scholarly journals Scalable Data Model for Traffic Congestion Avoidance in a Vehicle to Cloud Infrastructure

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5074
Author(s):  
Ioan Stan ◽  
Vasile Suciu ◽  
Rodica Potolea
Keyword(s):  
Data Structures ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Negative Impact ◽  
Range Query ◽  
Data Representation ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Traffic Information ◽  
Cloud Infrastructure

Traffic congestion experience in urban areas has negative impact on our daily lives by consuming our time and resources. Intelligent Transportation Systems can provide the necessary infrastructure to mitigate such challenges. In this paper, we propose a novel and scalable solution to model, store and control traffic data based on range query data structures (K-ary Interval Tree and K-ary Entry Point Tree) which allows data representation and handling in a way that better predicts and avoids traffic congestion in urban areas. Our experiments, validation scenarios, performance measurements and solution assessment were done on Brooklyn, New York traffic congestion simulation scenario and shown the validity, reliability, performance and scalability of the proposed solution in terms of time spent in traffic, run-time and memory usage. The experiments on the proposed data structures simulated up to 10,000 vehicles having microseconds time to access traffic information and below 1.5 s for congestion free route generation in complex scenarios. To the best of our knowledge, this is the first scalable approach that can be used to predict urban traffic and avoid congestion through range query data structure traffic modelling.

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 Sensing Urban Transportation Events from Multi-Channel Social Signals with the Word2vec Fusion Model

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4093 ◽  
Author(s):  
Hao Lu ◽  
Kaize Shi ◽  
Yifan Zhu ◽  
Yisheng Lv ◽  
Zhendong Niu
Keyword(s):  
Single Channel ◽  
Low Cost ◽  
Transportation Systems ◽  
Urban Traffic ◽  
Traffic Information ◽  
Social Signals ◽  
Fusion Model ◽  
Online Data ◽  
Traffic Incidents ◽  
Traffic Incident

Social sensors perceive the real world through social media and online web services, which have the advantages of low cost and large coverage over traditional physical sensors. In intelligent transportation researches, sensing and analyzing such social signals provide a new path to monitor, control and optimize transportation systems. However, current research is largely focused on using single channel online social signals to extract and sense traffic information. Clearly, sensing and exploiting multi-channel social signals could effectively provide deeper understanding of traffic incidents. In this paper, we utilize cross-platform online data, i.e., Sina Weibo and News, as multi-channel social signals, then we propose a word2vec-based event fusion (WBEF) model for sensing, detecting, representing, linking and fusing urban traffic incidents. Thus, each traffic incident can be comprehensively described from multiple aspects, and finally the whole picture of unban traffic events can be obtained and visualized. The proposed WBEF architecture was trained by about 1.15 million multi-channel online data from Qingdao (a coastal city in China), and the experiments show our method surpasses the baseline model, achieving an 88.1% F1 score in urban traffic incident detection. The model also demonstrates its effectiveness in the open scenario test.

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.

scholarly journals KINERJA MANAJEMEN LALU LINTAS BARU DI KAWASAN LOSARI KOTA MAKASSAR

2020 ◽  
Vol 20 (1) ◽  
pp. 37-46
Author(s):  
Qadriathi Dg Bau ◽  
Ichsan Ali ◽  
Nurul Tri Ayu Reski
Keyword(s):  
Traffic Congestion ◽  
Traffic Management ◽  
Negative Impact ◽  
Service Level ◽  
Urban Traffic ◽  
Management Service ◽  
Traffic Conditions ◽  
Management Scheme ◽  
The Government ◽  
Main Thing

Abstract The problem of urban traffic congestion is the main thing that always gets attention because congestion has a negative impact on the economy, the environment, and vehicle drivers. Makassar City is one of the cities experiencing traffic congestion on several existing roads, including roads in the Losari Area. Various efforts have been made by the government to reduce traffic congestion in the area, but optimum results have not been obtained. In 2019, a change in the direction of traffic movement in the Losari area was done by implementing a traffic management called the New Traffic Management. Through this new scheme, changes are made in the direction of movement of traffic on Jalan Penghibur, Jalan Haji Bau, and Jalan Lamadukelleng. This study aims to analyze the performance of the New Traffic Management towards improving traffic conditions in the Losari Area. The results of this study indicate that the application of New Traffic Management in the Losari Area has succeeded in improving traffic conditions in the area. Through this new traffic management scheme, the three road sections observed have service level A. Keywords: traffic congestion, traffic management, service level  Abstrak Masalah kemacetan lalu lintas di perkotaan merupakan hal utama yang selalu mendapat perhatian karena kemacetan menimbulkan dampak negatif terhadap ekonomi, lingkungan, dan pengemudi kendaraan. Kota Makassar merupakan salah satu kota yang mengalami kemacetan lalu lintas di beberapa ruas jalan yang ada, termasuk jalan-jalan di kawasan Losari. Berbagai upaya telah dilakukan oleh pemerintah untuk mengurangi kemacetan lalu lintas di kawasan tersebut, tetapi belum diperoleh hasil yang optimum. Pada tahun 2019, dilakukan perubahan arah pergerakan lalu lintas di kawasan Losari dengan menerapkan suatu manajemen lalu lintas yang dinamakan Manajemen Lalu Lintas Baru atau New Traffic Management. Melalui skema yang baru ini dilakukan perubahan arah pergerakan lalu lintas di Jalan Penghibur, Jalan Haji Bau, dan Jalan Lamadu-kelleng. Penelitian ini bertujuan menganalisis kinerja Manajemen Lalu Lintas Baru ini terhadap perbaikan kondisi lalu lintas di kawasan Losari. Hasil studi ini menunjukkan bahwa penerapan Manajemen Lalu Lintas Baru di kawasan Losari berhasil memperbaiki kondisi lalu lintas di kawasan tersebut. Melalui skema manajemen lalu lintas yang baru ini, ketiga ruas jalan yang diamati mempunyai tingkat pelayanan A. Kata-kata kunci: kemacetan lalu lintas, manajemen lalu lintas, tingkat pelayanan

Road Traffic Congestion (TraCo) Estimation Using Multi-Layer Continuous Virtual Loop (MCVL)

2021 ◽  
Vol 17 (2) ◽  
pp. 46-71
Author(s):  
Manipriya Sankaranarayanan ◽  
Mala C. ◽  
Samson Mathew
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Road Traffic ◽  
Vehicle Detection ◽  
Transportation Systems ◽  
Traffic Information ◽  
Traffic Characteristics ◽  
Traffic Video ◽  
Virtual Loop

Any road traffic management application of intelligent transportation systems (ITS) requires traffic characteristics data such as vehicle density, speed, etc. This paper proposes a robust and novel vehicle detection framework known as multi-layer continuous virtual loop (MCVL) that uses computer vision techniques on road traffic video to estimate traffic characteristics. Estimations of traffic data such as speed, area occupancy and an exclusive spatial feature named as corner detail value (CDV) acquired using MCVL are proposed. Further, the estimation of traffic congestion (TraCo) level using these parameters is also presented. The performances of the entire framework and TraCo estimation are evaluated using several benchmark traffic video datasets and the results are presented. The results show that the improved accuracy in vehicle detection process using MCVL subsequently improves the precision of TraCo estimation. This also means that the proposed framework is well suited to applications that need traffic characteristics to update their traffic information system in real time.

DAMPAK PERKEMBANGAN PARIWISATA MINAT KHUSUS SNORKELING TERHADAP LINGKUNGAN: KASUS DESTINASI WISATA KARIMUNJAWA

2016 ◽  
Vol 10 (03) ◽  
pp. 13-28
Author(s):  
Sabda Elisa Priyanto
Keyword(s):  
Coral Reefs ◽  
Rural Areas ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Negative Impact ◽  
Positive Impact ◽  
Natural Habitat ◽  
Tourist Attraction ◽  
Environment Impact ◽  
The Impact

The study will analyze the impact of tourism by the type of special interest tourism to the environment. Impact on the coast and islands, the impact on vegetation, the impact wildlife, and the impact on urban areas and rural areas. Positive impact on the coast and the island is the effort for preservation and conservation of coral reefs, reef fish, giant clams and turtles, and encouraged to make environmentallyfriendly tourism activities. The negative impact is a damage to coral reefs from snorkeling activities, and the loss of traditional land allotment to the beach. The positive impact on vegetation is their attempt to biodiversity and conservation of vegetation typical of Publications, and reforestation activities is to replant mangrove. Negative impacts on vegetation is illegal logging and the clearing of trees to increase tourist attraction as supporters of the main activities. commercialization of the plant for souvenirs. Positive impact on wildlife is their conservation, preservation, and biodiversity, the breeding of animals and relocating the animals to their natural habitat. The negative impact is going hunting animals as souvenirs and tourist consumption, harassment of wildlife photography, animal exploitation for pertujukan, changes in animal instincts, and the migration of animals. Positive impact on urban areas and rural areas is happening arrangement karimunjawa towns and villages, and their empowerment. The negative impact of pressure on the land for the opening of a new tourist attraction, there are exchange in the function of residential land into commercial land, and the occurrence of traffic congestion, noise pollution, air pollution, and pollution aesthetics.  Keywords: Environmental Impact, Tourism, Snorkeling

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.

Analysis of the Influence of Traffic Information Messages on Route Selection

1995 ◽  
Vol 39 (17) ◽  
pp. 1082-1086
Author(s):  
W. Bradley Fain
Keyword(s):  
Situation Awareness ◽  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Traffic Information ◽  
Route Selection ◽  
Variable Message Signs ◽  
Message Format ◽  
Message Signs

Intelligent Transportation Systems (ITS) can reduce traffic congestion by displaying congestion-related delay information on roadside variable message signs or in-vehicle displays. Message format and content may have a significant impact on the percentage of drivers who decide to make a route diversion. In this study, the effect of various traffic information message types on driver routing decisions was evaluated. Results suggest that messages including both an advisory and a descriptive component promote situation awareness and rapid decision making, both of which are critical for this application.

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