Inter-Vehicle Communication Protocol Design for a Yielding Decision at an Unsignalized Intersection and Evaluation of the Protocol Using Radio Control Cars Equipped with Raspberry Pi

The Japanese government aims to introduce self-driven vehicles by 2020 to reduce the number of accidents and traffic jams. Various methods have been proposed for traffic control at accident-prone intersections to achieve safe and efficient self-driving. Most of them require roadside units to identify and control vehicles. However, it is difficult to install roadside units at all intersections. This paper proposes an inter-vehicle communication protocol that enables vehicles to transmit their vehicle information and moving direction information to nearby vehicles. Vehicles identify nearby vehicles using images captured by vehicle-mounted cameras. These arrangements make it possible for vehicles to exchange yielding intention at an unsignalized intersection without using a roadside unit. To evaluate the operations of the proposed protocol, we implemented the protocol in Raspberry Pi computers, which were connected to cameras and mounted on radio control cars and conducted experiments. The experiments simulated an unsignalized intersection where both self-driven and human-driven vehicles were present. The vehicle that had sent a yielding request identified the yielding vehicle by recognizing the colour of each radio control car, which was part of the vehicle information, from the image captured by its camera. We measured a series of time needed to complete the yielding sequence and evaluated the validity of yielding decisions

Intelligent Transportation Related Complex Systems and Sensors

Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITS) are being widely adopted worldwide to improve the efficiency and safety of the transportation system. They enable users to be better informed and make safer, more coordinated, and smarter decisions on the use of transport networks. Current ITSs are complex systems, made up of several components/sub-systems characterized by time-dependent interactions among themselves. Some examples of these transportation-related complex systems include: road traffic sensors, autonomous/automated cars, smart cities, smart sensors, virtual sensors, traffic control systems, smart roads, logistics systems, smart mobility systems, and many others that are emerging from niche areas. The efficient operation of these complex systems requires: i) efficient solutions to the issues of sensors/actuators used to capture and control the physical parameters of these systems, as well as the quality of data collected from these systems; ii) tackling complexities using simulations and analytical modelling techniques; and iii) applying optimization techniques to improve the performance of these systems. It includes twenty-four papers, which cover scientific concepts, frameworks, architectures and various other ideas on analytics, trends and applications of transportation-related data