Nowadays, most traditional industries are facing great challenges, and so is the traditional bus industry. To design or renew a route in a metropolis cost our government a considerable amount of money, and human resource as well. Effective as it might be when being put into use, an increasing volume of data is still being neglected. In our research, we apply multi-source data analysis technique...

(ABSTRACT) Traffic congestion has been cited as the most conspicuous problem in traffic management. It has far-reaching economic, social and political effects. Intelligent Transportation Systems (ITS) research and development programs have been assigned the task of developing sophisticated techniques and counter-measures to reduce traffic congestion to manageable levels, and also achieve these ...

Today’s transportation systems have been increasingly utilizing a wide range of sensors to monitor, control, and analyze many parts of transportation system components. The sensor usage has been further accelerated by the US DOT’s emphasis on Intelligent Transportation Systems (ITS) technologies in recent years. On the other hand, while the usage of sensors has increased, archiving (or saving) ...

This paper presents the essential temporal data constructs necessary in providing solutions for transportation applications that use dynamic data, such as facility management systems, safety and incident management, transportation planning, emergency management, and intelligent transportation systems. These temporal data constructs are categorized as time stamps, temporal topology and temporal ...

The objective of this paper is to review object-oriented (OO) approaches to data modeling and data handling and their usefulness in transportation planning and modeling in general and Intelligent Transportation Systems in particular. The paper begins with a discussion of the current GIS data model for representing a transportation network and the most common database management systems used in ...

Climate change is one of the greatest environmental, economic, and social challenges of our time. Urban transportation has had a major negative impact on our environment—most of our air pollution comes from transport. This paper explores ways to move toward a more sustainable transport system by focusing on creating a more efficient and livable city and improving the environmental efficiency of...

Rapid developments of mobile technologies, data acquisition and big data analytics, and their integration with critical application domains such as transportation systems have the potential to produce more efficient, real-time, intelligent and safe transportation infrastructure. To increase the quality of transportation services, wireless sensor networks, mobile phones, crowd sourcing, RFID and...

The objective of this paper is to review object-oriented (OO) approaches to data modeling and data handling and their usefulness in transportation planning and modeling in general and Intelligent Transportation Systems in particular. The paper begins with a discussion of the current GIS data model for representing a transportation network and the most common database management systems used in ...

SHIVA (Simulated Highways for Intelligent Vehicle Algorithms) is a kinematic simulation of vehicles moving and interacting on a user-defined stretch of roadway. The vehicles can be equipped with simulated human drivers as well as sensors and algorithms for automated control. These algorithms influence the vehicles’ motion through simulated commands to the accelerator, brake and steering wheel. ...