Impact of Road Traffic Characteristics on Environmental Factors Using IoT Urban Big Data

2021 ◽  
Vol 20 (5) ◽  
pp. 130-145
Author(s):  
Byeong hun Park ◽  
◽  
Dayoung Yoo ◽  
Dongjoo Park ◽  
Jungyeol Hong
Keyword(s):  
Big Data ◽  
Environmental Factors ◽  
Road Traffic ◽  
Traffic Characteristics

Influence of environmental factors on road traffic accidents: Hospital based cross sectional study at Tirupati

2018 ◽  
Vol 7 (1) ◽  
pp. 52
Author(s):  
Bayapa Reddy N. ◽  
Shakeer Kahn P. ◽  
Surendra Babu D. ◽  
Khadervali N. ◽  
Chandrasekhar C. ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Cross Sectional Study ◽  
Road Traffic Accidents ◽  
Sectional Study ◽  
Cross Sectional

scholarly journals Extracting Road Traffic Volume in the City before and during covid-19 through Video Remote Sensing

2021 ◽  
Vol 13 (12) ◽  
pp. 2329
Author(s):  
Elżbieta Macioszek ◽  
Agata Kurek
Keyword(s):  
Travel Behavior ◽  
Traffic Management ◽  
Road Traffic ◽  
Traffic Volume ◽  
The Road ◽  
Traffic Characteristics ◽  
Annual Average Daily Traffic ◽  
On The Road ◽  
The Impact ◽  
The City

Continuous, automatic measurements of road traffic volume allow the obtaining of information on daily, weekly or seasonal fluctuations in road traffic volume. They are the basis for calculating the annual average daily traffic volume, obtaining information about the relevant traffic volume, or calculating indicators for converting traffic volume from short-term measurements to average daily traffic volume. The covid-19 pandemic has contributed to extensive social and economic anomalies worldwide. In addition to the health consequences, the impact on travel behavior on the transport network was also sudden, extensive, and unpredictable. Changes in the transport behavior resulted in different values of traffic volume on the road and street network than before. The article presents road traffic volume analysis in the city before and during the restrictions related to covid-19. Selected traffic characteristics were compared for 2019 and 2020. This analysis made it possible to characterize the daily, weekly and annual variability of traffic volume in 2019 and 2020. Moreover, the article attempts to estimate daily traffic patterns at particular stages of the pandemic. These types of patterns were also constructed for the weeks in 2019 corresponding to these stages of the pandemic. Daily traffic volume distributions in 2020 were compared with the corresponding ones in 2019. The obtained results may be useful in terms of planning operational and strategic activities in the field of traffic management in the city and management in subsequent stages of a pandemic or subsequent pandemics.

scholarly journals Optimization of Planning Layout of Urban Building Based on Improved Logit and PSO Algorithms

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Yun Li ◽  
Yanping Chen ◽  
Miaoxi Zhao ◽  
Xinxin Zhai
Keyword(s):  
Big Data ◽  
Performance Index ◽  
Logit Model ◽  
Evaluation System ◽  
Road Traffic ◽  
Storage System ◽  
Pso Algorithm ◽  
Building Layout ◽  
Fitness Value ◽  
Architectural Planning

There is a huge amount of data in the opportunity of “turning waste into treasure” with the arrival of the big data age. Urban layout is very important for the development of urban transportation and building system. Once the layout of the city is finalized, it will be difficult to start again. Therefore, the urban architectural layout planning and design have a very important impact. This paper uses the urban architecture layout big data for building layout optimization using advanced computation techniques. Firstly, a big data collection and storage system based on the Hadoop platform is established. Then, the evaluation model of urban building planning based on improved logit and PSO algorithm is established. The PSO algorithm is used to find the suitable area for this kind of building layout, and then through five impact indicators: land prices, rail transit, historical protection, road traffic capacity, and commercial potential have been established by using the following logit linear regression model. Then, the bridge between logit and PSO algorithm is established by the fitness value of particle. The particle in the particle swarm is assigned to the index parameter of logit model, and then the logit model in the evaluation system is run. The performance index corresponding to the set of parameters is obtained. The performance index is passed to the PSO as the fitness value of the particle to search for the best adaptive position. The reasonable degree of regional architectural planning is obtained, and the rationality of urban architectural planning layout is determined.

Environmental factors affecting the frequency of road traffic accidents: a case study of sub-urban area of Pakistan

2019 ◽  
Vol 26 (12) ◽  
pp. 11674-11685 ◽  
Author(s):  
Hafiz Mohkum Hammad ◽  
Muhammad Ashraf ◽  
Farhat Abbas ◽  
Hafiz Faiq Bakhat ◽  
Saeed A. Qaisrani ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Urban Area ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Road Traffic Accidents ◽  
Factors Affecting

scholarly journals The Capacity of the Road Network: Data Collection and Statistical Analysis of Traffic Characteristics

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1765 ◽  
Author(s):  
Vladimir Shepelev ◽  
Sergei Aliukov ◽  
Kseniya Nikolskaya ◽  
Salavat Shabiev
Keyword(s):  
Data Collection ◽  
Road Traffic ◽  
Negative Consequences ◽  
The Road ◽  
Traffic Characteristics ◽  
Traffic Capacity ◽  
Traffic Data Collection ◽  
Fuzzy Logic Method ◽  
Additional Fuel Consumption ◽  
Additional Fuel

The possibilities of collecting the necessary information using multi-touch cameras and ways to improve road traffic data collection are considered. An increase in the number of vehicles leads to traffic jams, which in turn leads to an increase in travel time, additional fuel consumption and other negative consequences. To solve this problem, it is necessary to have a reliable information collection system and apply modern effective methods of processing the collected information. The technology considered in the article allows taking into account pedestrians crossing the intersection. The purpose of this article is to determine the most important traffic characteristics that affect the traffic capacity of the intersection, in other words, the actual number of passing cars. Throughput is taken as a dependent variable. Based on the results of the regression analysis, a model was developed to predict the intersection throughput taking into account the most important traffic characteristics. Besides, this model is based on the fuzzy logic method and using the Fuzzy TECH 5.81d Professional Edition computer program.

Evaluation and Analysis of Factors Affecting Road Traffic Accidents in Tripoli-Libya

2018 ◽  
Vol 38 ◽  
pp. 124-132
Author(s):  
Faris Ahmed Abdulfatah Elturki ◽  
Shaban Ismael Albrka Ali
Keyword(s):  
Environmental Factors ◽  
Human Factors ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Influential Factor ◽  
Road Traffic Accidents ◽  
Permanent Disability ◽  
High Exposure ◽  
Transportation Demand ◽  
The Road

Incessant of transportation demand growth in developing countries in latest years has led to several traffic issues in city areas, among the most challenging ones are vehicular emission, traffic congestion, and accidents. The growth of transportation demand has great influences, and very unfortunate impact on the society regarding crashes, death, and injuries from road accidents have reached epidemic proportions worldwide. The variation increased in speeds and vehicle density resulted in high exposure to accidents which lead loss of life and permanent disability, injury, and damage to property. This paper classified and investigate the most critical factors affect road traffic accidents (RTAs) in Tripoli the capital city of Libya. Four main categories were chosen to build the questionnaire, namely; human factors, road factors, vehicle factors and environmental factors. Moreover, a quantitative method was used to collect the data from the field, 400 respondents include; drivers, pedestrian and passengers were the sample size of the questionnaire and relative importance index (RII) were used for classification of one group and among all groups. The results show that more than 84%of respondents considered the over speeding as the most significant factor cusses of RTAs among all groups, while 81% considered the disobedience to driving code such as children who are playing with the car on the road as the most influential factor in human factors group. Also, nearly 74% of respondents seeing that poor brakes or brake failure factor has a high and considerable impact on the RTAs among the vehicle factors. Regarding the road factors group, 79% of the respondents ranked poor or no street lighting factor as one of the most effective factors on RTAs in road factors and third effecting factor concerning all factors, on the other hand, the environmental factors have the slights impacts compared with other factors.

A Multivariate Copula-Based Macro-Level Crash Count Model

2018 ◽  
Vol 2672 (30) ◽  
pp. 64-75 ◽  
Author(s):  
Shamsunnahar Yasmin ◽  
Salah Uddin Momtaz ◽  
Tammam Nashad ◽  
Naveen Eluru
Keyword(s):  
Road Traffic ◽  
Predictive Performance ◽  
Macro Level ◽  
Road User ◽  
Road Traffic Crash ◽  
Model Estimation ◽  
Frequency Model ◽  
Traffic Characteristics ◽  
The Impact ◽  
Multivariate Copula

The current study contributes to safety literature both methodologically and empirically by developing a macro-level multivariate copula-based crash frequency model for crash counts. The multivariate model accommodates for the impact of observed and unobserved effects on zonal level crash counts of different road user groups including car, light truck, van, other motorized vehicle (including truck, bus and other vehicles), and non-motorists (including pedestrians and cyclists). The proposed model is estimated using Statewide Traffic Analysis Zone (STAZ) level road traffic crash data for the state of Florida. A host of variable groups including land-use characteristics, roadway attributes, traffic characteristics, socio-economic characteristics and demographic characteristics are considered. The model estimation results illustrate the applicability of the proposed framework for multivariate crash counts. Model estimation results are further augmented by evaluation of predictive performance and policy analysis.

Sign in / Sign up

Export Citation Format

Share Document