Tsai Yun Liao

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.

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.

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.

Smart mobility: Evaluation of demand-responsive transit systems in chiayi city

Smart City has been envisioned as one vital solution for developing cities around the world to improve living quality of cities. In spite of different definitions of Smart City, one essential element in Smart City is smart transport or smart mobility. How to improve transport through future technologies is an important issue in developing smart cities. In this study, a smart city framework for Chiayi City (Taiwan) is proposed. The framework is described in eco transportation modes, including electric bicycle, electric moped, electric vehicle, and electric bus to provide different levels of mobility. Numerical analysis based on current transit demand data is conducted to examine possible alternatives. The concept of electric bus in conjunction with demand responsive transit service is examined numerically by solving number of dispatched vehicles, capacity, and drivers. However, due to available data, cost of diesel bus is used in financial analysis as an illustration for the Chiayi City.