Computational Intelligence Inspired Data Delivery for Vehicle-to-Roadside Communications

We propose a vehicle-to-roadside communication protocol based on distributed clustering where a coalitional game approach is used to stimulate the vehicles to join a cluster, and a fuzzy logic algorithm is employed to generate stable clusters by considering multiple metrics of vehicle velocity, moving pattern, and signal qualities between vehicles. A reinforcement learning algorithm with game theory based reward allocation is employed to guide each vehicle to select the route that can maximize the whole network performance. The protocol is integrated with a multi-hop data delivery virtualization scheme that works on the top of the transport layer and provides high performance for multi-hop end-to-end data transmissions. We conduct realistic computer simulations to show the performance advantage of the protocol over other approaches

PRIORITY BASED TRAFFIC LIGHTS CONTROLLER USING WIRELESS SENSOR NETWORKS

Vehicular traffic is continuously increasing around the world, especially in large urban areas. The resulting congestion has become a major concern to transportation specialists and decision makers. The existing methods for traffic management, surveillance and control are not adequately efficient in terms of performance, cost, maintenance, and support. In this paper, the design of a system that utilizes and efficiently manages traffic light controllers is presented. In particular, we present an adaptive traffic control system based on a new traffic infrastructure using Wireless Sensor Network (WSN). These techniques are dynamically adaptive to traffic conditions on both single and multiple intersections. An intelligent traffic light controller system with a new method of vehicle detection and dynamic traffic signal time manipulation is used in the project. The project is also designed to control traffic over multiple intersections and follows international standards for traffic light operations. A central monitoring station is designed to monitor all access nodes.

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Development On Automatic Vehicle Speed Control Using Radio Frequency Technology

Reducing the rate of occurrence of road accidents is a big challenge to traffic officials and road users in various parts of the world.  These accidents mainly result from the behavior of the driver in respect to speed control while driving.  Most drivers drive vehicles at high speed even in speed limited areas and under undesirable traffic conditions without considering the safety of the public. While it is not practical to monitor all parts of the road throughout the time, it is not also possible for the traffic police to control the drivers with full effect.  The advancement in wireless sensor technology has made it possible to develop autonomous in-vehicle systems capable of effectively restricting over speeding in various traffic and road conditions. Thus, in this project, a model was proposed and developed for the control of vehicle speed system using fuzzy logic inference system in conjunction with the radio frequency identification (RFID) technology. The application of the proposed model to various road conditions and speed limits were simulated and observed using Matlab simulink toolbox. The results from the simulation showed an improvement in the vehicle speed control by over 51.4% compared to a conventional PID based vehicle speed control system

No driver, No Regulation? --Online Legal Driving Behavior Monitoring for Self-driving Vehicles

Defined traffic laws must be respected by all vehicles. However, it is essential to know which behaviors violate the current laws, especially when a responsibility issue is involved in an accident. This brings challenges of digitizing human-driver-oriented traffic laws and monitoring vehicles' behaviors continuously. To address these challenges, this paper aims to digitize traffic law comprehensively and provide an application for online monitoring of legal driving behavior for autonomous vehicles. This paper introduces a layered trigger domain-based traffic law digitization architecture with digitization-classified discussions and detailed atomic propositions for online monitoring. The principal laws on a highway and at an intersection are taken as examples, and the corresponding logic and atomic propositions are introduced in detail. Finally, the digitized traffic laws are verified on the Chinese highway and intersection datasets, and defined thresholds are further discussed according to the driving behaviors in the considered dataset. This study can help manufacturers and the government in defining specifications and laws and can also be used as a useful reference in traffic laws compliance decision-making. Source code is available on https://github.com/SOTIF-AVLab/DOTL.Comment: 22 pages, 11 figure

INTELLIGENT VEHICLE PARKING SYSTEM WITH WARNING CONTROL

This paper is about a system for assisting a car driver while parking in reverse direction. This system is used in vehicles, and continuously detects the obstacle so as to avoid accidental situation while reversing the vehicle. It makes easy for a driver to park the car in reverse direction. Driver gets immediate warning on LCD display about the obstacle. This system also gives warning to the pedestrians using buzzer while reversing the car. It not only gives warning but also apply automatic brakes when distance between an obstacle and car is below some threshold value. This is a microcontroller based system which is useful in automobiles as an intelligent vehicle assistant for safe driving. Most of the car drivers used the reverse radar or reverse camera to detect the road situation behind the vehicle when it is engaged in reverse gear. As a matter of fact, the pedestrians can virtually know if the vehicle is backing up or not only by seeing the permanent bright reverse lamps. And as there is not much change with the reverse lamp to be seen, therefore their warning function for pedestrians seems to be still insufficient eventually. Not only the warning feature of the reverse lamps is virtually not sufficient but their function will be influenced owing tothe different installation positions. Hence we propose the new technology to overcome this issue