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Artificial Transportation Systems (ATS) can support a variety of computational experiments for different purposes, and have become important tools for transportation research. However, when the road network modeled in ATS is large or there are a lot of vehicles, ATS will run very slow or even cannot be started due to the memory limit of a standalone computer. With the acceleration of urbanization process and rapid increase of car ownership, it is necessary to find a high-performance computing method for running large-scale ATS. Therefore, the paper presents an Erlang-based approach to realize concurrent and distributed computing of ATS. To verify the feasibility, a prototype is built, and a performance test is conducted. The results show the method can achieve the efficiency utilization of computing resources.

On the basis of the introduction of related concepts and theories, analyze the construction process of parallel transportation system and its application in traffic signal control system. The parallel transportation system of Tailiu road is established and applied in the estimation of effectiveness, the selection of control plan, and the development trend forecast in the project of rebuilding traffic signal control system on Tailiu road. It is shown that our methods are effective in practice.

There has been an ever-increasing interest in research on traffic detection and traffic scene understanding based on computer vision, driven by the increasing processor speed and the increasing deployment of cameras. This field is of increasing relevance for the intelligent transport system (ITS). Therefore, there seems to be a real need for an analytical review of recent developments in this domain. We present here is a comprehensive review of video processing techniques state of the art for vehicle detection and tracking and an outlook to future research directions.

Evacuees' behaviors have a significant impact on evacuation efficiency. Evacuation clearance time is one of the key indicators in the evacuation planning and management. Evacuees' departure time choice, destination choice and route choice behavior based on real-time traffic information are three crucial factors used to estimate evacuation clearance time. In this paper, we use the orthogonal experimental design method to determine values of these three factors simultaneously, which can reduce evacuation clearance time significantly. Once we obtain these values, we can guide evacuees' departure time choice, destination choice and route choice behavior to approximate these values and evacuation efficiency will improve greatly. The dynamic traffic evacuation process is modeled using a rule-based multi-agent microscopic traffic simulation system called TransWorld. The simulation experiment results illustrate the effectiveness and reliability of the proposed method. The proposed methodology, computational results and discussions can be used for future emergency evacuation planning and management.

ACP (Artificial societies, Computational experiments, and Parallel execution) approach is adopted by our method to build parallel public transport system (PPTS). The framework of PPTS is proposed and some components are analyzed. Two key steps in building up PPTS are discussed. The first is growing up artificial public transport system from bottom up using agent-based technology. The second is implementing schedule plans of public vehicles using cloud computing. One specific PPTS is established for Guangzhou 2010 Asian Games. Its effectiveness is verified and illustrated by comparing the traffic parameters between before and after the employment.

Information of Activities location is critical for traffic simulation based on activity. To replace time-consuming manual acquisition, this paper proposes an information extraction method based on ontology and frequent subtree to acquire place-related information from the Web automatically. A destination selection model based on Nested Logit is established to use this information in traffic simulation. To verify the method and model, information of places within Zhongguancun area is acquired from the Web, and then experiments with uniform design are carried out on artificial transportation systems and regression analysis is done.

Artificial Transportation Systems (ATS) provide a comprehensive perspective to study actual transportation systems, which are a kind of open and complex giant system referring to diverse engineering and social disciplines. To make use of achievements from related research fields, ontology for ATS is constructed in this paper. Besides conceptual model involved in modeling and applications of ATS, the compatibility with other ontology is considered. Further, an ontological knowledge base with SOA (Service-Oriented Architecture) is designed to manage information and knowledge in ATS. The architecture and interfaces of the knowledge base are presented. Benefit from this, construction and applications of ATS can be conducted on a uniform information and knowledge platform. A case study about traffic jam pattern is demonstrated.