Increasing Intelligence in Inter-Vehicle Communications to Reduce Traffic Congestions: Experiments in Urban and Highway Environments

Abstract

Intelligent Transportation Systems (ITS) rely on Inter-Vehicle Communication (IVC) to streamline the operation of vehicles by managing vehicle traffic, assisting drivers with safety and sharing information, as well as providing appropriate services for passengers. Traffic congestion is an urban mobility problem, which causes stress to drivers and economic losses. In this context, this work proposes a solution for the detection, dissemination and control of congested roads based on inter-vehicle communication, called INCIDEnT. The main goal of the proposed solution is to reduce the average trip time, CO emissions and fuel consumption by allowing motorists to avoid congested roads. The simulation results show that our proposed solution leads to short delays and a low overhead. Moreover, it is efficient with regard to the coverage of the event and the distance to which the information can be propagated. The findings of the investigation show that the proposed solution leads to (i) high hit rate in the classification of the level of congestion, (ii) a reduction in average trip time, (iii) a reduction in fuel consumption, and (iv) reduced CO emissions

Optimization of Transmission Signal Power through Observation of Congestion in VANets Using the Fuzzy Logic Approach: A Case Study in Highway and Urban Layout

“…These elements provide the information ubiquity and lead to transformations. This insight supports the expectation of mobile communication in vehicles as a near reality and also triggers the elaboration of intelligent and safe transportation systems transportation systems (ITS) [1,2], once the inconvenient traffic congestions cause frustrating experiences to drivers, perform a negative impact on economy, and harm the environment [3]. The initiatives with ITS benefit from the aspects underlying the innovations in processing technology, detection, and communication, contributing to the intention of providing resources to monitor traffic conditions in a region and helping to reduce congestions, as well as providing information and services for users of these systems, like drivers, and passengers [4].…”

Cooperative Automated Vehicles: A Review of Opportunities and Challenges in Socially Intelligent Vehicles Beyond Networking

“…Indeed, information from CAM messages and other map and vehicle information can be integrated in one place to enable a vehicle to reason more comprehensively about its situation. The concept of the Local Dynamic Map (LDM) 16 acts as a platform to combine static geographic information system (GIS) maps, with objects (e.g., vehicles and pedestrians) which are dynamic in nature. The work in [78] provided an LDM ontology allowing knowledgebased integration and querying of LDM knowledge to support situation awareness, e.g., to query about surrounding vehicles in safety applications.…”

A Real-Time Automatic Plate Recognition System Based on Optical Character Recognition and Wireless Sensor Networks for ITS

“…On the other hand, the development of Intelligent Transportation Systems (ITSs) is becoming a feasible solution for many current issues. ITS is the junction of various technologies that focus on service and application delivery that will monitor and manage the transportation system, making it more comfortable and secure [2].…”

“…According to Patel et al [6], the development of a conventional ALPR system can be divided into four steps: (1) vehicle capture image, (2) number plate detection, (3) character segmentation, and character recognition. The main functions of steps (1) and (2) are to detect the object (vehicle) and capture the image to find out the potential regions within the image that may contain the license plate. The discussion of the object detection algorithms is beyond the scope of this paper.…”