scholarly journals A model to identify urban traffic congestion hotspots in complex networks

2016 ◽  
Vol 3 (10) ◽  
pp. 160098 ◽  
Author(s):  
Albert Solé-Ribalta ◽  
Sergio Gómez ◽  
Alex Arenas
Keyword(s):  
Complex Networks ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Urban Environments ◽  
Urban Traffic ◽  
Traffic Data ◽  
Time Data ◽  
Proposed Model ◽  
And Control ◽  
Real Traffic

The rapid growth of population in urban areas is jeopardizing the mobility and air quality worldwide. One of the most notable problems arising is that of traffic congestion. With the advent of technologies able to sense real-time data about cities, and its public distribution for analysis, we are in place to forecast scenarios valuable for improvement and control. Here, we propose an idealized model, based on the critical phenomena arising in complex networks, that allows to analytically predict congestion hotspots in urban environments. Results on real cities’ road networks, considering, in some experiments, real traffic data, show that the proposed model is capable of identifying susceptible junctions that might become hotspots if mobility demand increases.

scholarly journals A Model for Sustainable Courier Services: Vehicle Routing with Exclusive Lanes

2020 ◽  
Vol 12 (3) ◽  
pp. 1077
Author(s):  
Keyju Lee ◽  
Junjae Chae ◽  
Bomi Song ◽  
Donghyun Choi
Keyword(s):  
Vehicle Routing ◽  
Carbon Emissions ◽  
Vehicle Routing Problem ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Southeast Asian ◽  
Routing Problem ◽  
Heterogeneous Fleet ◽  
Proposed Model ◽  
Asian Cities

In Southeast Asian cities, it is common for logistic companies to operate a heterogeneous fleet of delivery vehicles with motorcycles being the preferred vehicle to handle the final phase of delivery. In such scenarios, heterogeneous fleet vehicle routing problem (HFVRP) is generally applied to plan an optimal delivery. However, in many downtown cores of large and rapidly developing Southeast Asian cities, HFVRP is neither viable nor reliable because of road usage restrictions. The purpose of this article is to develop and test a different approach that accurately takes these restrictions into account and provides viable and more sustainable results. Restrictions in this paper refer to situations of urban areas in Vietnam where (i) certain vehicle types are prohibited in specified areas or where narrow alleyways limit the utilization of vehicles that exceed the road capacity and (ii) certain roads are exclusive to certain vehicle types. In networks, limited access and exclusive lanes are represented as links, or arcs, exclusive to one or another. Taking these limitations into consideration, we have developed a unique model, which we have termed Vehicle Routing Problem with Exclusive Links (VRP-EL). The model was validated and tested for its performance on scenarios with varying ratios of exclusive links. Scenarios up to 500 customers were tested on a meta-heuristic algorithm, simulated annealing. VRP-EL produces realistic outcomes. Limiting certain links to be selected according to vehicle types increases overall travel distance. However, this increase outweighs the cost of re-planning and rerouting had they not been constrained initially. The reduction in traveling distance leads to fossil fuel reduction for the overall system. The estimation of reduced carbon emissions through applying the proposed model is presented. Considering the severe traffic congestion and carbon emissions caused by motorcycles in Vietnam, the proposed model leads to a sustainable road environment.

Measuring Economic Costs of Urban Traffic Congestion to Business

2003 ◽  
Vol 1839 (1) ◽  
pp. 98-106 ◽  
Author(s):  
Glen Weisbrod ◽  
Don Vary ◽  
George Treyz
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Economic Benefits ◽  
Urban Traffic ◽  
Production Costs ◽  
Market Area ◽  
Economic Costs ◽  
Local Data ◽  
Economic Implications ◽  
Reduction Strategies

Key findings are provided from NCHRP Study 2-21, which examined how urban traffic congestion imposes economic costs within metropolitan areas. Specifically, the study applied data from Chicago and Philadelphia to examine how various producers of economic goods and services are sensitive to congestion, through its impact on business costs, productivity, and output levels. The data analysis showed that sensitivity to traffic congestion varies by industry sector and is attributable to differences in each industry sector's mix of required inputs and hence its reliance on access to skilled labor, access to specialized inputs, and access to a large, transportation-based market area. Statistical analysis models were applied with the local data to demonstrate how congestion effectively shrinks business market areas and reduces the "agglomeration economies" of businesses operating in large urban areas, thus raising production costs. Overall, this research illustrates how it is possible to estimate the economic implications of congestion, an approach that may be applied in the future for benefit-cost analysis of urban congestion-reduction strategies or for development of congestion pricing strategies. The analysis also shows how congestion-reduction strategies can induce additional traffic as a result of economic benefits.

Analysis of Trends in Data on Transit Bus Dwell Times

2017 ◽  
Vol 2619 (1) ◽  
pp. 64-74 ◽  
Author(s):  
Isaac K. Isukapati ◽  
Hana Rudová ◽  
Gregory J. Barlow ◽  
Stephen F. Smith
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Traffic Signal ◽  
Urban Traffic ◽  
Distribution Model ◽  
Signal Control ◽  
Traffic Signal Control ◽  
Real Time Control ◽  
Arrival Times ◽  
On The Road

Transit vehicles create special challenges for urban traffic signal control. Signal timing plans are typically designed for the flow of passenger vehicles, but transit vehicles—with frequent stops and uncertain dwell times—may have different flow patterns that fail to match those plans. Transit vehicles stopping on urban streets can also restrict or block other traffic on the road. This situation results in increased overall wait times and delays throughout the system for transit vehicles and other traffic. Transit signal priority (TSP) systems are often used to mitigate some of these issues, primarily by addressing delay to the transit vehicles. However, existing TSP strategies give unconditional priority to transit vehicles, exacerbating quality of service for other modes. In networks for which transit vehicles have significant effects on traffic congestion, particularly urban areas, the use of more-realistic models of transit behavior in adaptive traffic signal control could reduce delay for all modes. Estimating the arrival time of a transit vehicle at an intersection requires an accurate model of dwell times at transit stops. As a first step toward developing a model for predicting bus arrival times, this paper analyzes trends in automatic vehicle location data collected over 2 years and allows several inferences to be drawn about the statistical nature of dwell times, particularly for use in real-time control and TSP. On the basis of this trend analysis, the authors argue that an effective predictive dwell time distribution model must treat independent variables as random or stochastic regressors.

scholarly journals Traffic Efficiency Models for Urban Traffic Management Using Mobile Crowd Sensing: A Survey

2021 ◽  
Vol 13 (23) ◽  
pp. 13068
Author(s):  
Akbar Ali ◽  
Nasir Ayub ◽  
Muhammad Shiraz ◽  
Niamat Ullah ◽  
Abdullah Gani ◽  
...  
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Low Cost ◽  
Urban Traffic ◽  
Traffic Data ◽  
Mobile Crowdsensing ◽  
Traffic Efficiency ◽  
Crowd Sensing ◽  
Management Schemes ◽  
Mobile Crowd

The population is increasing rapidly, due to which the number of vehicles has increased, but the transportation system has not yet developed as development occurred in technologies. Currently, the lowest capacity and old infrastructure of roads do not support the amount of vehicles flow which cause traffic congestion. The purpose of this survey is to present the literature and propose such a realistic traffic efficiency model to collect vehicular traffic data without roadside sensor deployment and manage traffic dynamically. Today’s urban traffic congestion is one of the core problems to be solved by such a traffic management scheme. Due to traffic congestion, static control systems may stop emergency vehicles during congestion. In daily routine, there are two-time slots in which the traffic is at peak level, which causes traffic congestion to occur in an urban transportation environment. Traffic congestion mostly occurs in peak hours from 8 a.m. to 10 a.m. when people go to offices and students go to educational institutes and when they come back home from 4 p.m. to 8 p.m. The main purpose of this survey is to provide a taxonomy of different traffic management schemes for avoiding traffic congestion. The available literature categorized and classified traffic congestion in urban areas by devising a taxonomy based on the model type, sensor technology, data gathering techniques, selected road infrastructure, traffic flow model, and result verification approaches. Consider the existing urban traffic management schemes to avoid congestion and to provide an alternate path, and lay the foundation for further research based on the IoT using a Mobile crowd sensing-based traffic congestion control model. Mobile crowdsensing has attracted increasing attention in traffic prediction. In mobile crowdsensing, the vehicular traffic data are collected at a very low cost without any special sensor network infrastructure deployment. Mobile crowdsensing is very popular because it can transmit information faster, collect vehicle traffic data at a very low cost by using motorists’ smartphone or GPS vehicular embedded sensor, and it is easy to install, requires no special network deployment, has less maintenance, is compact, and is cheaper compared to other network options.

scholarly journals Understanding the Factors That Are Associated with Motorcycle Crash Severity in Rural and Urban Areas of Ghana

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
William Agyemang ◽  
Emmanuel Kofi Adanu ◽  
Steven Jones
Keyword(s):  
Rural Areas ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Urban Traffic ◽  
Sub Saharan Africa ◽  
Crash Data ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
Run Off ◽  
Sub Saharan

Like many countries in sub-Saharan Africa, Ghana has witnessed an increase in the use of motorcycles for both commercial transport and private transport of people and goods. The rapid rise in commercial motorcycle activities has been attributed to the problem of urban traffic congestion and the general lack of reliable and affordable public transport in rural areas. This study investigates and compares factors that are associated with motorcycle crash injury outcomes in rural and urban areas of Ghana. This comparison is particularly important because the commercial use of motorcycles and their rapid growth in urban areas are a new phenomenon, in contrast to rural areas where people have long relied on motorcycles for their transportation needs. Preliminary analysis of the crash data revealed that more of the rural area crashes occurred under dark and unlit roadway conditions, while urban areas recorded more intersection-related crashes. Additionally, it was found that more pedestrian collisions happened in urban areas, while head-on collisions happened more in rural areas. The model estimation results show that collisions with a pedestrian, run-off-road, and collisions that occur under dark and unlit roadway conditions were more likely to result in fatal injury. Findings from this study are expected to help in crafting and targeting appropriate countermeasures to effectively reduce the occurrence and severity of motorcycle crashes throughout the country and, indeed, sub-Saharan Africa.

Self-organization models of urban traffic lights based on digital infochemicals

SIMULATION ◽  
2018 ◽  
Vol 95 (3) ◽  
pp. 271-285 ◽  
Author(s):  
Guangyu Zou ◽  
Levent Yilmaz
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Urban Transportation ◽  
Urban Traffic ◽  
Self Organization ◽  
Traffic Lights ◽  
Traffic Systems ◽  
Signaling Strategies ◽  
Better Than ◽  
Organization Models

This paper presents a self-organizing model to design effective traffic signaling strategies in order to reduce traffic congestion in urban areas. The proposed traffic signaling system is based on a pattern model of self-organization, i.e., digital infochemicals (DIs), which are analogous to chemical substances that convey information between interactive elements mediated via the environment. In the context of traffic systems, the DIs refer to information generated by vehicles and dissipated by the urban transportation infrastructure. Based on the exploratory analysis with one single intersection, we demonstrate that the DI-based strategy performs significantly better than both the fixed and trigger-based scheduling strategies in terms of queue length and waiting time under both fixed and dynamic traffic demands.

scholarly journals The Management of Urban Freeway Traffic

1974 ◽  
Vol 1 (2) ◽  
pp. 141-149 ◽  
Author(s):  
Allen R. Cook
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Traffic Management ◽  
Control Strategies ◽  
False Alarms ◽  
Freeway Traffic ◽  
Detection Algorithms ◽  
Urban Freeway ◽  
And Control ◽  
Alternate Routes

The advent of computer-controlled electronic freeway surveillance and control systems in the past decade represents a potentially significant new operational tool for traffic engineers in large urban areas. These systems are capable of responding to rapidly changing traffic conditions and in various demonstration projects they have proven useful in maintaining an acceptable level of service for freeway operations, reducing the extent and duration of traffic congestion, minimizing the adverse effects of accidents and other incidents on traffic operations, and reducing accident experience. Surveillance system goals and techniques for achieving these goals are reviewed in this paper with particular emphasis on the problem of managing unexpected capacity-reducing incident situations. Recent research has demonstrated the feasibility of detecting incidents from traffic flow data, which is desirable for surveillance purposes because this information can be used to implement control strategies which attempt in real-time to divert some freeway traffic to alternate routes. Some of the operational problems involved with freeway traffic management are discussed, particularly the generation of false alarms by detection algorithms and driver willingness to be diverted to alternate routes.

scholarly journals Dynamic Analysis of Traffic State and Congestion Propagation on Bidirectional Grid Network

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Shu-bin Li ◽  
Bai-bai Fu ◽  
Jian-feng Zheng
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Network Performance ◽  
Simulation Software ◽  
Urban Traffic ◽  
Grid Network ◽  
Traffic State ◽  
Proposed Model ◽  
Air Pollutions ◽  
Density Relationship

Many traffic problems in China such as traffic jams and air pollutions are mainly caused by the increasing traffic volume. In order to alleviate the traffic congestion and improve the network performance, the analysis of traffic state and congestion propagation has attracted a great interest. In this paper, an improved mesoscopic traffic flow model is proposed to capture the speed-density relationship on segments, the length of queue, the flow on links, and so forth, The self-developed dynamic traffic simulation software (DynaCHINA) is used to reproduce the traffic congestion and propagation in a bidirectional grid network for different demand levels. The simulation results show that the proposed model and method are capable of capturing the real traffic states. Hence, our results can provide decision supports for the urban traffic management and planning.

scholarly journals On the Environmental and Social Sustainability of Urban Bus Transport Practices: The EU Case

2018 ◽  
Author(s):  
Cristina López ◽  
Rocío Ruíz-Benítez ◽  
Carmen Vargas-Machuca
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Business Models ◽  
Life Quality ◽  
Hierarchical Structures ◽  
Social Sustainability ◽  
Urban Environments ◽  
The European Union ◽  
Urban Bus ◽  
Bus Transport

Logistics in urban areas are currently suffering a radical transformation due to increasingly population concentration and the massive use of cars as the preferred transport mode. These issues have resulted in higher pollution levels in urban environments and traffic congestion impacting the world globally. Facilitating the use of sustainable transport modes is widely regarded as a necessity to cope with these adverse effects on citizens’ life quality. Hence, some regions, as the European Union, are encouraging bus transport firms to make their business models more environmentally and socially sustainable. The aim of this research is thus to explore how practices adopted by urban bus companies can improve cities’ sustainability. With this in mind, a combined Importance Performance Analysis (IPA)-Analytic Hierarchy Process (AHP) method was applied. In this way, both environmental and social sustainability effects of developed practices were represented through hierarchical structures separately. Subsequently, importance and performance ratings of practices in each sustainability dimension were estimated, and thus two IPA grids were generated. These grids support managers in the establishment of more effective action plans to improve logistics sustainability in cities. Findings also provide guidance to governments on the practices that should be promoted in future urban mobility plans.

Sign in / Sign up

Export Citation Format

Share Document