportation 2018 (August 1, 2018): 1–11. http://dx.doi.org/10.1155/2018/8616120.
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Dynamic congestion pricing has attracted increasing attentions during the recent years. Nevertheless, limited research has been conducted to address the dynamic tolling scheme at the network level, such as to cooperatively manage two alternative networks with heterogeneous properties, e.g., the two-layer network consisting of both expressway and arterial network in the urban areas. Recently, the macroscopic fundamental diagram (MFD) developed by both field experiments and simulation tests illustrates a unimodal low-scatter relationship between the mean flow and density network widely, providing the network traffic state is roughly homogeneous. It reveals traffic flow properties at an aggregated level and sheds light on dynamic traffic management of a large network. This paper proposes a bilevel programming toll model, incorporating MFD to solve the unbalanced flow distribution problem within the two-layer transportation networks. The upper level model aims at minimizing the total travel time, while the lower level focuses on the MFD-based traffic assignment, which extends the link-based traffic assignment to network wide level. Genetic algorithm (GA) and the method of successive average were adopted for solving the proposed model, on which an online experimental platform was established using VISSIM, MATLAB, and Visual Studio software packages. The results of numerical studies demonstrate that the total travel time is decreased by imposing the dynamic toll, while the total travel time savings significantly outweigh the toll paid. Consequently, the proposed dynamic toll scheme is believed to be effective from both traffic and economic points of view.
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Yu, Xiao Jun. "Bounding the Inefficiency of Multiclass Stochastic Traffic Equilibrium under Congestion Pricing." Advanced Materials Research 219-220 (March 2011): 932–36. http://dx.doi.org/10.4028/www.scientific.net/amr.219-220.932.
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There are often some efficiency losses between user equilibrium (UE) and system optimization (SO). This paper investigates the efficiency losses of multiclass stochastic user equilibrium (SUE) traffic assignment under congestioin pricing against SO. Serveral bounds of the efficiency loss for this problem when the tolls are considered as part of the system cost are derived, with the time-based criterion and the monetary-based criterion, respectively. It is shown that the upper bound of efficiency loss caused by the time-based SUE depends on the type of link travel time function, the network complexity, the travel demand, and the degree of users’ perception error on travel cost. The upper bound of efficiency loss caused by the monetary-based SUE depends on the value of time (VOT) of user classes besides the aforementioned factors.
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Banks, James H. "Metering Ramps to Divert Traffic around Bottlenecks." Transportation Research Record: Journal of the Transportation Research Board 1925, no. 1 (January 2005): 12–19. http://dx.doi.org/10.1177/0361198105192500102.
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Three elementary cases, with ramp metering used to reduce delay by diverting traffic around bottlenecks, are analyzed. In these cases ( a) travel times on an alternate route bypassing the bottleneck are insensitive to flow on the alternate route, ( b) the alternate route is undersaturated but travel times are sensitive to flow, and ( c) the alternate route is oversaturated. Travel time equilibria and traffic assignments are relatively straightforward in all cases provided that equilibria in Cases b and c are assumed to be approximate and traffic assignments are based on drivers’ expectations about traffic conditions prevailing at particular times of day. A metering strategy intended to minimize delay is proposed. This strategy is expressed in terms of the order in which metering is initiated at different ramps and is similar to one previously proposed to maximize output to exits upstream of the bottleneck.
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Rousseau, Guy, and Tracy Clymer. "Travel Demand Modeling and Conformity Determination: Atlanta Regional Commission Case Study." Transportation Research Record: Journal of the Transportation Research Board 1817, no. 1 (January 2002): 172–76. http://dx.doi.org/10.3141/1817-22.
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The Atlanta Regional Commission (ARC) regional travel demand model is described as it relates to its link-based emissions postprocessor. In addition to conformity determination, an overview of other elements is given. The transit networks include the walk and highway access links. Trip generation addresses trip production, trip attraction, reconciliation of productions and attractions, and special adjustments made for Hartsfield Atlanta International Airport. Trip distribution includes the application of the composite impedance variable. In the mode choice model, home-based work uses a logit function, whereas nonwork uses information from the home-based work to estimate modal shares. Traffic assignment includes preparation of time-of-day assignments. The model assigns single-occupancy vehicles, high-occupancy vehicles, and trucks by using separate trip tables. The procedures can accept or prohibit each of the three types of vehicles from each highway lane. Feedback between the land use model and the traffic model is accounted for via composite impedances generated by the traffic model and is a primary input to the land use model DRAM/EMPAL. The land use model is based on census tract geography, whereas the travel demand model is based on traffic analysis zones that are subareas within census tracts. The ARC model has extended the state of the practice by using the log sum variable from mode choice as the impedance measure rather than the standard highway time. This change means that the model is sensitive not only to highway travel time but also to highway and transit costs.
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Liu, Henry X., Xuegang Ban, Bin Ran, and Pitu Mirchandani. "Analytical Dynamic Traffic Assignment Model with Probabilistic Travel Times and Perceptions." Transportation Research Record: Journal of the Transportation Research Board 1783, no. 1 (January 2002): 125–33. http://dx.doi.org/10.3141/1783-16.
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Cho, Joongmin, Young-Joo Lee, Seongkwan Mark Lee, Ki Han Song, and Wonho Suh. "Analysis of Macroscopic Traffic Network Impacted by Structural Damage to Bridges from Earthquakes." Applied Sciences 11, no. 7 (April 3, 2021): 3226. http://dx.doi.org/10.3390/app11073226.
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Highway systems play a key role in providing mobility to society, especially during emergency situations, including earthquakes. Bridges in highway systems are susceptible to damage from earthquakes, causing traffic capacity loss leading to a serious impact on surrounding areas. To better prepare for such scenarios, it is important to estimate capacity loss and traffic disruptions from earthquakes. For this purpose, a traffic-capacity-analysisbased methodology was developed to model the performance of a transportation network immediately following an earthquake using a macroscopic multi-level urban traffic planning simulation model EMME4. This method employs the second order linear approximation (SOLA) traffic assignment and calculates total system travel time for various capacity loss scenarios due to bridge damage from earthquakes. It has been applied to Pohang City in Korea to evaluate the performance of traffic networks in various situations. The results indicate a significant increase in travel time and a decrease in travel speed as the intensity of an earthquake increases. However, the impact on traffic volume varies depending on the bridges. It is assumed that the location of the bridges and traffic routing patterns might be the main reason. The results are expected to help estimate the impact on transportation networks when earthquakes cause traffic capacity loss on bridges.
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Ramazani, H., Y. Shafahi, and S. E. Seyedabrishami. "A fuzzy traffic assignment algorithm based on driver perceived travel time of network links." Scientia Iranica 18, no. 2 (April 2011): 190–97. http://dx.doi.org/10.1016/j.scient.2011.03.028.
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Janson, Bruce N. "Modeling Network Travel Time Impact of Freeway Ramp Metering." Transportation Research Record: Journal of the Transportation Research Board 1645, no. 1 (January 1998): 152–59. http://dx.doi.org/10.3141/1645-19.
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Whether freeway ramp metering can reduce total travel time in a corridor of several alternative routes depends on changes in route volumes and travel times. Ramp metering effectiveness and ramp metering algorithms have been evaluated mainly on the basis of improved freeway operations. Most studies have not evaluated the impact on alternative routes because of the complexity of the problem (e.g., which routes and what lengths of routes should be studied). An analysis of ramp metering impact in a network corridor is presented, first for simple steady-state cases and then for more complex cases involving time-varying demand, upstream and downstream queueing on freeway and alternative routes, and variable ramp metering rates based on freeway conditions. Time-varying examples are solved with a dynamic traffic assignment model called DYMOD. The analysis shows that ramp metering yields total travel time savings if (a) downstream freeway capacities are sufficiently restrictive, and (b) competitive alternative routes exist to accommodate the diverted traffic. The conditions under which ramp metering can be effective is illustrated by an examination of these simplified cases, and a useful modeling approach to analyzing systemwide impact in a larger corridor is demonstrated.
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Joksimovic, Dusica, Michiel C. J. Bliemer, and Piet H. L. Bovy. "Optimal Toll Design Problem in Dynamic Traffic Networks with Joint Route and Departure Time Choice." Transportation Research Record: Journal of the Transportation Research Board 1923, no. 1 (January 2005): 61–72. http://dx.doi.org/10.1177/0361198105192300107.
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Road pricing is one of the market-based traffic control measures that can influence travel behavior to alleviate congestion on roads. This paper addresses the effects of uniform (constant, fixed) and time-varying (step) tolls on the travel behavior of users on the road network. The problem of determining optimal prices in a dynamic traffic network is considered by applying second-best tolling scenarios imposing tolls only to a subset of links on the network and considering elastic demand. The optimal toll design problem is formulated as a bilevel optimization problem with the road authority (on the upper level) setting the tolls and the travelers (on the lower level) who respond by changing their travel decisions (route and departure time choice). To formulate the optimal toll design problem, the so-called mathematical program with equilibrium constraints (MPEC) formulation was used, considering the dynamic nature of traffic flows on the one hand and dynamic pricing on the other. Until now, the MPEC formulation has been applied in static cases only. The model structure comprises three interrelated levels: (a) dynamic network loading, (b) route choice and departure time choice, and (c) road pricing level. For solving the optimal toll design problem in dynamic networks, a simple search algorithm is used to determine the optimal toll pattern leading to optimization of the objective function of the road authority subject to dynamic traffic assignment constraints. Nevertheless, uniform and time-varying pricing is analyzed, and a small hypothetical network is considered.
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Durlin, Thomas, and Vincent Henn. "Dynamic Network Loading Model with Explicit Traffic Wave Tracking." Transportation Research Record: Journal of the Transportation Research Board 2085, no. 1 (January 2008): 1–11. http://dx.doi.org/10.3141/2085-01.
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A dynamic network loading (DNL) model is presented: it can be used both for dynamic traffic assignment (DTA) and for an accurate description of traffic. The proposed DNL model is composed of (a) the link model based on the Lighthill-Whitham-Richards macroscopic first-order model solved with the wave-tracking method, (b) a new intersection model that generalizes the Daganzo macroscopic merge model to complex intersections, and (c) a traffic signal model that represents the mean effects of stage alternation on traffic in terms of delays and of capacity restrictions. Both the wave-tracking method and the traffic signal model are applied in a network context for the first time. The model can be consistently solved with various precision scales: low-precision scales to quickly provide a good estimation of travel times on the network for DTA purposes, and high-precision scales for accurate descriptions of traffic with all the desired modeling details.
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Nigro, Marialisa, Akmal Abdelfatah, Ernesto Cipriani, Chiara Colombaroni, Gaetano Fusco, and Andrea Gemma. "Dynamic O-D Demand Estimation: Application of SPSA AD-PI Method in Conjunction with Different Assignment Strategies." Journal of Advanced Transportation 2018 (2018): 1–18. http://dx.doi.org/10.1155/2018/2085625.
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This paper examines the impact of applying dynamic traffic assignment (DTA) and quasi-dynamic traffic assignment (QDTA) models, which apply different route choice approaches (shortest paths based on current travel times, User Equilibrium: UE, and system optimum: SO), on the accuracy of the solution of the offline dynamic demand estimation problem. The evaluation scheme is based on the adoption of a bilevel approach, where the upper level consists of the adjustment of a starting demand using traffic measures and the lower level of the solution of the traffic network assignment problem. The SPSA AD-PI (Simultaneous Perturbation Stochastic Approximation Asymmetric Design Polynomial Interpolation) is adopted as a solution algorithm. A comparative analysis is conducted on a test network and the results highlight the importance of route choice model and information for the stability and the quality of the offline dynamic demand estimations.
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Marker, John T., and Konstadinos G. Goulias. "Truck Traffic Prediction Using Quick Response Freight Model Under Different Degrees of Geographic Resolution: Geographic Information System Application in Pennsylvania." Transportation Research Record: Journal of the Transportation Research Board 1625, no. 1 (January 1998): 118–23. http://dx.doi.org/10.3141/1625-15.
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The new Quick Response Freight Manual (QRFM) was used to model truck traffic in Centre County, Pennsylvania, using Geographic Information System software. The QRFM methodology of truck traffic estimation follows the three-step process of trip generation, trip distribution, and traffic assignment. Trip generation was estimated by four classes of business employment and number of households and was aggregated to traffic analysis zones. Trip distribution employed a doubly constrained gravity model with travel time–based friction factors. User equilibrium was used for traffic assignment. Model calibration was performed by comaparing total vehicle miles traveled from model output with observed data. A comparison is made in truck traffic estimation between two models when the model resolution is changed, that is, when the size and number of traffic analysis zones (TAZs) is changed. One model uses census tracts and the other uses census blocks and block groups as TAZs. Both models use the same network, which includes all major highways and most local roads in the urbanized region of the county. Results from the two aggregation scales of analysis were compared with each other by using traffic counts in the Roadway Management System of Pennsylvania as reference data. The estimated truck traffic link volumes favor the use of the more disaggregate TAZ scheme, which is based on blocks and block groups.
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Bliemer, Michiel C. J. "Quasi-Variational Inequality Approach to Multi-User-Class Dynamic Traffic Assignment." Transportation Research Record: Journal of the Transportation Research Board 1710, no. 1 (January 2000): 11–19. http://dx.doi.org/10.3141/1710-02.
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The extension of a single-user-class macroscopic dynamic traffic assignment model to include multiple user classes is considered. The distinction between user classes is based on vehicle characteristics. Cars and trucks are two typical classes. To deal with various asymmetries that may occur, such as intra-user-class interaction and spatial and temporal asymmetries, the model is specified as a quasi-variational inequality problem. A nested modified projection method is successfully adopted to solve the assignment problem. The solution of the problem depends heavily on the choice of some very important input: the multiclass link travel time functions. Under mild restrictions there exists a solution, which need not be unique. A case study illustrates the model.
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Meng, Qiang, Wei Xu, and Hai Yang. "Trial-and-Error Procedure for Implementing a Road-Pricing Scheme." Transportation Research Record: Journal of the Transportation Research Board 1923, no. 1 (January 2005): 103–9. http://dx.doi.org/10.1177/0361198105192300111.
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This paper deals with a road-pricing scheme that aims at alleviating congestion phenomena or air and noise pollution in some areas of a transportation network in such a way that the volumes of traffic flow on entry links to these areas do not exceed their respective predetermined thresholds by levying appropriate tolls at these links. This paper begins to show that the road-pricing scheme is equivalent to a problem that determines optimal Lagrangian multipliers for a user equilibrium traffic assignment problem with link capacity constraints. It then proceeds to devise a novel trial-and-error procedure requiring observed traffic flows at the entry links only, to identify a solution for the road-pricing scheme when link travel time functions, origin–destination demand functions, and users’ value of travel time are unknown. The procedure is as follows. A trial on a set of given tolls is conducted, and then the resultant link flows are observed. According to these observed traffic flows, a new set of tolls for the next trial is adjusted by executing a simple projection operation. The trial-and-error procedure is, in fact, a variation of a gradient projection method for dual formulation of the traffic assignment problem, and its convergence can be guaranteed under mild conditions. Accordingly, a conjecture for the convergence of trial-and-error implementation of the congestion pricing proposed by economists is rigorously proved. Furthermore, the iterative procedure presented in this paper in practice can facilitate the estimation of such tolls by land transport authorities.
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Dell'Orco, Mauro, Ozgur Baskan, and Mario Marinelli. "A Harmony Search Algorithm approach for optimizing traffic signal timings." PROMET - Traffic&Transportation 25, no. 4 (July 19, 2013): 349–58. http://dx.doi.org/10.7307/ptt.v25i4.979.
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In this study, a bi-level formulation is presented for solving the Equilibrium Network Design Problem (ENDP). The optimisation of the signal timing has been carried out at the upper-level using the Harmony Search Algorithm (HSA), whilst the traffic assignment has been carried out through the Path Flow Estimator (PFE) at the lower level. The results of HSA have been first compared with those obtained using the Genetic Algorithm, and the Hill Climbing on a two-junction network for a fixed set of link flows. Secondly, the HSA with PFE has been applied to the medium-sized network to show the applicability of the proposed algorithm in solving the ENDP. Additionally, in order to test the sensitivity of perceived travel time error, we have used the HSA with PFE with various level of perceived travel time. The results showed that the proposed method is quite simple and efficient in solving the ENDP.
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Yang, Fan, Henry X. Liu, Rachel R. He, Xuegang Ban, and Bin Ran. "Bilevel Formulation for Optimal Traffic-Information Dissemination." Transportation Research Record: Journal of the Transportation Research Board 1836, no. 1 (January 2003): 21–28. http://dx.doi.org/10.3141/1836-04.
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With the fast-growing telematics market and maturing traffic-information services, telematics devices provide a feasible means with which to manage traffic more efficiently. The provision of traffic information to travelers usually involves different parties that have distinctive objectives: travelers are concerned with benefits of travel-time savings at an affordable service charge, private information service providers (ISPs) seek to provide marketable information services from which they can derive a profit, and traffic management centers (TMCs) have the responsibility to maintain and improve system performance, especially to minimize the total system travel time. How transportation system managers can analyze the trade-offs among these objectives and adjust this new traffic-information flow diagram to improve system performance remains an open question. The trade-offs needed among the conflicting multiple objectives of different parties are studied, and traffic system performance is analyzed. The complex traffic network is formulated as a bilevel program. The upper level can be formulated by using various objective functions, such as the objectives for ISP and TMC. The lower level is a multiclass dynamic traffic-assignment model, which determines dynamic traffic flows in the network by considering the information dissemination strategies provided by the upper-level model. Numerical results of a small network are provided to illustrate the behavior of this model, and they prove that when there is congestion in the dynamic transportation network, appropriate subscribed rates benefit both all travelers and system performance, while the ISPs’ information influences little without congestion in the transportation network.
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Kamga, Camille N., Kyriacos C. Mouskos, and Robert E. Paaswell. "A methodology to estimate travel time using dynamic traffic assignment (DTA) under incident conditions." Transportation Research Part C: Emerging Technologies 19, no. 6 (December 2011): 1215–24. http://dx.doi.org/10.1016/j.trc.2011.02.004.
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Zhou, Weiyi, Mofeng Yang, Minha Lee, and Lei Zhang. "Q-Learning-Based Coordinated Variable Speed Limit and Hard Shoulder Running Control Strategy to Reduce Travel Time at Freeway Corridor." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 11 (September 16, 2020): 915–25. http://dx.doi.org/10.1177/0361198120949875.
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To increase traffic mobility and safety, several types of active traffic management (ATM) strategies, such as variable speed limit (VSL), ramp metering, dynamic message signs, and hard shoulder running (HSR), are adopted in many countries. While all kinds of ATM strategies show promise in releasing traffic congestion, many studies indicate that stand-alone strategies have very limited capability. To remedy the defects of stand-alone strategies, cooperative ATM strategies have caught researchers’ attention and different combinations have been studied. In this paper, a coordinated VSL and HSR control strategy based on a reinforcement learning technique—Q-learning—is proposed. The proposed control strategy bridges up a direct connection between the traffic flow data and the ATM control strategies via intensive self-learning processes, thus reducing the need for human knowledge. A typical congested interstate highway, I-270 in Maryland, United States, was selected as the study area to evaluate the proposed strategy. A dynamic traffic assignment simulation model was introduced to calibrate the network with real-world data and was used to evaluate the regional impact of the proposed algorithm. Simulation results indicated that the proposed coordinated control could reduce corridor travel time by up to 27%. The performance of various control strategies were also compared. The results suggested that the proposed strategy outperformed the stand-alone control strategies and the traditional feedback-based VSL strategy in mitigating congestion and reducing travel time on the freeway corridor.
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Yang, Da, Xinpeng Zhao, Yuting Chen, Xi Zhang, and Chongshuang Chen. "Study on the Day-Based Work Zone Scheduling Problem in Urban Road Networks Based on the Day-to-Day Traffic Assignment Model." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 16 (June 11, 2018): 14–22. http://dx.doi.org/10.1177/0361198118757982.
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Many work zones exist in the urban road network and have a great negative impact on city traffic. Finding the optimal work zone schedule can minimize the negative impact of work zones on traffic. This paper focuses on the day-based work zone scheduling problem in the urban network. Existing studies on the day-based work zone scheduling problem do not consider the progression of day-to-day traffic from a non-equilibrium state to an equilibrium state during the construction period. For the first time, this paper proposes a model for day-based work zone scheduling by introducing a day-to-day traffic assignment model, in which the target of the optimization problem is minimizing the increase in travel cost caused by work zones. Numerical examples are presented to explore the variations of the optimal construction sequence for different work durations, crew numbers, and model parameter values. Some new findings are obtained in the paper. When the construction duration of each work zone is relatively short (for example, less than 20 days), the optimal scheduling will obviously change with the work duration; when all of the construction durations increase to a threshold (for example, 60 days), the optimal construction sequence will no longer change. An optimal crew number exists that can minimize the increment of travel cost caused by work zones. During the construction period, the total travel cost in the network can be decreased by guiding travelers to change their original travel habits.
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Das, Aathira K., and Bhargava Rama Chilukuri. "Link Cost Function and Link Capacity for Mixed Traffic Networks." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 9 (June 24, 2020): 38–50. http://dx.doi.org/10.1177/0361198120926454.
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Link cost function and link capacity are critical factors in traffic assignment modeling. Popular link cost functions like the Bureau of Public Roads (BPR) function have well-known drawbacks and are not suitable for mixed traffic conditions where a variety of vehicle classes use the road in a non-lane-based movement. Similarly, capacity is generally considered as a constant value. However, in mixed traffic conditions, capacity is not constant, but a function of vehicle class composition. Toward addressing these issues, this paper proposes a link cost function in relation to link travel time and link capacity in relation to vehicular traffic flow for mixed traffic conditions. The functions are developed based on the kinematic wave model, which is popularly used for estimating traffic dynamics on the roads. The developed link cost function and link capacity use field measurable parameters that incorporate mixed traffic features. The functions are validated against empirical data obtained from 12 signal cycles from two different signalized intersections in Chennai, India, representing different scenarios of mixed traffic, and it was found that the results match well with the empirical data.
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Abdelghaffar, Hossam M., and Hesham A. Rakha. "A Novel Decentralized Game-Theoretic Adaptive Traffic Signal Controller: Large-Scale Testing." Sensors 19, no. 10 (May 17, 2019): 2282. http://dx.doi.org/10.3390/s19102282.
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This paper presents a novel de-centralized flexible phasing scheme, cycle-free, adaptive traffic signal controller using a Nash bargaining game-theoretic framework. The Nash bargaining algorithm optimizes the traffic signal timings at each signalized intersection by modeling each phase as a player in a game, where players cooperate to reach a mutually agreeable outcome. The controller is implemented and tested in the INTEGRATION microscopic traffic assignment and simulation software, comparing its performance to that of a traditional decentralized adaptive cycle length and phase split traffic signal controller and a centralized fully-coordinated adaptive phase split, cycle length, and offset optimization controller. The comparisons are conducted in the town of Blacksburg, Virginia (38 traffic signalized intersections) and in downtown Los Angeles, California (457 signalized intersections). The results for the downtown Blacksburg evaluation show significant network-wide efficiency improvements. Specifically, there is a 23.6 % reduction in travel time, a 37.6 % reduction in queue lengths, and a 10.4 % reduction in CO 2 emissions relative to traditional adaptive traffic signal controllers. In addition, the testing on the downtown Los Angeles network produces a 35.1 % reduction in travel time on the intersection approaches, a 54.7 % reduction in queue lengths, and a 10 % reduction in CO 2 emissions compared to traditional adaptive traffic signal controllers. The results demonstrate significant potential benefits of using the proposed controller over other state-of-the-art centralized and de-centralized adaptive traffic signal controllers on large-scale networks both during uncongested and congested conditions.
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Chen, Deqi, Xuedong Yan, Feng Liu, Xiaobing Liu, Liwei Wang, and Jiechao Zhang. "Evaluating and Diagnosing Road Intersection Operation Performance Using Floating Car Data." Sensors 19, no. 10 (May 15, 2019): 2256. http://dx.doi.org/10.3390/s19102256.
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Urban road intersections play an important role in deciding the total travel time and the overall travel efficiency. In this paper, an innovative traffic grid model has been proposed, which evaluates and diagnoses the traffic status and the time delay at intersections across whole urban road networks. This method is grounded on a massive amount of floating car data sampled at a rate of 3 s, and it is composed of three major parts. (1) A grid model is built to transform intersections into discrete cells, and the floating car data are matched to the grids through a simple assignment process. (2) Based on the grid model, a set of key traffic parameters (e.g., the total time delay of all the directions of the intersection and the average speed of each direction) is derived. (3) Using these parameters, intersections are evaluated and the ones with the longest traffic delays are identified. The obtained intersections are further examined in terms of the traffic flow ratio and the green time ratio as well as the difference between these two variables. Using the central area of Beijing as the case study, the potential and feasibility of the proposed method are demonstrated and the unreasonable signal timing phases are detected. The developed method can be easily transferred to other cities, making it a useful and practical tool for traffic managers to evaluate and diagnose urban signal intersections as well as to design optimal measures for reducing traffic delay and increase operation efficiency at the intersections.
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Tang, Qinrui, Huijun Liu, and Bernhard Friedrich. "Lane-based signal optimization with left turn prohibition in urban road networks." Canadian Journal of Civil Engineering 46, no. 2 (February 2019): 73–80. http://dx.doi.org/10.1139/cjce-2018-0079.
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Left turns may generate efficiency problems, which can be solved by appropriately prohibiting left turns. The goal of this paper is to propose a method for purpose of minimizing total travel times in urban road networks by prohibiting left turns. With left turn prohibition, the signal timing plan is optimized with the lane-based method because the method can adequately handle both signal timing optimization and lane assignment. The total travel time is calculated with link flows and link travel time being estimated with signal settings. As illustrated by numerical examples, prohibiting left turns reduces the total travel time of car traffic in road networks. As the left turn prohibition results can handle the randomness in the network, these results provide potential implications for congestion management.
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Li, Manman, Jian Lu, Jiahui Sun, and Qiang Tu. "Day-to-Day Evolution of Traffic Flow with Dynamic Rerouting in Degradable Transport Network." Journal of Advanced Transportation 2019 (December 23, 2019): 1–12. http://dx.doi.org/10.1155/2019/1524178.
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Random events like accidents and vehicle breakdown, degrade link capacities and lead to uncertain travel environment. And whether travelers adjust route or not depends on the utility difference (dynamic rerouting behavior) rather than a constant. Considering travelers’ risk-taking behavior in uncertain environment and dynamic rerouting behavior, a new day-to-day traffic assignment model is established. In the proposed model, an exponential-smoothing filter is adopted to describe travelers’ learning for uncertain travel time. The cumulative prospect theory is used to reflect route utility and its reference point is adaptive and set to be the minimal travel time under a certain on-time arrival probability. Rerouting probability is determined by the difference between expected utility and perceived utility of previously chosen route. Rerouting travelers choose new routes in a logit model while travelers who do not choose to reroute travel on their previous routes again. The proposed model’s several mathematical properties, including fixed point existence, uniqueness, and stability condition, are investigated through theoretical analyses. Numerical experiments are also conducted to validate the proposed heuristic stability condition, show the effects of four main parameters on dynamic natures of the system, and investigate the differences of the system based on expected utility theory and cumulative prospect theory and with static rerouting behavior and dynamic rerouting behavior.
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Dowling, Richard G., Rupinder Singh, and Willis Wei-Kuo Cheng. "Accuracy and Performance of Improved Speed-Flow Curves." Transportation Research Record: Journal of the Transportation Research Board 1646, no. 1 (January 1998): 9–17. http://dx.doi.org/10.3141/1646-02.
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Skabardonis and Dowling recommended updated Bureau of Public Road speed-flow curves for freeways and signalized arterials to improve the accuracy of speed estimates used in transportation demand models. These updated curves generally involved the use of higher power functions that show relatively little sensitivity to volume changes until demand exceeds capacity, when the predicted speed drops abruptly to a very low value. Skabardonis and Dowling demonstrated that the curves provide improved estimates of vehicle speeds under both uncongested and queueing conditions; however, they did not investigate the impact of these curves on the performance of travel demand models. Practitioners have been concerned about the impacts of such abrupt speed-flow curves on the performance of their travel demand models. Spiess has stated that higher power functions are more difficult computationally for computers to evaluate and that more abrupt speed-flow curves adversely affect the rate of convergence to equilibrium solutions in the traffic assignment process. In this paper the impact of the Skabardonis and Dowling updated speed-flow curves on the performance of selected travel demand models is investigated. The updated speed-flow curves were found to significantly increase travel demand model run times. However, it is demonstrated that an alternative speed-flow equation developed by Akçelik has similar or better accuracy and provides much superior convergence properties during the traffic assignment process. The Akçelik curve significantly reduced travel demand model run times.
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Baskan, Ozgur. "A Multiobjective Bilevel Programming Model for Environmentally Friendly Traffic Signal Timings." Advances in Civil Engineering 2019 (October 20, 2019): 1–13. http://dx.doi.org/10.1155/2019/1638618.
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Rapid urbanization and mobility needs of road users increase traffic congestion and delay on urban road networks. Thus, local authorities aim to reduce users’ total travel time through providing a balance between traffic volume and capacity. To do this, they optimize traffic signal timings, which is one of the most preferred methods, and thus they can increase the reserve capacity of a road network. However, more travel demand along with more reserve capacity leads to vehicle emissions problem which has become quite dangerous for road users, especially in developing countries. Therefore, this study presents a multiobjective bilevel programming model which considers both the maximization of reserve capacity of a road network and the minimization of vehicle emissions by aiming to achieve environmentally friendly signal timings. At the upper level, Pareto-optimal solutions of the proposed multiobjective model are found based on differential evolution algorithm framework by using the weighted sum method. Stochastic traffic assignment problem is presented at the lower level to evaluate the users’ reactions. Two signalized road networks are chosen to show the effectiveness of the proposed model. The first one is a small network consisting two signalized intersections that are used to show the effect of the weighting factor on the proposed multiobjective model. The other road network with 96 O-D pairs and 9 signalized intersections is chosen as the second numerical application to investigate the performance of the proposed model on relatively large road networks. It is believed that results of this study may provide useful insights to local authorities who are responsible for regulating traffic operations with environmental awareness at the same time.
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Liang, Xiao, Gonçalo Homem de Almeida Correia, and Bart van Arem. "Applying a Model for Trip Assignment and Dynamic Routing of Automated Taxis with Congestion: System Performance in the City of Delft, The Netherlands." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 8 (May 4, 2018): 588–98. http://dx.doi.org/10.1177/0361198118758048.
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This paper proposes a method of assigning trips to automated taxis (ATs) and designing the routes of those vehicles in an urban road network, and also considering the traffic congestion caused by this dynamic responsive service. The system is envisioned to provide a seamless door-to-door service within a city area for all passenger origins and destinations. An integer programming model is proposed to define the routing of the vehicles according to a profit maximization function, depending on the dynamic travel times, which varies with the ATs’ flow. This will be especially important when the number of automated vehicles (AVs) circulating on the roads is high enough that their routing will cause delays. This system should be able to serve not only the reserved travel requests, but also some real-time requests. A rolling horizon scheme is used to divide one day into several periods in which both the real-time and the booked demand will be considered together. The model was applied to the real size case study city of Delft, the Netherlands. The results allow assessing of the impact of the ATs movements on traffic congestion and the profitability of the system. From this case-study, it is possible to conclude that taking into account the effect of the vehicle flows on travel time leads to changes in the system profit, the satisfied percentage and the driving distance of the vehicles, which highlights the importance of this type of model in the assessment of the operational effects of ATs in the future.
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Ameli, Mostafa, Jean-Patrick Lebacque, and Ludovic Leclercq. "Computational Methods for Calculating Multimodal Multiclass Traffic Network Equilibrium: Simulation Benchmark on a Large-Scale Test Case." Journal of Advanced Transportation 2021 (February 18, 2021): 1–17. http://dx.doi.org/10.1155/2021/8815653.
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This study reviews existing computational methods to calculate simulation-based dynamic network equilibrium. We consider a trip-based multimodal approach for the dynamic network loading. Mode and path choices are carried out at the same level; therefore, travel times depend on the travel path and the mode attributes of travelers. This study develops a multiclass model with several parameters per class. Two different categories of algorithms (heuristic and metaheuristic) are considered in order to solve the discrete dynamic traffic assignment (DTA) problem. Finally, we analyze the equilibrium in a large-scale multimodal DTA test case (Lyon 6th + Villeurbanne) in order to investigate the performance of different optimization approaches to solve trip-based DTA. The results show that, in a multimodal and heterogeneous setting, the metaheuristic methods provide better solutions than the heuristic methods in terms of optimality and computation time. These improvements are even more significant than in a homogeneous setting.
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Chakraborty, Shantanu, David Rey, Emily Moylan, and S. Travis Waller. "Link Transmission Model-Based Linear Programming Formulation for Network Design." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 48 (June 4, 2018): 139–47. http://dx.doi.org/10.1177/0361198118774753.
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This article presents a linear programming formulation to solve the network design problem using the link transmission model (LTM) as the underlying traffic flow model. The original LTM was adapted by incorporating link-sending and receiving flows using linear inequalities. Furthermore, route choice was relaxed, and transfer flow variables were used to model vehicles’ routing decisions within the network. The objective function of the linear program aimed to minimize the total difference between the cumulative vehicle numbers (CVN) at the upstream and at the downstream boundaries of each link subject to flow-conservation and budget constraints. CVN were represented using transfer flows from connected links. The resulting formulation is a linear program that represents a dynamic system optimum traffic flow pattern, embedding the LTM’s network loading procedure. In contrast to the single-destination system optimum dynamic traffic assignment, based on the cell transmission model, the proposed formulation requires considerably fewer decision variables, thus potentially providing a more scalable approach. The proposed formulation was implemented on an example network to illustrate the behavior of the model, and was compared with the cell-based formulation. We show that the model describes free-flow and congested traffic flow states accurately in terms of shock-wave propagation, queuing of vehicles, and optimal total system travel time.
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Zhang, Lei, Di Yang, Sepehr Ghader, Carlos Carrion, Chenfeng Xiong, Thomas F. Rossi, Martin Milkovits, Subrat Mahapatra, and Charles Barber. "An Integrated, Validated, and Applied Activity-Based Dynamic Traffic Assignment Model for the Baltimore-Washington Region." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 51 (September 18, 2018): 45–55. http://dx.doi.org/10.1177/0361198118796397.
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The paper discusses the integration process and initial applications of a new model for the Baltimore-Washington region that integrates an activity-based travel demand model (ABM) with a dynamic traffic assignment (DTA) model. Specifically, the integrated model includes InSITE, an ABM developed for the Baltimore Metropolitan Council, and DTALite, a mesoscopic DTA model. The integrated model simulates the complete daily activity choices of individuals residing in the model region, including long-term choices, such as workplace location; daily activity patterns, including joint household activities and school escorting; activity location choices; time-of-day choices; mode choices; and route choices. The paper describes the model development and integration approach, including modeling challenges, such as the need to maintain consistency between the ABM and DTA models in terms of temporal and spatial resolution, and practical implementation issues, such as managing model run time and ensuring sufficient convergence of the model. The integrated model results have been validated against observed daily traffic volumes and vehicle-miles traveled (VMT) for various functional classes. A land-use change scenario that analyzes the redevelopment of the Port Covington area in Baltimore is applied and compared with the baseline scenario. The validation and application results suggest that the integrated model outperforms a static assignment-based ABM and could capture behavioral changes at much finer time resolutions.
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Jiang, Chenming, Linjun Lu, Junliang He, and Caimao Tan. "A Two-Class Stochastic Network Equilibrium Model under Adverse Weather Conditions." Journal of Advanced Transportation 2020 (June 22, 2020): 1–14. http://dx.doi.org/10.1155/2020/2626084.
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Adverse weather condition is one of the inducements that lead to supply uncertainty of an urban transportation system, while travelers’ multiple route choice criteria are the nonignorable reason resulting in demand uncertainty. This paper proposes a novel stochastic traffic network equilibrium model considering impacts of adverse weather conditions on roadway capacity and route choice criteria of two-class mixed roadway travellers on demand modes, in which the two-class route choice criteria root in travelers’ different network information levels (NILs). The actual route travel time (ARTT) and perceived route travel time (PRTT) are considered as the route choice criteria of travelers with perfect information (TPI) and travelers with bounded information (TBI) under adverse weather conditions, respectively. We then formulate the user equilibrium (UE) traffic assignment model in a variational inequality problem and propose a solution algorithm. Numerical examples including a small triangle network and the Sioux Falls network are presented to testify the validity of the model and to clarify the inner mechanism of the two-class UE model under adverse weather conditions. Managerial implications and applications are also proposed based on our findings to improve the operation efficiency of urban roadway network under adverse weather conditions.
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Thomas, Jomy, Karthik K. Srinivasan, and Venkatachalam Thamizh Arasan. "VEHICLE CLASS WISE SPEED-VOLUME MODELS FOR HETEROGENEOUS TRAFFIC." TRANSPORT 27, no. 2 (June 26, 2012): 206–17. http://dx.doi.org/10.3846/16484142.2012.697442.
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Link performance functions commonly used for traffic assignment are often based on Volume Delay Functions (VDF) developed for homogeneous traffic. However, VDFs relating stream speed to the volume of traffic based on homogeneous lane-based traffic are not adequate for traffic assignment in developing countries due to the heterogeneous nature of traffic that is characterized by a mix of a wide range of vehicle classes with significant differences in static and dynamic characteristics and an imperfect lane discipline. Unfortunately, the use of VDFs similar to those for homogeneous traffic flow situations imposes strong restrictions considering two respects: 1) travel times at path and link levels can be obtained for an aggregated stream but not for individual vehicle types; 2) the effect of varying composition and asymmetric interactions is captured only to a limited extent by converting all vehicles into equivalent Passenger Car Unit (PCU). Hence, this paper proposes the development of VDFs specific to different classes of heterogeneous traffic, as it is more realistic in traffic assignment than the use of the same VDF for all classes of vehicles in a link. This study is aimed at developing models to determine the speed of each vehicle class as a function of flow and composition for six lane roads with heterogeneous traffic based on data obtained from Chennai city, India. Heterogeneity in this study mainly refers to differences in vehicle types (two-wheeler, car, bus, etc.) participating in mixed traffic. To develop multiple user class VDFs, the speed and flow of each vehicle class for a wide range of traffic flow conditions need to be recorded. As this is not possible using field measurements, an established micro-simulation model (HETEROSIM) is used for determining speeds for each vehicle type by systematically varying the volume and composition levels over a range of values that represent relevant and practical traffic conditions observed in six lane divided roads in Chennai city. The proposed delay functions are different from standard single user class VDFs in three key respects: first, they enable more realistic behaviour by modelling differences in class wise speeds at a given volume and composition level; second, they allow for capturing asymmetric interactions of different vehicle types on an average speed of a given vehicle class. Finally, speed-flow relationships for each class are also allowed to vary across volume levels which enable the representation of differential interactions at different levels of congestion in mixed traffic. The need for homogenizing the volumes in terms of a single class is obviated. The models significantly outperformed single class VDFs in both calibration and validation datasets. Further, the proposed models are used for analyzing heterogeneous traffic characteristics. Empirical evidence of asymmetric interactions and the impact of composition on classwise performance are also found and quantified. Finally, two applications of the proposed models are demonstrated for the level of service analysis of different classes and impact analysis of excluding some classes. The proposed models may have applications such as determining class wise road user costs and performance measures (e.g. emissions) that depend on class-specific speeds.
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Balakrishna, Ramachandran, Haris N. Koutsopoulos, Moshe Ben-Akiva, Bruno M. Fernandez Ruiz, and Manish Mehta. "Simulation-Based Evaluation of Advanced Traveler Information Systems." Transportation Research Record: Journal of the Transportation Research Board 1910, no. 1 (January 2005): 90–98. http://dx.doi.org/10.1177/0361198105191000111.
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Traveler information has the potential to reduce travel times and improve their reliability. Studies have verified that driver overreaction from the dissemination of information can be eliminated through prediction-based route guidance that uses short-term forecasts of network state. Critical off-line tests of advanced dynamic traffic assignment–based prediction systems have been limited, since the system being evaluated has also been used as the test bed. This paper outlines a detailed simulation-based laboratory for the objective and independent evaluation of advanced traveler information systems, a laboratory with the flexibility to analyze the impacts of various design parameters and modeling errors on the quality of the generated guidance. MITSIMLab, a system for the evaluation of advanced traffic management systems, is integrated with Dynamic Network Assignment for the Management of Information to Travelers (DynaMIT), a simulation-based decision support system designed to generate prediction-based route guidance. Evaluation criteria and requirements for the closed-loop integration of MITSIMLab and DynaMIT are discussed. Detailed case studies demonstrating the evaluation methodology and sensitivity of DynaMIT's guidance are presented.
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Yang, Hang, Zhongyu Wang, Yajie Zou, Bing Wu, and Xuesong Wang. "Level-Change Stackelberg Games Model for the Combined Traffic Assignment–Signal Control Equilibrium on Networks." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 48 (August 23, 2018): 24–35. http://dx.doi.org/10.1177/0361198118780706.
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Combined traffic assignment–signal control equilibrium is usually integrated into a non-cooperative games model between the network authority and road users. Unlike a pure Wardropian equilibrium, in reality there may be both competition and cooperation between authority and users. Authority has always been regarded as the upper level in classical bi-level formulations, but this placement may increase the difficulty of obtaining a global optimal solution between authority and users. This paper proposes a level-change Stackelberg (LC Stackelberg) model that embraces both authority–user and user–authority formulations. The model is calibrated by a model predictive control (MPC) controller. A route-choice probability model is used to estimate flow burden on two parallel routes. Meanwhile, the difference of route-choice probability between the two parallel paths is regarded as the level-change threshold. A generalized autoregressive conditional heteroscedasticity (GJR-GARCH) model is used as a triggering function in the MPC controller to fulfill the level-change procedure. A modified wavelet neural network algorithm is used to seek the global optimal solution. Cournot, Stackelberg, and Monopoly, combined with a fixed-time control policy based on the Webster method, were chosen as benchmarks in a numerical example to test model validity. The results show that the LC Stackelberg model obtains the minimum total travel time compared with other models. Furthermore, the level-change between authority and users could also decrease route choice probability on one specific path, indicating the model’s potential application in urban networks.
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Mao, Xinhua, Jibiao Zhou, Changwei Yuan, and Dan Liu. "Resilience-Based Optimization of Postdisaster Restoration Strategy for Road Networks." Journal of Advanced Transportation 2021 (February 12, 2021): 1–15. http://dx.doi.org/10.1155/2021/8871876.
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This work proposes a framework for the optimization of postdisaster road network restoration strategies from a perspective of resilience. The network performance is evaluated by the total system travel time (TSTT). After the implementation of a postdisaster restoration schedule, the network flows in a certain period of days are on a disequilibrium state; thus, a link-based day-to-day traffic assignment model is employed to compute TSTT and simulate the traffic evolution. Two indicators are developed to assess the road network resilience, i.e., the resilience of performance loss and the resilience of recovery rapidity. The former is calculated based on TSTT, and the latter is computed according to the restoration makespan. Then, we formulate the restoration optimization problem as a resilience-based bi-objective mixed integer programming model aiming to maximize the network resilience. Due to the NP-hardness of the model, a genetic algorithm is developed to solve the model. Finally, a case study is conducted to demonstrate the effectiveness of the proposed method. The effects of key parameters including the number of work crews, travelers’ sensitivity to travel time, availability of budget, and decision makers’ preference on the values of the two objectives are investigated as well.