Transportation Research Record: Journal of the Transportation Research Board, 2014
The aim of this study was to solve the minimum path travel time budget (MPTTB) problem, in which ... more The aim of this study was to solve the minimum path travel time budget (MPTTB) problem, in which the travel time budget was the reliability index. This index was defined as the sum of the mean path travel time and the scaled standard deviation, which included the covariance matrix to consider correlation. Two existing solution methods in the literature, the outer approximation algorithm and Monte Carlo simulation method, were applied to solve the MPTTB problem. The former method approximated the hard nonlinear constraint of the MPTTB problem by a series of linear cuts generated iteratively and repeatedly solved a mixed integer program. The latter method, which was a simulation-based method, included two stages. The first stage founded a set of candidate paths, and the second stage generated the distribution of travel times for the existing paths in the candidate set. The numerical results for these two solution methods were conducted on the Chicago sketch network, and results showed that the methods found comparable solutions though they have respective advantages and drawbacks. Although the outer approximation algorithm demonstrated promising performance, it still relied on repeatedly solving a mixed integer program (subproblem) with a commercial solver, which could be a challenging task in its own right.
Transportation Research Record: Journal of the Transportation Research Board, 2014
This paper evaluates measurement methods for traffic flow variables taken at the network level. G... more This paper evaluates measurement methods for traffic flow variables taken at the network level. Generalized Edie's definitions of fundamental traffic flow variables along highways are extended for considering vehicles traveling in networks. These definitions are used to characterize traffic flow in networks and form the basis for estimating relationships among network density, flow, and speed in the form of a network fundamental diagram. The method relies on three-dimensional vehicle trajectories to provide estimates of network flow, density, and speed. Such trajectories may be routinely obtained from particle-based microscopic and mesoscopic simulation models and are increasingly available from tracking devices on vehicles. Numerical results from the simulation of two networks, in Chicago, Illinois, and Salt Lake City, Utah, are presented to illustrate and validate the estimation methodology. As part of the verification process, the study confirms that the traffic flow fundamental identity (Q 5 K • V) holds at the network level only when networkwide traffic flow variables are defined consistently with Edie's definitions.
EURO Journal on Transportation and Logistics, 2014
This paper provides a discussion of network traffic flow stability and network capacity including... more This paper provides a discussion of network traffic flow stability and network capacity including existing definitions and measurement methods in the literature. To characterize network traffic flow, three phases are defined as free flow (F), inhomogenously congested (IC), and homogenously congested. It is shown that in large non-homogenous networks, the F ? IC transition is usually a hysteretic phase transition. This paper examines the effects of adaptive driving on network capacity and traffic instability in a simulated network model of the Chicago metropolitan area as a large-scale highly congested complex network with exit flows. Results show that when the number of adaptive drivers increases, the general trend for network capacity is also increasing with some fluctuations due to randomness of traffic and overlapping effects of route choices. It is also found that adaptive driving may increase average network flow but may not necessarily improve network output, especially when the population of adaptive drivers is large and no gridlock exists. Results also suggest that with a larger population of adaptive drivers, hysteresis and gridlock are less likely to form. However, it is shown that bifurcation and multivaluedness can still occur even when the entire population of drivers is adaptive.
The Transit Capacity and Quality of Service Manual (TCQSM) provides transit agencies with tools f... more The Transit Capacity and Quality of Service Manual (TCQSM) provides transit agencies with tools for measuring system performance at different levels of operation. Bus service reliability, one of the key performance measures, has become a major concern of both transit operators and users because it significantly affects user experience and service quality perceptions. The objective of this paper is to assess the existing reliability measures proposed by TCQSM and develop new ones at the bus stop level. The latter are not suggested as replacements for the existing measures; rather, they are complementary. Using empirical data from archived Bus Dispatch System (BDS) data in Portland, Oregon, a number of key characteristics of distributions of delay (schedule deviation) and headway deviation are identified. In addition, the proposed reliability measures at the stop level are capable of differentiating between the costs of being early versus late. The results of this study can be implemented in transit operations for use in improving schedules and operations strategies. Also, transit agencies can use the proposed reliability measures to evaluate and prioritize stops for operational improvement purposes.
ABSTRACT Installing charging facilities in existing parking lots in city centers is considered an... more ABSTRACT Installing charging facilities in existing parking lots in city centers is considered an effective measure to encourage the adoption of plug-in electric vehicles (PEV). This paper is concerned with the problem of optimally locating these facilities to minimize the total system cost. The problem is formulated as a fixed charge facility location model with charging capacity constraints. The model extends the existing work by allowing unserved demands and considering drivers' tendency to stick to familiar parking lots. Accordingly, inconvenience costs are introduced for unserved demands and for those who have to change their parking lots for the purpose of charging. The proposed model is not only always feasible, but also introduces a pricing mechanism so that the level of service (measured by the cost of unserved demands) can be traded off with infrastructure cost. In addition, a stochastic version of the proposed model is developed to address the effects of uncertain PEV market penetration rate on the design of charging facilities. A case study is conducted to analyze the sensitivity of the models to different cost components, and to compare the results of the stochastic and deterministic models.
ABSTRACT This paper integrates real-time traveler information on prevailing traffic conditions (a... more ABSTRACT This paper integrates real-time traveler information on prevailing traffic conditions (adaptive driving) into time-dependent origin-destination demand estimation in a simulation-based dynamic traffic assignment model. The objective is to explore the impact of adaptive driving on demand estimation, and to recognize a growing component of the traveling public in the methods used to infer network flow patterns given partial observations. Time-dependent origin-destination demand estimation can be formulated as a bi-level optimization problem in which the deviation from observations and historical demand are subject to a minimization. In the classical problem, it is assumed that users will follow paths that they have been assigned based on the user equilibrium model. Growing penetration of a wide array of devices enable users to receive real-time information on prevailing (and possibly predicted) traffic conditions, which enables them to update their path choice en-route. However, not all travelers receive or follow such information. This paper proposes a modified optimization algorithm to estimate the time-dependent origin-destination trip tables for large-scale networks considering varying population of adaptive drivers. The modified algorithm is solved with a tri-level algorithm. This algorithm is applied to a highly congested urban network of Chicago.
Transportation Research Part C: Emerging Technologies, 2013
This study explores the limiting properties of network-wide traffic flow relations under heavily ... more This study explores the limiting properties of network-wide traffic flow relations under heavily congested conditions in a large-scale complex urban street network; these limiting conditions are emulated in the context of dynamic traffic assignment (DTA) experiments on an actual large network. The primary objectives are to characterize gridlock and understand its dynamics. This study addresses a gap in the literature with regard to the existence of exit flow and recovery period. The onedimensional theoretical Network Fundamental Diagram (NFD) only represents steady-state behavior and holds only when the inputs change slowly in time and traffic is distributed homogenously in space. Also, it does not describe the hysteretic behavior of the network traffic when a gridlock forms or when network recovers. Thus, a model is proposed to reproduce hysteresis and gridlock when homogeneity and steady-state conditions do not hold. It is conjectured that the network average flow can be approximated as a non-linear function of network average density and variation in link densities. The proposed model is calibrated for the Chicago Central Business District (CBD) network. We also show that complex urban networks with multiple route choices, similar to the idealized network tested previously in the literature, tend to jam at a range of densities that are smaller than the theoretical average network jam density. Also it is demonstrated that networks tend to gridlock in many different ways with different configurations. This study examines how mobility of urban street networks could be improved by managing vehicle accumulation and re-distributing network traffic via strategies such as demand management and disseminating real-time traveler information (adaptive driving). This study thus defines and explores some key characteristics and dynamics of urban street network gridlocks including gridlock formation, propagation, recovery, size, etc.
Transportation Research Record: Journal of the Transportation Research Board, 2014
ABSTRACT The main goal of the study was to integrate demand models into weather-responsive networ... more ABSTRACT The main goal of the study was to integrate demand models into weather-responsive network traffic estimation and prediction system methodologies. The study examined the behavioral responses of travelers along several dimensions in response to weather-related transportation management strategies in conjunction with active travel demand management strategies before and during severe weather events. Specific management interventions included pretrip, information-based mode, and departure time choice adjustments, as well as policy-based rescheduling of school hours. The paper presents a case study of the Chicago, Illinois, area network under snow conditions to assess the effect of a combination of demand management strategies to maintain the same level of network performance as under clear weather conditions. A combination of earlier dissemination of information and school-opening policy resulted in a similar level of network performance maintained under a median snow day as compared with a clear weather day. The paper presents integrated supply and demand models for simulation and an assessment of demand management strategies in conjunction with weather-related congestion.
Transportation Research Record: Journal of the Transportation Research Board, 2013
The objective of the project is to develop a framework and procedures for implementing and evalua... more The objective of the project is to develop a framework and procedures for implementing and evaluating weather-responsive traffic management (WRTM) strategies using Traffic Estimation and Prediction System (TrEPS) methodologies. In a previous FHWAfunded project, a methodology was developed and tested for incorporating weather impacts in off-line TrEPS. This capability is now included in on-line TrEPS, which interacts with multiple sources of local real-time information, to provide operators with predicted traffic states under the current and future weather conditions. The main goal is to support the decision making process for addressing the disruptive effect of inclement weather on the traffic system. These tools were developed, applied, calibrated and tested in three different locations across the US. The networks selected include Salt Lake City, UT, New York's Long Island Expressway Area and Chicago, IL. In addition to building the networks and developing the various demand and supply inputs, calibration of the traffic models to local weather conditions has provided a rich database of calibrated weather-sensitive traffic models that could be applied in any region. The methodology is configured to run with real-time traffic data (e.g. from loop detectors or RTMS sensors). The methodology was used to evaluate the effectiveness of different weather-related traffic management strategies in specific areas. The project has successfully demonstrated the potential of a TrEPS installation that is "always on", up to date and adaptively calibrated to address a range of weather conditions and scenarios, retrievable on demand by local operating agencies through a scenario manager.
Transportation Research Record: Journal of the Transportation Research Board, 2013
ABSTRACT This paper examines how correlations in link travel times affect reliable path finding i... more ABSTRACT This paper examines how correlations in link travel times affect reliable path finding in a stochastic network. The reliable path is defined as the path that requires the lowest travel time budget to ensure a given probability of on-time arrival. Such a path can be found by solving the shortest path problem considering on-time arrival reliability (SPOTAR). SPOTAR is solved approximately by using an approach based on Monte Carlo simulation. A major advantage of the simulation-based algorithm is its ability to deal with correlated link travel times. Through the use of a real-world network, the simulation-based algorithm is first validated by comparing it with a label-correcting algorithm that can solve the uncorrelated case exactly; the impacts of the correlations on link travel times are then examined. The results of the numerical experiments indicate that correlations affect the optimal SPOTAR solutions significantly. However, larger correlations do not always lead to larger errors in the reliable route choices that ignore them.
Transportation Research Record: Journal of the Transportation Research Board, 2014
The aim of this study was to solve the minimum path travel time budget (MPTTB) problem, in which ... more The aim of this study was to solve the minimum path travel time budget (MPTTB) problem, in which the travel time budget was the reliability index. This index was defined as the sum of the mean path travel time and the scaled standard deviation, which included the covariance matrix to consider correlation. Two existing solution methods in the literature, the outer approximation algorithm and Monte Carlo simulation method, were applied to solve the MPTTB problem. The former method approximated the hard nonlinear constraint of the MPTTB problem by a series of linear cuts generated iteratively and repeatedly solved a mixed integer program. The latter method, which was a simulation-based method, included two stages. The first stage founded a set of candidate paths, and the second stage generated the distribution of travel times for the existing paths in the candidate set. The numerical results for these two solution methods were conducted on the Chicago sketch network, and results showed that the methods found comparable solutions though they have respective advantages and drawbacks. Although the outer approximation algorithm demonstrated promising performance, it still relied on repeatedly solving a mixed integer program (subproblem) with a commercial solver, which could be a challenging task in its own right.
Transportation Research Record: Journal of the Transportation Research Board, 2014
This paper evaluates measurement methods for traffic flow variables taken at the network level. G... more This paper evaluates measurement methods for traffic flow variables taken at the network level. Generalized Edie's definitions of fundamental traffic flow variables along highways are extended for considering vehicles traveling in networks. These definitions are used to characterize traffic flow in networks and form the basis for estimating relationships among network density, flow, and speed in the form of a network fundamental diagram. The method relies on three-dimensional vehicle trajectories to provide estimates of network flow, density, and speed. Such trajectories may be routinely obtained from particle-based microscopic and mesoscopic simulation models and are increasingly available from tracking devices on vehicles. Numerical results from the simulation of two networks, in Chicago, Illinois, and Salt Lake City, Utah, are presented to illustrate and validate the estimation methodology. As part of the verification process, the study confirms that the traffic flow fundamental identity (Q 5 K • V) holds at the network level only when networkwide traffic flow variables are defined consistently with Edie's definitions.
EURO Journal on Transportation and Logistics, 2014
This paper provides a discussion of network traffic flow stability and network capacity including... more This paper provides a discussion of network traffic flow stability and network capacity including existing definitions and measurement methods in the literature. To characterize network traffic flow, three phases are defined as free flow (F), inhomogenously congested (IC), and homogenously congested. It is shown that in large non-homogenous networks, the F ? IC transition is usually a hysteretic phase transition. This paper examines the effects of adaptive driving on network capacity and traffic instability in a simulated network model of the Chicago metropolitan area as a large-scale highly congested complex network with exit flows. Results show that when the number of adaptive drivers increases, the general trend for network capacity is also increasing with some fluctuations due to randomness of traffic and overlapping effects of route choices. It is also found that adaptive driving may increase average network flow but may not necessarily improve network output, especially when the population of adaptive drivers is large and no gridlock exists. Results also suggest that with a larger population of adaptive drivers, hysteresis and gridlock are less likely to form. However, it is shown that bifurcation and multivaluedness can still occur even when the entire population of drivers is adaptive.
The Transit Capacity and Quality of Service Manual (TCQSM) provides transit agencies with tools f... more The Transit Capacity and Quality of Service Manual (TCQSM) provides transit agencies with tools for measuring system performance at different levels of operation. Bus service reliability, one of the key performance measures, has become a major concern of both transit operators and users because it significantly affects user experience and service quality perceptions. The objective of this paper is to assess the existing reliability measures proposed by TCQSM and develop new ones at the bus stop level. The latter are not suggested as replacements for the existing measures; rather, they are complementary. Using empirical data from archived Bus Dispatch System (BDS) data in Portland, Oregon, a number of key characteristics of distributions of delay (schedule deviation) and headway deviation are identified. In addition, the proposed reliability measures at the stop level are capable of differentiating between the costs of being early versus late. The results of this study can be implemented in transit operations for use in improving schedules and operations strategies. Also, transit agencies can use the proposed reliability measures to evaluate and prioritize stops for operational improvement purposes.
ABSTRACT Installing charging facilities in existing parking lots in city centers is considered an... more ABSTRACT Installing charging facilities in existing parking lots in city centers is considered an effective measure to encourage the adoption of plug-in electric vehicles (PEV). This paper is concerned with the problem of optimally locating these facilities to minimize the total system cost. The problem is formulated as a fixed charge facility location model with charging capacity constraints. The model extends the existing work by allowing unserved demands and considering drivers' tendency to stick to familiar parking lots. Accordingly, inconvenience costs are introduced for unserved demands and for those who have to change their parking lots for the purpose of charging. The proposed model is not only always feasible, but also introduces a pricing mechanism so that the level of service (measured by the cost of unserved demands) can be traded off with infrastructure cost. In addition, a stochastic version of the proposed model is developed to address the effects of uncertain PEV market penetration rate on the design of charging facilities. A case study is conducted to analyze the sensitivity of the models to different cost components, and to compare the results of the stochastic and deterministic models.
ABSTRACT This paper integrates real-time traveler information on prevailing traffic conditions (a... more ABSTRACT This paper integrates real-time traveler information on prevailing traffic conditions (adaptive driving) into time-dependent origin-destination demand estimation in a simulation-based dynamic traffic assignment model. The objective is to explore the impact of adaptive driving on demand estimation, and to recognize a growing component of the traveling public in the methods used to infer network flow patterns given partial observations. Time-dependent origin-destination demand estimation can be formulated as a bi-level optimization problem in which the deviation from observations and historical demand are subject to a minimization. In the classical problem, it is assumed that users will follow paths that they have been assigned based on the user equilibrium model. Growing penetration of a wide array of devices enable users to receive real-time information on prevailing (and possibly predicted) traffic conditions, which enables them to update their path choice en-route. However, not all travelers receive or follow such information. This paper proposes a modified optimization algorithm to estimate the time-dependent origin-destination trip tables for large-scale networks considering varying population of adaptive drivers. The modified algorithm is solved with a tri-level algorithm. This algorithm is applied to a highly congested urban network of Chicago.
Transportation Research Part C: Emerging Technologies, 2013
This study explores the limiting properties of network-wide traffic flow relations under heavily ... more This study explores the limiting properties of network-wide traffic flow relations under heavily congested conditions in a large-scale complex urban street network; these limiting conditions are emulated in the context of dynamic traffic assignment (DTA) experiments on an actual large network. The primary objectives are to characterize gridlock and understand its dynamics. This study addresses a gap in the literature with regard to the existence of exit flow and recovery period. The onedimensional theoretical Network Fundamental Diagram (NFD) only represents steady-state behavior and holds only when the inputs change slowly in time and traffic is distributed homogenously in space. Also, it does not describe the hysteretic behavior of the network traffic when a gridlock forms or when network recovers. Thus, a model is proposed to reproduce hysteresis and gridlock when homogeneity and steady-state conditions do not hold. It is conjectured that the network average flow can be approximated as a non-linear function of network average density and variation in link densities. The proposed model is calibrated for the Chicago Central Business District (CBD) network. We also show that complex urban networks with multiple route choices, similar to the idealized network tested previously in the literature, tend to jam at a range of densities that are smaller than the theoretical average network jam density. Also it is demonstrated that networks tend to gridlock in many different ways with different configurations. This study examines how mobility of urban street networks could be improved by managing vehicle accumulation and re-distributing network traffic via strategies such as demand management and disseminating real-time traveler information (adaptive driving). This study thus defines and explores some key characteristics and dynamics of urban street network gridlocks including gridlock formation, propagation, recovery, size, etc.
Transportation Research Record: Journal of the Transportation Research Board, 2014
ABSTRACT The main goal of the study was to integrate demand models into weather-responsive networ... more ABSTRACT The main goal of the study was to integrate demand models into weather-responsive network traffic estimation and prediction system methodologies. The study examined the behavioral responses of travelers along several dimensions in response to weather-related transportation management strategies in conjunction with active travel demand management strategies before and during severe weather events. Specific management interventions included pretrip, information-based mode, and departure time choice adjustments, as well as policy-based rescheduling of school hours. The paper presents a case study of the Chicago, Illinois, area network under snow conditions to assess the effect of a combination of demand management strategies to maintain the same level of network performance as under clear weather conditions. A combination of earlier dissemination of information and school-opening policy resulted in a similar level of network performance maintained under a median snow day as compared with a clear weather day. The paper presents integrated supply and demand models for simulation and an assessment of demand management strategies in conjunction with weather-related congestion.
Transportation Research Record: Journal of the Transportation Research Board, 2013
The objective of the project is to develop a framework and procedures for implementing and evalua... more The objective of the project is to develop a framework and procedures for implementing and evaluating weather-responsive traffic management (WRTM) strategies using Traffic Estimation and Prediction System (TrEPS) methodologies. In a previous FHWAfunded project, a methodology was developed and tested for incorporating weather impacts in off-line TrEPS. This capability is now included in on-line TrEPS, which interacts with multiple sources of local real-time information, to provide operators with predicted traffic states under the current and future weather conditions. The main goal is to support the decision making process for addressing the disruptive effect of inclement weather on the traffic system. These tools were developed, applied, calibrated and tested in three different locations across the US. The networks selected include Salt Lake City, UT, New York's Long Island Expressway Area and Chicago, IL. In addition to building the networks and developing the various demand and supply inputs, calibration of the traffic models to local weather conditions has provided a rich database of calibrated weather-sensitive traffic models that could be applied in any region. The methodology is configured to run with real-time traffic data (e.g. from loop detectors or RTMS sensors). The methodology was used to evaluate the effectiveness of different weather-related traffic management strategies in specific areas. The project has successfully demonstrated the potential of a TrEPS installation that is "always on", up to date and adaptively calibrated to address a range of weather conditions and scenarios, retrievable on demand by local operating agencies through a scenario manager.
Transportation Research Record: Journal of the Transportation Research Board, 2013
ABSTRACT This paper examines how correlations in link travel times affect reliable path finding i... more ABSTRACT This paper examines how correlations in link travel times affect reliable path finding in a stochastic network. The reliable path is defined as the path that requires the lowest travel time budget to ensure a given probability of on-time arrival. Such a path can be found by solving the shortest path problem considering on-time arrival reliability (SPOTAR). SPOTAR is solved approximately by using an approach based on Monte Carlo simulation. A major advantage of the simulation-based algorithm is its ability to deal with correlated link travel times. Through the use of a real-world network, the simulation-based algorithm is first validated by comparing it with a label-correcting algorithm that can solve the uncorrelated case exactly; the impacts of the correlations on link travel times are then examined. The results of the numerical experiments indicate that correlations affect the optimal SPOTAR solutions significantly. However, larger correlations do not always lead to larger errors in the reliable route choices that ignore them.
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Papers by Ali Zockaie