IEEE Transactions on Intelligent Transportation Systems, 2012
As demand for proactive real-time transportation management systems has grown, major developments... more As demand for proactive real-time transportation management systems has grown, major developments have been seen in short-time traffic forecasting methods. Recent studies have introduced time series theory, neural networks, genetic algorithms, etc., to short-time traffic forecasting to make forecasts more reliable, efficient and accurate. However, most of these methods can only deal with data recorded at regular time intervals, thereby restricting the range of data collection tools to loop detectors or other equipment that generate regular data. The study reported here represents an attempt to expand on several existing time series forecasting methods to accommodate data recorded at irregular time intervals, thus ensuring these methods can be used to obtain predicted traffic speeds through intermittent data sources such as the GPS. The study tested several methods using the GPS data from 480 Hong Kong taxis. The results show that the best performance is obtained using a neural network model with acceleration information predicted by ARIMA model.
Journal of the Eastern Asia Society for Transportation Studies, 2015
Grave-sweeping is a popular special event in Asia, especially in Chinese societies, in which fami... more Grave-sweeping is a popular special event in Asia, especially in Chinese societies, in which families visit columbaria to express filial piety to their ancestors. The extraordinarily high travel demands usually associated with visiting columbaria during a relative short period around the grave-sweeping festivals severely affect the local traffic. To design and plan adequate transport facilities and services to cater to the travel needs of these families, modeling of their travel demand is a prerequisite procedure. This paper develops and calibrates a non-linear regression model for trip attraction and a joint logit model for trip distribution and modal split using data from headcount and revealed preference surveys collected at selected columbaria during the Ching Ming Festivals of 2013 and 2014. This paper also discusses policy insights gained from the model results that can be applied to the planning of transport facilities and the provision of feeder services to mitigate local co...
This paper proposes an approach-proportion-based variational inequality (VI) formulation for the ... more This paper proposes an approach-proportion-based variational inequality (VI) formulation for the multi-class dynamic traffic assignment problem with physical queues using the concept of intersection movements . To solve the problem, an extragradient method that only requires mild assumptions for convergence is developed. A car-truck interaction paradox, stating that allowing trucks traveling in a network or increasing the demand of trucks traveling in a network could improve the network performance for cars, in terms of total car travel time, is discussed. Numerical examples are set up to illustrate the importance of considering multiple vehicle types and their interaction in a dynamic traffic assignment model and the effects of various parameters on the occurrence of the paradox.
Transportation Research Part C: Emerging Technologies, 2020
With the growing importance of bike-sharing systems, this paper designs a new framework to solve ... more With the growing importance of bike-sharing systems, this paper designs a new framework to solve rebalancing problem. It contains two aspects: dynamic rebalancing within each station and static rebalancing among stations. Firstly, we give a new flow-type task window (F-window) by defining the consistency index of travelers. It is more suitable as a task window for rebalancing than time-type task window (T-window) based on three aspects analysis. Through three assumptions, the temporal-distribution learning model including task window and station storage configuration, are built to realize new dynamic rebalancing. The spatial-distribution learning method is introduced to divide management areas for static rebalancing. The empirical results show that F-window can better match the strong time-sensitive of demand fluctuation. Compared with traditional rebalancing needs hours, each rebalancing within a station can be completed within average 4 min. By setting the station storage configuration, it makes rebalancing in this paper meets the demand of 28.3 times the hourly rebalancing within one week. And the number of vehicles visiting stations has dropped below 20%.
Transportation Research Part D: Transport and Environment, 2019
Abstract Reducing roadside emissions is a common challenge in metropolitan cities. In Hong Kong, ... more Abstract Reducing roadside emissions is a common challenge in metropolitan cities. In Hong Kong, conventional liquefied petroleum gas taxis are one of the main contributors to roadside emissions as they operate on the streets 24 h a day with a long daily driving mileage. Moreover, these taxis suffer from a severely poor service reputation. To enhance the environmental friendliness and service quality of the taxi industry, this study explores the market potential of operating premium electric taxis in the dispatching mode. A stated preference survey was conducted to 1410 taxi customers about their taxi-riding choices between premium electric taxis and conventional liquefied petroleum gas taxis. In total, 5640 observations were obtained and used to develop a series of binary logistic regression models with different model formulations for the determination of the significant factors influencing customers’ selections. The findings indicate that walk time to and wait time for taxis were the most critical concerns to the customers, and they were more willing to take premium taxis if their journey distance was longer and their desired improvement on taxi service quality was greater. The socio-demographic status of taxi customers also influences their choices. The associated policy implications are discussed for promoting taxis with better service quality and fewer roadside emissions. The findings provide some policy insights to other international cities that have a similar taxi market to Hong Kong.
Transportation Research Part B: Methodological, 2019
Sectional fares have been used in transit services in practice but are rarely examined analytical... more Sectional fares have been used in transit services in practice but are rarely examined analytically and compared with flat and distance-based fares, especially under the considerations of path choice, elastic demand, service frequency, and profitability. This paper proposes a bilevel programming model to jointly determine the fare and frequency setting to maximize transit operator's profit. The preceding three fare structures can be incorporated into the bilevel model. To consider the path choice and elastic demand in the bilevel model, the existing approach-based stochastic user equilibrium transit assignment model for the fixed demand was extended to the elastic demand case and the resultant model was used in the lower level model. To solve the bilevel model, the sensitivity-based descent search method that takes into account the approach-based formulation for the elastic demand transit assignment is proposed, in which the approach-based formulation was solved by the cost-averaging self-regulated averaging method. Numerical studies and mathematical analyses were performed to examine the model properties and compare the three fare structures. The result of the Tin Shui Wai network instance is also provided to illustrate the performance of the solution method. It is proven that when all passengers' destinations are located at transit terminals, the sectional fare structure is always better than the other two fare structures in terms of profitability. For more general networks, the sectional fare structure is always better than the flat fare structure, but the choice between sectional and distance-based fare structures depends on the geometry of the network (e.g., the route structure and the distance between stops), the demand distribution, and the maximum allowable fares. It is also proven that the optimal profit (total vehicle mileage) is strictly monotonically decreasing (monotonically decreasing) with respect to the unit operating cost. Moreover, it is proven that the lower level approach-based assignment problem with elastic demand has exactly one solution. However, the bi-level problem can have multiple optimal solutions. Interestingly, it is found that from the operator's profitability point of view, providing better information to the passengers may not be good.
Transportation Research Part B: Methodological, 2019
This study estimates and manages the stochastic traffic dynamics in a bi-modal transportation sys... more This study estimates and manages the stochastic traffic dynamics in a bi-modal transportation system, and gives hints on how increasing data availability in transport and cities can be utilized to estimate transport supply functions and manage transport demand simultaneously. In the bi-modal system, travelers' mode choices are based on their perceptions of the two travel modes: driving or public transit. Some travelers who have access to real-time road (car) traffic information may shift their mode based on the information received (note that real-time information about public transit departures/arrivals is not considered here). For the roadway network, the within-day traffic evolution is modeled through a Macroscopic Fundamental Diagram (MFD), where the flow dynamics exhibits a certain level of uncertainty. A non-parametric approach is proposed to estimate the MFD. To improve traffic efficiency, we develop an adaptive pricing mechanism coupled with the learned MFD. The adaptive pricing extends the study of Liu and Geroliminis (2017) to the time-dependent case, which can better accommodate temporal demand variations and achieve higher efficiency. Numerical studies are conducted on a one-region theoretical city network to illustrate the dynamic evolution of traffic, the MFD learning framework, and the efficiency of the adaptive pricing mechanism.
International Journal of Sustainable Transportation, 2019
Abstract There has been a recent surge of research interest in quantifying the health and environ... more Abstract There has been a recent surge of research interest in quantifying the health and environmental impacts of increased cycling in urban environments. Although there is general agreement that the benefits of increased cycling outweigh the risks, most of the methodologies developed have had limited value for evaluating real-world transport policies. This is because they are based on hypothetical scenarios where increased cycling takes place but give no consideration to the courses of action which may help policymakers to achieve the scenarios. A useful extension to these methodologies would be one which allowed a user to find the optimal infrastructure design and/or policies which would maximize total societal benefit, taking into account the health and environmental impacts of cycling. In this study, a Network Design Problem is formulated for systematically designing cycling network layouts in order to maximize the net benefits to the network users and society. The problem is formulated as a mathematical program with equilibrium constraints (MPEC) and a solution approach based on a genetic algorithm (GA) is provided to solve the problem. The problem formulation and solution algorithm are tested using a numerical example. The GA algorithm was shown to efficiently converge to an optimal or near-optimal solution for the cycle network design. The proposed optimization framework may be adopted by transport authorities and/or urban planners as a decision support tool to help them to systematically identify the best design for a cycle network which balances the benefits and risks to all stakeholders.
Transportation Research Part B: Methodological, 2018
We investigate the day-today modal choice of commuters in a bi-modal transportation system compri... more We investigate the day-today modal choice of commuters in a bi-modal transportation system comprising both private transport and public transit. On each day, commuters adjust their modal choice, based on the previous day's perceived travel cost and intraday toll or subsidy of each mode, to minimize their perceived travel cost. Meanwhile, the transportation authority sets the number of bus runs and the tolls or subsidies of two modes on each day, based on the previous day's modal choice of commuters, to simultaneously reduce the daily total actual travel cost of the transportation system and achieve a Pareto improvement or zero-sum revenue target at a stationary state. The evolution process of the modal choice of commuters, associated with the strategy adjustment process of the authority, is formulated as a dynamical system model. We analyze several properties of the dynamical system with respect to its stationary point and evolutionary trajectory. Moreover, we introduce new concepts of Pareto improvement and zero-sum revenue in a day-today dynamic setting and propose the two targets' implementations in either a prior or a posterior form. We show that, although commuters have different perceived travel costs for using the same travel mode, the authority need not know the probability distribution of perceived travel costs of commuters to achieve the Pareto improvement target. Finally, we give a set of numerical examples to show the properties of the model and the implementation of the toll or subsidy schemes.
International Transactions in Operational Research, 2019
This paper investigates a new cash transportation problem, which is a variant of the capacitated ... more This paper investigates a new cash transportation problem, which is a variant of the capacitated vehicle routing problem. To better satisfy the demands of customers (e.g., banks, large retailers, shopping centers, automated teller machines, etc.
Transportation Research Part B: Methodological, 2018
There has been a resurgence of interest in demand-responsive shared-ride systems, motivated by co... more There has been a resurgence of interest in demand-responsive shared-ride systems, motivated by concerns for the environment and also new developments in technologies which enable new modes of operations. This paper surveys the research developments on the Dial-A-Ride Problem (DARP) since 2007. We provide a classification of the problem variants and the solution methodologies, and references to benchmark instances. We also present some application areas for the DARP, discuss some future trends and challenges, and indicate some possible directions for future research.
Transportation Research Part B: Methodological, 2018
Travel time uncertainty has significant effects on travel reliability and travelers' generalized ... more Travel time uncertainty has significant effects on travel reliability and travelers' generalized trip cost. However, travel time uncertainty has not been considered in existing ride-sharing models, leading to an inaccurate estimation of the benefit from ride-sharing and irrational ride-sharing matches. To fill in the gap, this paper proposes a stochastic ride-sharing model, in which travel time is assumed to be stochastic and follow a time-independent general distribution that has a positive lower bound. Due to travel time uncertainty, travelers may not arrive at their destinations on time. Different from the traditional models taking time windows as hard constraints, the proposed ride-sharing system only requires each participant announcing a role and the desired arrival time window. In the model, the generalized trip cost consists of the cost of driving a vehicle, the cost of travel time, and the cost of schedule delay early and late. This study investigates the effect of the unit variable cost of driving, travelers' values of time (VOTs), and travel time uncertainty on the cost saving of ride-sharing trips compared to driving-alone trips. A bi-objective ridesharing matching model is proposed to maximize both the total generalized trip cost saving and the number of matches. The proposed ride-sharing model is further extended to consider time-dependent travel time uncertainty, and the Monte Carlo simulation (MCS) method is developed to evaluate the mean generalized trip cost. Finally, numerical examples are provided to illustrate the properties of the two proposed models. The results show that the unit variable cost of driving, travelers' VOTs, travel time uncertainty, and the selection of the weight in the objective function have significant impacts on the performance of the proposed ride-sharing system with travel time uncertainty. The results also show that a feasible ride-sharing match based on deterministic travel time can become infeasible in a stochastic ride-sharing system. It is therefore important to consider travel time uncertainty when determining the matches.
Bike sharing systems are very popular nowadays. One of the characteristics is that bikes are pick... more Bike sharing systems are very popular nowadays. One of the characteristics is that bikes are picked up from some surplus bike stations and transported to all deficit bike stations by a repositioning vehicle with limited capacity to satisfy the demand of deficit bike stations. Motivated by this real world bicycle repositioning problem, we study the selective pickup and delivery problem, where demand at every delivery node has to be satisfied by the supply collected from a subset of pickup nodes. The objective is to minimize the total travel cost incurred from visiting the nodes. We present a GRASP with path-relinking for solving the described problem. Experimental results show that this simple heuristic improves the existing results in the literature with an average improvement of 5.72% using small computing times. The proposed heuristic can contribute to the development of effective and efficient algorithms for real world bicycle reposition operations.
Cell-based dynamic equilibrium models are one class of dynamic traffic assignment (DTA) models th... more Cell-based dynamic equilibrium models are one class of dynamic traffic assignment (DTA) models that can capture equilibrium conditions and realistic traffic dynamics, such as queue spillback, queue formulation, and queue dissipation. However, compared with point-queue DTA models or DTA models using wholelink delay models for flow propagation, cell-based equilibrium models are often more computational demanding. This may raise issues for actual applications, in particular, for the implementation for real-time traffic control and route guidance applications, because the solution must be obtained quickly. Moreover, recent cellbased dynamic equilibrium models tend to capture more realistic travel behavior and traffic dynamics but this made the resulting models even more complicated and more difficult to solve for optimal solutions. Hence, this article aims at reviewing the recent development of cell-based dynamic equilibrium models, the formulation approaches, solution methods used, and the components of these models so as to point out the implementation issues of the latest cell-based dynamic equilibrium model with the consideration supply stochasticity for traffic control and route guidance applications as well as some gaps for future research directions.
Transportation Research Part E: Logistics and Transportation Review, 2014
We study the static bike repositioning problem We modify the problem to improve its realism and... more We study the static bike repositioning problem We modify the problem to improve its realism and reduce the solution space We solve the problem by iterated tabu search with specific operators We obtain high quality solutions efficiently *Highlights (for review)
... NH and C. Stamatiadis (2001).'Combining traffic assignment and adaptive control in a dyn... more ... NH and C. Stamatiadis (2001).'Combining traffic assignment and adaptive control in a dynamic ... Lo, H.(2002),'Trip travel time reliability in degradable transport networks', in MAP Taylor (ed ... Lo, H. and YK Tung (2003),'Network with degradable links: capacity analysis and design ...
IEEE Transactions on Intelligent Transportation Systems, 2012
As demand for proactive real-time transportation management systems has grown, major developments... more As demand for proactive real-time transportation management systems has grown, major developments have been seen in short-time traffic forecasting methods. Recent studies have introduced time series theory, neural networks, genetic algorithms, etc., to short-time traffic forecasting to make forecasts more reliable, efficient and accurate. However, most of these methods can only deal with data recorded at regular time intervals, thereby restricting the range of data collection tools to loop detectors or other equipment that generate regular data. The study reported here represents an attempt to expand on several existing time series forecasting methods to accommodate data recorded at irregular time intervals, thus ensuring these methods can be used to obtain predicted traffic speeds through intermittent data sources such as the GPS. The study tested several methods using the GPS data from 480 Hong Kong taxis. The results show that the best performance is obtained using a neural network model with acceleration information predicted by ARIMA model.
Journal of the Eastern Asia Society for Transportation Studies, 2015
Grave-sweeping is a popular special event in Asia, especially in Chinese societies, in which fami... more Grave-sweeping is a popular special event in Asia, especially in Chinese societies, in which families visit columbaria to express filial piety to their ancestors. The extraordinarily high travel demands usually associated with visiting columbaria during a relative short period around the grave-sweeping festivals severely affect the local traffic. To design and plan adequate transport facilities and services to cater to the travel needs of these families, modeling of their travel demand is a prerequisite procedure. This paper develops and calibrates a non-linear regression model for trip attraction and a joint logit model for trip distribution and modal split using data from headcount and revealed preference surveys collected at selected columbaria during the Ching Ming Festivals of 2013 and 2014. This paper also discusses policy insights gained from the model results that can be applied to the planning of transport facilities and the provision of feeder services to mitigate local co...
This paper proposes an approach-proportion-based variational inequality (VI) formulation for the ... more This paper proposes an approach-proportion-based variational inequality (VI) formulation for the multi-class dynamic traffic assignment problem with physical queues using the concept of intersection movements . To solve the problem, an extragradient method that only requires mild assumptions for convergence is developed. A car-truck interaction paradox, stating that allowing trucks traveling in a network or increasing the demand of trucks traveling in a network could improve the network performance for cars, in terms of total car travel time, is discussed. Numerical examples are set up to illustrate the importance of considering multiple vehicle types and their interaction in a dynamic traffic assignment model and the effects of various parameters on the occurrence of the paradox.
Transportation Research Part C: Emerging Technologies, 2020
With the growing importance of bike-sharing systems, this paper designs a new framework to solve ... more With the growing importance of bike-sharing systems, this paper designs a new framework to solve rebalancing problem. It contains two aspects: dynamic rebalancing within each station and static rebalancing among stations. Firstly, we give a new flow-type task window (F-window) by defining the consistency index of travelers. It is more suitable as a task window for rebalancing than time-type task window (T-window) based on three aspects analysis. Through three assumptions, the temporal-distribution learning model including task window and station storage configuration, are built to realize new dynamic rebalancing. The spatial-distribution learning method is introduced to divide management areas for static rebalancing. The empirical results show that F-window can better match the strong time-sensitive of demand fluctuation. Compared with traditional rebalancing needs hours, each rebalancing within a station can be completed within average 4 min. By setting the station storage configuration, it makes rebalancing in this paper meets the demand of 28.3 times the hourly rebalancing within one week. And the number of vehicles visiting stations has dropped below 20%.
Transportation Research Part D: Transport and Environment, 2019
Abstract Reducing roadside emissions is a common challenge in metropolitan cities. In Hong Kong, ... more Abstract Reducing roadside emissions is a common challenge in metropolitan cities. In Hong Kong, conventional liquefied petroleum gas taxis are one of the main contributors to roadside emissions as they operate on the streets 24 h a day with a long daily driving mileage. Moreover, these taxis suffer from a severely poor service reputation. To enhance the environmental friendliness and service quality of the taxi industry, this study explores the market potential of operating premium electric taxis in the dispatching mode. A stated preference survey was conducted to 1410 taxi customers about their taxi-riding choices between premium electric taxis and conventional liquefied petroleum gas taxis. In total, 5640 observations were obtained and used to develop a series of binary logistic regression models with different model formulations for the determination of the significant factors influencing customers’ selections. The findings indicate that walk time to and wait time for taxis were the most critical concerns to the customers, and they were more willing to take premium taxis if their journey distance was longer and their desired improvement on taxi service quality was greater. The socio-demographic status of taxi customers also influences their choices. The associated policy implications are discussed for promoting taxis with better service quality and fewer roadside emissions. The findings provide some policy insights to other international cities that have a similar taxi market to Hong Kong.
Transportation Research Part B: Methodological, 2019
Sectional fares have been used in transit services in practice but are rarely examined analytical... more Sectional fares have been used in transit services in practice but are rarely examined analytically and compared with flat and distance-based fares, especially under the considerations of path choice, elastic demand, service frequency, and profitability. This paper proposes a bilevel programming model to jointly determine the fare and frequency setting to maximize transit operator's profit. The preceding three fare structures can be incorporated into the bilevel model. To consider the path choice and elastic demand in the bilevel model, the existing approach-based stochastic user equilibrium transit assignment model for the fixed demand was extended to the elastic demand case and the resultant model was used in the lower level model. To solve the bilevel model, the sensitivity-based descent search method that takes into account the approach-based formulation for the elastic demand transit assignment is proposed, in which the approach-based formulation was solved by the cost-averaging self-regulated averaging method. Numerical studies and mathematical analyses were performed to examine the model properties and compare the three fare structures. The result of the Tin Shui Wai network instance is also provided to illustrate the performance of the solution method. It is proven that when all passengers' destinations are located at transit terminals, the sectional fare structure is always better than the other two fare structures in terms of profitability. For more general networks, the sectional fare structure is always better than the flat fare structure, but the choice between sectional and distance-based fare structures depends on the geometry of the network (e.g., the route structure and the distance between stops), the demand distribution, and the maximum allowable fares. It is also proven that the optimal profit (total vehicle mileage) is strictly monotonically decreasing (monotonically decreasing) with respect to the unit operating cost. Moreover, it is proven that the lower level approach-based assignment problem with elastic demand has exactly one solution. However, the bi-level problem can have multiple optimal solutions. Interestingly, it is found that from the operator's profitability point of view, providing better information to the passengers may not be good.
Transportation Research Part B: Methodological, 2019
This study estimates and manages the stochastic traffic dynamics in a bi-modal transportation sys... more This study estimates and manages the stochastic traffic dynamics in a bi-modal transportation system, and gives hints on how increasing data availability in transport and cities can be utilized to estimate transport supply functions and manage transport demand simultaneously. In the bi-modal system, travelers' mode choices are based on their perceptions of the two travel modes: driving or public transit. Some travelers who have access to real-time road (car) traffic information may shift their mode based on the information received (note that real-time information about public transit departures/arrivals is not considered here). For the roadway network, the within-day traffic evolution is modeled through a Macroscopic Fundamental Diagram (MFD), where the flow dynamics exhibits a certain level of uncertainty. A non-parametric approach is proposed to estimate the MFD. To improve traffic efficiency, we develop an adaptive pricing mechanism coupled with the learned MFD. The adaptive pricing extends the study of Liu and Geroliminis (2017) to the time-dependent case, which can better accommodate temporal demand variations and achieve higher efficiency. Numerical studies are conducted on a one-region theoretical city network to illustrate the dynamic evolution of traffic, the MFD learning framework, and the efficiency of the adaptive pricing mechanism.
International Journal of Sustainable Transportation, 2019
Abstract There has been a recent surge of research interest in quantifying the health and environ... more Abstract There has been a recent surge of research interest in quantifying the health and environmental impacts of increased cycling in urban environments. Although there is general agreement that the benefits of increased cycling outweigh the risks, most of the methodologies developed have had limited value for evaluating real-world transport policies. This is because they are based on hypothetical scenarios where increased cycling takes place but give no consideration to the courses of action which may help policymakers to achieve the scenarios. A useful extension to these methodologies would be one which allowed a user to find the optimal infrastructure design and/or policies which would maximize total societal benefit, taking into account the health and environmental impacts of cycling. In this study, a Network Design Problem is formulated for systematically designing cycling network layouts in order to maximize the net benefits to the network users and society. The problem is formulated as a mathematical program with equilibrium constraints (MPEC) and a solution approach based on a genetic algorithm (GA) is provided to solve the problem. The problem formulation and solution algorithm are tested using a numerical example. The GA algorithm was shown to efficiently converge to an optimal or near-optimal solution for the cycle network design. The proposed optimization framework may be adopted by transport authorities and/or urban planners as a decision support tool to help them to systematically identify the best design for a cycle network which balances the benefits and risks to all stakeholders.
Transportation Research Part B: Methodological, 2018
We investigate the day-today modal choice of commuters in a bi-modal transportation system compri... more We investigate the day-today modal choice of commuters in a bi-modal transportation system comprising both private transport and public transit. On each day, commuters adjust their modal choice, based on the previous day's perceived travel cost and intraday toll or subsidy of each mode, to minimize their perceived travel cost. Meanwhile, the transportation authority sets the number of bus runs and the tolls or subsidies of two modes on each day, based on the previous day's modal choice of commuters, to simultaneously reduce the daily total actual travel cost of the transportation system and achieve a Pareto improvement or zero-sum revenue target at a stationary state. The evolution process of the modal choice of commuters, associated with the strategy adjustment process of the authority, is formulated as a dynamical system model. We analyze several properties of the dynamical system with respect to its stationary point and evolutionary trajectory. Moreover, we introduce new concepts of Pareto improvement and zero-sum revenue in a day-today dynamic setting and propose the two targets' implementations in either a prior or a posterior form. We show that, although commuters have different perceived travel costs for using the same travel mode, the authority need not know the probability distribution of perceived travel costs of commuters to achieve the Pareto improvement target. Finally, we give a set of numerical examples to show the properties of the model and the implementation of the toll or subsidy schemes.
International Transactions in Operational Research, 2019
This paper investigates a new cash transportation problem, which is a variant of the capacitated ... more This paper investigates a new cash transportation problem, which is a variant of the capacitated vehicle routing problem. To better satisfy the demands of customers (e.g., banks, large retailers, shopping centers, automated teller machines, etc.
Transportation Research Part B: Methodological, 2018
There has been a resurgence of interest in demand-responsive shared-ride systems, motivated by co... more There has been a resurgence of interest in demand-responsive shared-ride systems, motivated by concerns for the environment and also new developments in technologies which enable new modes of operations. This paper surveys the research developments on the Dial-A-Ride Problem (DARP) since 2007. We provide a classification of the problem variants and the solution methodologies, and references to benchmark instances. We also present some application areas for the DARP, discuss some future trends and challenges, and indicate some possible directions for future research.
Transportation Research Part B: Methodological, 2018
Travel time uncertainty has significant effects on travel reliability and travelers' generalized ... more Travel time uncertainty has significant effects on travel reliability and travelers' generalized trip cost. However, travel time uncertainty has not been considered in existing ride-sharing models, leading to an inaccurate estimation of the benefit from ride-sharing and irrational ride-sharing matches. To fill in the gap, this paper proposes a stochastic ride-sharing model, in which travel time is assumed to be stochastic and follow a time-independent general distribution that has a positive lower bound. Due to travel time uncertainty, travelers may not arrive at their destinations on time. Different from the traditional models taking time windows as hard constraints, the proposed ride-sharing system only requires each participant announcing a role and the desired arrival time window. In the model, the generalized trip cost consists of the cost of driving a vehicle, the cost of travel time, and the cost of schedule delay early and late. This study investigates the effect of the unit variable cost of driving, travelers' values of time (VOTs), and travel time uncertainty on the cost saving of ride-sharing trips compared to driving-alone trips. A bi-objective ridesharing matching model is proposed to maximize both the total generalized trip cost saving and the number of matches. The proposed ride-sharing model is further extended to consider time-dependent travel time uncertainty, and the Monte Carlo simulation (MCS) method is developed to evaluate the mean generalized trip cost. Finally, numerical examples are provided to illustrate the properties of the two proposed models. The results show that the unit variable cost of driving, travelers' VOTs, travel time uncertainty, and the selection of the weight in the objective function have significant impacts on the performance of the proposed ride-sharing system with travel time uncertainty. The results also show that a feasible ride-sharing match based on deterministic travel time can become infeasible in a stochastic ride-sharing system. It is therefore important to consider travel time uncertainty when determining the matches.
Bike sharing systems are very popular nowadays. One of the characteristics is that bikes are pick... more Bike sharing systems are very popular nowadays. One of the characteristics is that bikes are picked up from some surplus bike stations and transported to all deficit bike stations by a repositioning vehicle with limited capacity to satisfy the demand of deficit bike stations. Motivated by this real world bicycle repositioning problem, we study the selective pickup and delivery problem, where demand at every delivery node has to be satisfied by the supply collected from a subset of pickup nodes. The objective is to minimize the total travel cost incurred from visiting the nodes. We present a GRASP with path-relinking for solving the described problem. Experimental results show that this simple heuristic improves the existing results in the literature with an average improvement of 5.72% using small computing times. The proposed heuristic can contribute to the development of effective and efficient algorithms for real world bicycle reposition operations.
Cell-based dynamic equilibrium models are one class of dynamic traffic assignment (DTA) models th... more Cell-based dynamic equilibrium models are one class of dynamic traffic assignment (DTA) models that can capture equilibrium conditions and realistic traffic dynamics, such as queue spillback, queue formulation, and queue dissipation. However, compared with point-queue DTA models or DTA models using wholelink delay models for flow propagation, cell-based equilibrium models are often more computational demanding. This may raise issues for actual applications, in particular, for the implementation for real-time traffic control and route guidance applications, because the solution must be obtained quickly. Moreover, recent cellbased dynamic equilibrium models tend to capture more realistic travel behavior and traffic dynamics but this made the resulting models even more complicated and more difficult to solve for optimal solutions. Hence, this article aims at reviewing the recent development of cell-based dynamic equilibrium models, the formulation approaches, solution methods used, and the components of these models so as to point out the implementation issues of the latest cell-based dynamic equilibrium model with the consideration supply stochasticity for traffic control and route guidance applications as well as some gaps for future research directions.
Transportation Research Part E: Logistics and Transportation Review, 2014
We study the static bike repositioning problem We modify the problem to improve its realism and... more We study the static bike repositioning problem We modify the problem to improve its realism and reduce the solution space We solve the problem by iterated tabu search with specific operators We obtain high quality solutions efficiently *Highlights (for review)
... NH and C. Stamatiadis (2001).'Combining traffic assignment and adaptive control in a dyn... more ... NH and C. Stamatiadis (2001).'Combining traffic assignment and adaptive control in a dynamic ... Lo, H.(2002),'Trip travel time reliability in degradable transport networks', in MAP Taylor (ed ... Lo, H. and YK Tung (2003),'Network with degradable links: capacity analysis and design ...
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