Ta Yin Hu

An object-oriented evaluation framework for dynamic vehicle routing problems under real-time information

The dynamic vehicle routing problems (DVRP) is an extension of vehicle routing problems (VRP) in order to consider possible variations of travel times in the network. In this research, a two-stage framework for solving dynamic vehicle routing problem is proposed. In the first stage, the sweep method is adopted in vehicle assignment. In the second stage, a tabu search algorithm is implemented to improve routes under real-time information. The framework is implemented in an object-oriented approach and possible benefit from real-time information is illustrated through numerical simulation. The simulation-assignment model, DynaTAIWAN is applied in numerical simulation to evaluate real-time routing strategies in a traffic network. Numerical experiments are conducted in a 50 Nodes Network and a Taichung City. The results show that positive benefits could be achieved through utilization of real-time information with careful design.

Development and Empirical Study of Real-Time Simulation-Based Dynamic Traffic Assignment Model

This research aims at developing a system of real-time simulation-based dynamic traffic model under mixed traffic flow conditions. The system consists of two layers, namely, simulation layer and real-time control layer. The system is implemented based on rolling horizon approach, which is advanced for each stage; thus real-time data can be incorporated within the framework. In order to predict normative, as well as predictive, information, a simulation-based dynamic traffic assignment model is employed within each stage. Empirical data for a real city network, such as flows from vehicle detectors, are used to validate the model in a real-time environment. The values of mean absolute percentage error and root-mean-squared percentage error are within 15%, and the results show promising agreements between observed and simulated flows.

Flow Equilibrium Under Dynamic Traffic Assignment and Signal Control—An Illustration of Pretimed and Actuated Signal Control Policies

Under intelligent transportation systems, the interaction between signal setting and traffic assignment is an important issue in designing efficient advanced traffic management systems. Most of the studies only describe the interaction under static assumptions, which do not consider possible temporal flow distribution. These assumptions limit the applicability in real-time management and control. This paper focuses on finding equilibrium under the interaction of signal setting and traffic assignment. The problem is constructed and solved through a bi-level framework. The upper level solves for signal setting parameters based on flow distributions, including cycle length and green splits. The lower level solves for user equilibrium dynamic traffic assignment (UEDTA) flows in a traffic network. The signal setting parameters are adjusted through pretimed and actuated signal controls. UEDTA flow patterns are generated through a simulation-based dynamic traffic assignment (DTA) model, DynaTAIWAN. Numerical experiments based on a real network in Kaohsiung City, Taiwan, are conducted to study the dynamic equilibrium. The numerical results indicate the existence of equilibrium flow under signal control and route assignment in a dynamic aspect. The results show that the average travel times under the pretimed signal policy are, in general, better than the times under the actuated signal policy.

An empirical study of simulation-based dynamic traffic assignment procedures

Abstract Under Intelligent Transportation Systems (ITS), real-time operations of traffic management measures depend on long-term planning results, such as the origin–destination (OD) trip distribution; however, results from current planning procedures are unable to provide fundamental data for dynamic analysis. In order to capture dynamic traffic characteristics, transportation planning models should play an important role to integrate basic data with real-time traffic management and control. In this paper, a heuristic algorithm is proposed to establish the linkage between daily OD trips and dynamic traffic assignment (DTA) procedures; thus results from transportation planning projects, in terms of daily OD trips, can be extended to estimate time-dependent OD trips. Field data from Taiwan are collected and applied in the calibration and validation processes. Dynamic Network Assignment-Simulation Model for Advanced Road Telematics (DYNASMART-P), a simulation-based DTA model, is applied to generate time-dependent flows. The results from the validation process show high agreement between actual flows from vehicle detectors (VDs) and simulated flows from DYNAMSART-P.

Real-Time Implementation of Simulation-based Dynamic Traffic Assignment Model

This research aims at developing a real-time simulation-based dynamic traffic model for mixed traffic flow conditions for ATMS/ATIS applications. The real-time model is implemented based on rolling horizon approach. The rolling horizon is advanced for each stage, thus real-time data can be incorporated within the framework. In order to predict normative as well as predictive information, a simulation-based DTA model is employed within each stage. Empirical data for freeways, including flows from toll stations and vehicle detectors, are used to validate the model in a real-time environment.

A resilience optimization model for transportation networks under disasters

Natural and/or man-made disasters have caused serious problems in transportation systems due to their unpredictable and destructive characteristics. Under disasters, transportation infrastructure plays an important role in emergency management; however, this infrastructure is also vulnerable because of disasters. One way to describe the vulnerable is through resilience. Resilience refers to the ability to recover from a disruption under unexpected conditions, such as natural and/or man-made disasters. How to enhance resilience of transportation infrastructure under disasters is an important issue when facing natural or man-made disasters. This study aims to measure and optimize transportation resilience under disasters. An optimization model for resilience under the constraints of budget and traversal time is proposed. One special feature is that preparedness and recovery activities are implicitly considered and incorporated within the optimization model. The mathematical model provides a good connection between preparedness/recovery activities and network-level resilience. In order to illustrate the proposed model, a real city network and assumptions on activities of emergency management are used in a series of numerical experiments. Traffic conditions before and after disasters are evaluated by the simulation-assignment model, DynaTAIWAN. Experiments and results illustrate advantages for network-level transportation resilience assessment and also prioritize preparedness and recovery activities under budget constraints.

Fuel consumption and emission models development and application for advanced traffic management strategies

Due to the development of industry and commerce, the percentage of fuel consumptions and emissions of the transport sector is increasing in recent years. As a result, the levels of CO2 and other emissions have worsened the environment, and thus global-warming and air-pollution issues need to be incorporated within the planning and operation of transportation system. This research proposes two energy consumption and emission models for mixed traffic flows under a wide variety of advanced traffic management strategies. These two models are defined as the link-based and the trip-based fuel consumption and emission model. The link-based model is developed based on link characteristics, including static and dynamic attributes of the link, such as link length, number of vehicles, and average speed on links. The trip-based model calculates fuel consumption and emission based on trip characteristics, such as vehicle movement trajectory. These two models are integrated with a simulation-assignment model, DynaTAIWAN. Numerical experiments are conducted to illustrate the proposed models. Traffic management strategies, including real-time information and advanced traffic control systems, are evaluated based on the performance of fuel consumption and emission. The experiment results show the models are robust and advanced traffic management strategies can indeed reduce fuel consumption and CO2 emission.

Impact assessment of network reliability with route information under severe weather

Climate change and severe weather impacts on transportation and infrastructure have become global and environmental issues in the whole world. All human and transportation infrastructure systems are affected by climate change. Taiwan was hit by Typhoon Morakot and it caused a flood disaster in August 2009. This research focuses on the weather assessment measures of network reliability under route information. Two indexes are proposed to examine network reliability under route information, including: connectivity reliability and travel time reliability. Numerical experiments are conducted based on a real traffic network, the Jiaxian network, to illustrate the impact assessment of network reliability.

Dynamic flow equilibrium for flow-responsive signal settings and time-dependent traffic assignment

Under Intelligent Transportation Systems (ITS), the interaction between signal setting and traffic assignment is an important issue in designing efficient Advanced Traffic Management Systems (ATMS). This research focuses on finding dynamic user equilibrium between signal setting and route assignment. The problem is solved through a bi-level framework. The upper level solves for signal setting parameters based on flows, including cycle length and green splits. The lower level solves for time-dependent user equilibrium (UE) flows in a traffic network. The signal setting is adjusted through actuated signal control. Dynamic UE flow patterns are solved through a simulation-based DTA model, DynaTAIWAN. This bi-level framework can be applied in cities with signalized networks. Numerical experiments are conducted based on a subnetwork of the Kaohsiung City to study the dynamic equilibrium.

An object-oriented simulation-assignment model with consideration of mixed traffic flows for its applications

This paper aims at developing an integrated dynamic simulation-assignment model, DynaTAIWAN, for advanced traffic management systems as well as advanced traveller information systems. The model is composed of two layers, namely simulation-layer and real-time control layer. One of the key features of DynaTAIWAN is its ability to model multiple vehicle classes, especially motorcycles. Numerical experiments are conducted on two networks for illustrating possible capabilities of DynaTAIWAN