Enhancing intelligence in traffic management systems to aid in vehicle traffic congestion problems in smart cities

2020 ◽  
Vol 107 ◽  
pp. 102265
Author(s):  
Geraldo P. Rocha Filho ◽  
Rodolfo I. Meneguette ◽  
José R. Torres Neto ◽  
Alan Valejo ◽  
Li Weigang ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Smart Cities ◽  
Management Systems ◽  
Vehicle Traffic ◽  
Congestion Problems

scholarly journals Road Traffic Congestion Management Based on a Search-Allocation Approach

2017 ◽  
Vol 18 (1) ◽  
pp. 25-33 ◽  
Author(s):  
Jamal Raiyn
Keyword(s):  
Travel Time ◽  
Real Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Self Regulation ◽  
Congestion Management ◽  
Shortest Route ◽  
Road Traffic Congestion

Abstract This paper introduces a new scheme for road traffic management in smart cities, aimed at reducing road traffic congestion. The scheme is based on a combination of searching, updating, and allocation techniques (SUA). An SUA approach is proposed to reduce the processing time for forecasting the conditions of all road sections in real-time, which is typically considerable and complex. It searches for the shortest route based on historical observations, then computes travel time forecasts based on vehicular location in real-time. Using updated information, which includes travel time forecasts and accident forecasts, the vehicle is allocated the appropriate section. The novelty of the SUA scheme lies in its updating of vehicles in every time to reduce traffic congestion. Furthermore, the SUA approach supports autonomy and management by self-regulation, which recommends its use in smart cities that support internet of things (IoT) technologies.

scholarly journals A New Approach of Smart Mobility for Heavy Goods Vehicles in Casablanca

2021 ◽  
Author(s):  
Mohammed Mouhcine Maaroufi ◽  
Laila Stour ◽  
Ali Agoumi
Keyword(s):  
Environmental Sustainability ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Smart Cities ◽  
Research Work ◽  
Transport Infrastructure ◽  
Transport Systems ◽  
Smart Mobility ◽  
Heavy Goods Vehicles

Managing mobility, both of people and goods, in cities is a thorny issue. The travel needs of urban populations are increasing and put pressure on transport infrastructure. The Moroccan cities are no exception and will struggle, in the short term, to respond to the challenges of the acceleration of the phenomenon of urbanization and the increase in demand for mobility. This will inevitably prevent them from turning into smart cities. The term smart certainly alludes to better use of technologies, but smart mobility is also defined as “a set of coordinated actions intended to improve the efficiency, effectiveness and environmental sustainability of cities” [1]. The term mobility highlights the preponderance of humans over infrastructure and vehicles. Faced with traffic congestion, the solutions currently adopted which consist of fitting out and widening the infrastructures, only encourage more trips and report the problem with more critical consequences. It is true that beyond a certain density of traffic, even Intelligent Transport Systems (ITS) are not useful. The concept of dynamic lane management or Advanced Traffic Management (ATM) opens up new perspectives. Its objective is to manage and optimize road traffic in a variable manner, in space and in time. This article is a summary of the development of a road infrastructure dedicated to Heavy Goods Vehicles (HGV), the first of its kind in Morocco. It aims to avoid the discomfort caused by trucks in the urban road network of the city of Casablanca. This research work is an opportunity to reflect on the introduction of ITS and ATM to ensure optimal use of existing infrastructure before embarking on heavy and irreversible infrastructure projects.

Dynamic Routing of Emergency Vehicles with Traffic Management System and Implementation on CupCarbon for Smart Cities

2021 ◽  
Vol 9 (11) ◽  
pp. 1407-1412
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Management System ◽  
Smart Cities ◽  
Maximum Speed ◽  
Emergency Vehicle ◽  
Traffic Light ◽  
Emergency Vehicles ◽  
Traffic Management System ◽  
On The Road

The traffic congestion is one of the major problems in crowded cities, which causes people to spend hours on the road. In traffic congestion situations, finding alternate routes for emergency vehicles, which provides shortest travel time to nearby hospital is critically life-saving issue. In this paper, we propose a traffic management system and an algorithm for routing of an emergency vehicle. The algorithm uses distance between source and destination, maximum vehicle count, maximum speed, average speed, traffic light conditions on the roads, which are assumed to support vehicle-to-infrastructure (V2I) communication in 5G IoT network. Simulations are performed on CupCarbon IoT simulator platform for various test scenarios. The performance of the proposed emergency vehicle routing algorithm is compared against well known Link State algorithm. And, the results demonstrate the effectiveness of the proposed method.

Big Data Analytics and Internet of Things for Urban Transportation

2019 ◽  
pp. 244-277
Author(s):  
Jyoti Chandiramani ◽  
Sushma Nayak
Keyword(s):  
Big Data ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Smart City ◽  
Traffic Management ◽  
Smart Cities ◽  
Big Data Analytics ◽  
Considerable Impact ◽  
The Government

The idea of smart city has assumed popularity in numerous countries across the globe. In 2015, the Government of India embarked on a mission of creating 100 smart cities to sustain the burgeoning urban population. While a wide-ranging set of fundamentals has a key role in enhancing the quality of life of citizens, the chapter revolves around transportation issues and traffic management concerns in one of India's smart cities, Pune. Transport is one of the few areas where Pune lags behind compared to its urban counterparts in the country. Public transportation in the city has been ineffectual, and auto rickshaws have been unyielding and pricey, thus making it imperative to possess personal vehicles or resort to app-based cab services. A palpable outcome of this has been traffic congestion that leads to slower travelling speeds, extended trip times, and amplified vehicular queuing. Big data and IoT can make a considerable impact in realizing the smart city objectives for efficient transportation in Pune by serving as complementary measures to supply-side policies.

A Reference Architecture for Context-Aware Intelligent Traffic Management Platforms

2018 ◽  
Vol 14 (4) ◽  
pp. 65-79
Author(s):  
Zeenat Rehena ◽  
Marijn Janssen ◽  
Samiran Chattopadhyay
Keyword(s):  
Traffic Management ◽  
Smart Cities ◽  
Data Gathering ◽  
Management Systems ◽  
Reference Architecture ◽  
The Public ◽  
Use Of Resources ◽  
Heterogeneous Datasets ◽  
Using Data ◽  
Real Time Information

Smart cities have been heralded for improving traffic management by utilizing data for making better traffic management decisions. Multi-sided platforms collect data from sensors and citizen-generated data on one side and can provide input for decision-making using data analytics by governments and the public on the other side. However, there is no guidance for creating developing Intelligent Traffic Management Systems (ITMS) platforms. The involvement of various actors having different interest and heterogeneous datasets hampers development. In this article, the authors design a reference architecture (RA) to support intelligent traffic management systems for providing better a commute, and safety and security during travel based on real-time information. The main three layers of this RA are datasets, processes, and actors. The RA for ITMS provides guidance for designing and overcoming the challenges with: 1) heterogeneous datasets; 2) data gathering; 3) data processing; 4) data management; and 5) supporting various types of data users. The illustration and evaluation of the architecture shows possible solutions of the aforementioned challenges. The RA helps to integrate the activities performed by the various actors. In this way it can be used to reduce traffic queues, increase the efficient use of resources, smooth and safe commute of the citizens.

scholarly journals Traffic congestion propagation identification method in smart cities

2021 ◽  
Vol 13 (1) ◽  
pp. 45-57
Author(s):  
Attila M. Nagy ◽  
Vilmos Simon
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Road Network ◽  
Smart Cities ◽  
Network Data ◽  
Professional Literature ◽  
Large Cities ◽  
Traffic Jam ◽  
The Road ◽  
Traffic Jams

Managing the frequent traffic congestion (traffic jams) of the road networks of large cities is a major challenge for municipal traffic management organizations. In order to manage these situations, it is crucial to understand the processes that lead to congestion and propagation, because the occurrence of a traffic jam does not merely paralyze one street or road, but could spill over onto the whole vicinity (even an entire neighborhood). Solutions can be found in professional literature, but they either oversimplify the problem, or fail to provide a scalable solution. In this article, we describe a new method that not only provides an accurate road network model, but is also a scalable solution for identifying the direction of traffic congestion propagation. Our method was subjected to a detailed performance analysis, which was based on real road network data. According to testing, our method outperforms the ones that have been used to date.

scholarly journals Traffic Management Solutions at Roadwork Zones During Planned Special Events

2021 ◽  
Vol 16 (2) ◽  
pp. 30-47
Author(s):  
Dovydas Skrodenis ◽  
Donatas Čygas ◽  
Algis Pakalnis ◽  
Andrius Kairys
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Management Systems ◽  
Traffic Flows ◽  
Flow Capacity ◽  
Special Events ◽  
Traffic Capacity ◽  
Management Scheme ◽  
Congestion Problems ◽  
Planned Special Events

Planned special events (PSEs) attract more people than usual to specific areas, which leads to increased traffic flows and congestions on the roads. Roadwork zones are among the most vulnerable areas on the roads, where increased traffic can lead to congestion. In roadwork zones, the vehicle flow capacity is already lower than in the conventional situations without roadworks, but at the time of PSEs, these zones become difficult to pass if no attention is paid to the change of the traffic management scheme. This kind of events poses many threats for road authorities, thus, new traffic management systems should be considered. This paper analyzes 2 PSEs and one national celebration in Lithuania and a significant impact they have on the regular traffic flow. PSEs are taken into consideration as they attract traffic to a known place; however, national celebrations distort traffic along all roads and it is not known exactly, which roads will be congested the most. Since roadwork zones cause congestion problems even in conventional situations, this paper presents traffic capacity calculations at these road stretches during PSEs and considers how they change depending on the traffic management scheme.

scholarly journals AN EFFICIENT INTELLIGENT TRAFFIC LIGHT CONTROL AND DEVIATION SYSTEM FOR TRAFFIC CONGESTION AVOIDANCE USING MULTI-AGENT SYSTEM

Transport ◽  
2019 ◽  
Vol 35 (3) ◽  
pp. 327-335 ◽  
Author(s):  
Rajendran Sathiyaraj ◽  
Ayyasamy Bharathi
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Ad Hoc ◽  
Road Traffic ◽  
Smart Cities ◽  
Multi Agent System ◽  
Traffic Light ◽  
Traffic Light Control ◽  
Multi Agent ◽  
Hoc Networks

An efficient and intelligent road traffic management system is the corner stone for every smart cities. Vehicular Ad-hoc NETworks (VANETs) applies the principles of mobile ad hoc networks in a wireless network for Vehicle-to-vehicle data exchange communication. VANETs supports in providing an efficient Intelligent Transportation System (ITS) for smart cities. Road traffic congestion is a most common problem faced by many of the metropolitan cities all over the world. Traffic on the road networks are widely increasing at a larger rate and the current traffic management systems is unable to tackle this impediment. In this paper, we propose an Efficient Intelligent Traffic Light Control and Deviation (EITLCD) system, which is based on multi-agent system. This proposed system overcomes the difficulties of the existing traffic management systems and avoids the traffic congestion problem compare to the prior scenario. The proposed system is composed of two systems: Traffic Light Controller (TLC) system and Traffic Light Deviation (TLD) system. The TLC system uses three agents to supervise and control the traffic parameters. TLD system deviate the vehicles before entering into congested road. Traffic and travel related information from several sensors are collected through a VANET environment to be processed by the proposed technique. The proposed structure comprises of TLC system and makes use of vehicle measurement, which is feed as input to the TLD system in a wireless network. For route pattern identification, any traditional city map can be converted to planar graph using Euler’s path approach. The proposed system is validated using Nagel–Schreckenberg model and the performance of the proposed system is proved to be better than the existing systems in terms of its time, cost, expense, maintenance and performance.

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