Zhaosheng Yang

Travel Time Estimate Based on Floating Car

This paper presents a set of new methods to improve the accuracy of link travel time estimates. For map matching, signal planning is considered besides normal factors such as distance, direction and the connectivity. For link travel time estimates, virtual floating car is used to assist extracting individual link section travel time. Finally, effectiveness of the method is undertaken by actual data of Renmin Street and Ziyou Road in Changchun. Results show that map matching and individual link travel time’s precise improve by 19.5% and 21.08% respectively comparing by conventional method. And the average error of link travel time estimates is less than 10%.

Dispatching optimization and routing guidance for emergency vehicles in disaster

Based on the problem that disasters occur frequently all over the world recently. This paper aims to develop dispatching optimization and dynamical routing guidance techniques for emergency vehicles under disaster conditions, so as to reduce emergency response time and avoid further possible deterioration of disaster situation. As to dispatching for emergency vehicles, firstly, classify the casualties into several regions based on the pickup locations, quantity and severity of casualties by an adaptive spectral clustering method, and then work out dispatching strategies for emergency vehicles by k-means clustering method based on the distance among casualties regions, emergency supply stations and hospitals. As to routing guidance for emergency vehicles, centrally dynamic route guidance system based on parallel computing technology is presented to offer safe, reliable and fast routes for emergency vehicles, which are subject to the networks impedance function based on real-time forecasted travel time. Finally, the algorithms presented in this paper are validated based on the platform of ArcGIS by generating casualties randomly in random areas and damaging the simulation network of Changchun city randomly.

Design of Intelligent In-vehicle Navigation Systems for Dynamic Route Guidance with Real-time Information

In-vehicle route guidance systems (RGS) have gained significant popularity worldwide due to their promising potential to reduce many transportation-related problems such as driving-induced stress, congestion, traffic accidents, and air pollution. In this paper an implemental way to design the intelligent in-vehicle navigation systems was presented. Some key technologies such as 3D map display, speech interface and dynamic optimal path algorithm, were discussed. At last the navigation software was developed with the combination of MapX, Multigen Vega and Visual C++.

Research on the Map Matching of Typical Region Based on the Topological Analysis

Based on studying the map matching algorithms home and abroad, the paper introduced the map matching of typical region based on the topological analysis. The results of simulation on real driving data show that the map matching algorithm has the higher accuracy and can better solve the matching problem for complex road network in cities.

Support Vector Machines for Incident Detection in Urban Signalized Arterial Street Networks

An important method to solve the urban traffic congestion is to detect and identify the incident state before it becomes severity. This paper describes the development of support vector machines for urban signalized arterial streets incident detection. Input vector using two types of data: fixed detectors and probe vehicles. Incident detection is accomplished using five approaches: processing traffic input data with ARFIMA model, source data training with SVM, incident state that using to training SVM with fuzzy logic and then multiple attribute of incident state from fixed detector and probe vehicles with data fusion to decide the links and network state. Analysis data generated from a simulation of a small network are used. Different model are used to compared and evaluate the performance of the model of this paper.

Traffic Coordination and Control Model of Regional Boundary Based on Fuzzy Control

In the widely used traditional control system, traffic coordination and control between regions are neglected. Regional boundarypsilas traffic control effect has direct influence on the input traffic flow control and output traffic flow control of the regions. In this paper, a traffic coordination and control model of regional boundary based on fuzzy control is proposed. Two fuzzy controllers are designed to coordinate and control the regional boundary when traffic congestion happens. After that, a simulation network with 20 intersections and 45 links were put into VISSIM 4.2 to test the method proposed. Finally, after comparison, it comes to the conclusion that the proposed method could improve traffic condition of each region to some extent and alleviates traffic congestion.

Route Selection Model in Emergency Evacuation Based on Quasi-user Optimum Dynamic Traffic Assignment

The road network emergency evacuation means evacuating the traffic flow which is trapped to safer areas as immediately as possible, in order to bring the least impact and destruction by emergent catastrophe events. As the critical issue in emergency evacuation, aiming at the shortest evacuation time, we build a route selection model in emergency evacuation based on quasi-user optimum dynamic traffic assignment theory, and develop a constrained K-shortest paths algorithm within a dynamic restricted searching area. Efficiency and feasibility of the model and algorithm are proved by the simulation results.

Dynamic Model of Transit Signal Priority on Colored Time Petri Net

A dynamic coordination strategy model of the transit signal priority and traffic signal control cooperative system is created by using Colored Time Petri Nets (CTPNs). To extend the coordination from isolated intersections to the arterial network of intersections, a multi-level and multi-group computer supported cooperative system is described based on CTPNs. Then inter-intersection and cross-intersection coordination strategy for busses and vehicles was proposed to model transit signal priority in urban networks. INTRODUCTION Traffic management systems address the problem of reducing congestion, vehicle delay time, fuel consumption, and pollution. The most common technique to regulate and manage urban traffic areas and surface street networks is traffic signal control (Dotoli and Fanti 2006). Traffic signal control plays a central role in modern urban traffic management (Dotoli et al. 2003). Public transit, with the advantages of large capacity, reduced road occupancy, low fuel consumption and so forth, is considered to be one of the most effective ways to solve urban transportation problems (Han and Liu 2008). Transit signal priority (TSP) is a direct way to improve public transit service levels and attract residents to use public transit. In traffic control systems, general vehicle signal control and transit signal priority control share resources, resource conflicts, a tendency to deadlock and overflow, and require well-planned synchronization and scheduling. They are controlled to achieve satisfactory performance which includes reduced travel time for transit customers, improved schedule adherence and side-street traffic, and the smooth flow of traffic. (Dotoli et al. 2006). Therefore, it is of practical importance to develop, verify and, validate simple, yet powerful models that help to design and improve the safety and efficiency of traffic signal control systems. Petri nets have been proven to be a powerful modeling tool for various kinds of discrete event systems (Chung and Huang 2007). Compared with other analytical and simulation methods, Petri nets have the following advantages (Dos Santos Soares and Vrancken 2007; Wang et al. 1999): 1) Petri nets can easily express concurrency, competition, and synchronization activities among traffic, TSP and traffic control 2) Petri net modeling allows easy changes to be made to the network configuration, the traffic signal control logic, timing and coordination, and the assumptions on intersection physical layout, vehicle flow rate, turning movement, ICCTP 2009: Critical Issues in Transportation Systems Planning, Development, and Management ©2009 ASCE 1590

Research on the Coordination Optimization Method between Traffic Control and Traffic Guidance Based on Genetic Algorithm

This paper proposes a coordination optimization method between traffic control and traffic guidance so as to alleviate traffic congestion spatially and temporally. Firstly, this paper summarizes the state of art in this field and brings forward the existing problems. Secondly, considering both network equilibrium control optimization and signal timing optimization, a coordination optimization model including optimization objective function and restriction is proposed. Then, a solution algorithm based on genetic algorithm is proposed. Finally, this paper selects a region with 30 intersections in Changchun city as field test region, uses field data and simulation data to test the method. It comes a conclusion that this method could alleviate traffic congestion to some extent.

Novel Traffic Control System & Its Coordination Model based on Large-scale Systems Hierarchical Optimization Theory

Through the analysis of the existing traffic control systems, some deficiencies are found to be existed. As to these deficiencies, this paper proposes a novel traffic control system. With the help of large-scale hierarchical coordination theory, the architecture of novel traffic control system and coordination models & algorithm are proposed. After a simulation with real road network of Changchun city, the novel traffic control system and the coordination model are proved to be better than the traditional traffic control system.