Zhenjiang Li

Cloud Computing for Agent-Based Urban Transportation Systems

Agent-based traffic management systems can use the autonomy, mobility, and adaptability of mobile agents to deal with dynamic traffic environments. Cloud computing can help such systems cope with the large amounts of storage and computing resources required to use traffic strategy agents and mass transport data effectively. This article reviews the history of the development of traffic control and management systems within the evolving computing paradigm and shows the state of traffic control and management systems based on mobile multiagent technology.

A Case Study of Evaluating Traffic Signal Control Systems Using Computational Experiments

A new traffic signal control system (TSCS) evaluation method that uses computational experiments based on artificial transportation systems (ATSs) is proposed in this paper. Some basic ideas of the method are discussed, i.e., generating reasonable travel demand, modeling the influence of environment, and designing communication interface. Using a 30-day computational experiment on ATSs, a case study is carried out to evaluate three TSCSs, which are implemented using fixed-time (FT), queue-based responsive (QBR), and adaptive dynamic program (ADP) algorithms, respectively. Aside from normal weather, three types of adverse weather, i.e., rain, wind, and fog, are modeled in the computational experiment. After analyzing aggregate data and detailed operating record, reliable evaluation results are obtained from this case study. Furthermore, several interesting phenomena are observed in this case study, which have yet to be noticed by previous work.

OSGi-based service gateway architecture for intelligent automobiles

This paper describes the OSGi-based automotive specifications that improves the standard and integrates a great many existing automotive protocols and automotive networks. A key element of this specification is the OSGi-based automotive framework, which is open standard based, service-oriented infrastructure for provisioning, managing and developing telematics services. By using the technology of J2ME and extending the dynamic service deployment of OSGi, and integrating intelligent agent society, the mobile devices of automobile can access, download and use the various services from plenty of various service provider. The OSGi-based oriented-service automotive architecture is analyzed from the application and implementation points of view. Finally, the authors depict the tremendous benefits that OSGi platform technology offers in automotive networks and briefly discuss potential future work in this field.

A Fast Signal Timing Algorithm for Individual Oversaturated Intersections

In this paper, we propose a fast greedy search algorithm for optimal single-cycle signal timing at individual oversaturated intersections. We illustrate the efficiency of the algorithm with a numerical example in the literature.

A Review on Vision-Based Pedestrian Detection for Intelligent Vehicles

Vision-based pedestrian detection techniques for smart vehicles have emerged as a hot research topic in the field of vehicular electronics and driving safety. A vision-based system can recognize pedestrians in front of the moving vehicle, then warns the driver of the dangerous situation loudly or slows the vehicle down automatically to protect both drivers and pedestrians. In general, the vision-based pedestrian detection process can be divided into three consecutive steps: pedestrian detection, pedestrian recognition, and pedestrian tracking. In this paper, a great variety of methods associated with these three steps is introduced and compared in detail. In addition, the implementation of vision-based pedestrian detection on vehicles is also presented. In the end, we analyze the difficulties and the research trend in the future.

A Bibliographic Analysis of the IEEE Transactions on Intelligent Transportation Systems Literature

This paper presents a bibliographic analysis of the papers published in the IEEE Transactions on Intelligent Transportation Systems (T-ITS). We identify the most productive and high-impact authors, institutions, and countries/regions. We find that research on intelligent transportation systems is dominated by U.S. researchers and institutions and that China and Japan are the second most productive countries. According to this analysis, M. M. Trivedi, N. P. Papanikolopoulos, and P. A. Ioannou are the three most productive and influential authors in the IEEE T-ITS, whereas the Massachusetts Institute of Technology, Cambridge, the University of California, San Diego, and the University of Minnesota, Minneapolis, are three of the most productive and influential institutions in the IEEE T-ITS.

An automated vehicle counting system for traffic surveillance

The objective of this paper is to present a detailed description of using DSP board and image processing techniques to construct an automated vehicle counting system. Such a system has many potential applications, such as traffic signal control and district traffic abduction. We use TITMS320DM642 DSP as the computational unit to avoid heavy investment in industrial control computer while obtaining improved computational power and optimized system structure. The overall software is comprised of two parts: embedded DSP software and host PC software. The embedded DSP software acquires the video image from stationary cameras, detects and counts moving vehicles, and transmits the processing results and realtime images after compression to PC software through network. The host PC software works as a graphic user interface through which the end user can configure the DSP board parameters and access the video processing results. The vehicle detection and counting algorithm is carefully devised to keep robust and efficient in traffic scenes for longtime span and with changeful illumination. Experimental results show that the proposed system performs well in actual traffic scenes, and the processing speed and accuracy of the system can meet the requirement of practical applications.

An Urban Traffic Control System Based on Mobile Multi-Agents

This paper presents an urban traffic control system using the multi-agent technology, called aDAPTS for agent-based Distributed and Adaptive Platform for Transportation Systems. Based on the proposed system architecture, we divide an urban traffic system into five different functional modules and define five types of agents correspondingly. The composition and structure of each agent is discussed in detail and the correlation among them is addressed. Methods for verification and validation in artificial transportation systems are also studied in this paper.

Long short-term memory model for traffic congestion prediction with online open data

Traffic congestion in metropolitan areas has become more and more serious. Over the past decades, many academic and industrial efforts have been made to alleviate this problem, among which providing accurate, timely and predictive traffic conditions is a promising approach. Nowadays, online open data have rich traffic related information. Typical such resources include official websites of traffic management and operations, web-based map services (like Google map), weather forecasting websites, and local events (sport games, music concerts, etc.) websites. In this paper, online open data are discussed to provide traffic related information. Traffic conditions collected from web based map services are used to demonstrate the feasibility. The stacked long short-term memory model, a kind of deep architecture, is used to learn and predict the patterns of traffic conditions. Experimental results show that the proposed model for traffic condition prediction has superior performance over multilayer perceptron model, decision tree model and support vector machine model.

A Hierarchical Bus Rapid Transit System Based on Wireless Sensor Networks

Bus rapid transit (BRT) system is the key technology of intelligent transportation systems (ITS). This paper is about the research on a hierarchical BRT system based on multi-tier wireless sensor networks (WSN). It maps the features of WSN to BRT system and provides solutions for BRT technologies, such as transit signal priority.