scholarly journals Investigation on the road mortality of Anuran species on the Ikorodu-Epe/Ejirin-Ijebu Ode Roads in Lagos and Ogun States, Nigeria

2019 ◽  
Vol 37 (2) ◽  
pp. 59-70
Author(s):  
A. B Onadeko ◽  
O. S. Ogoanah
Keyword(s):  
Biological Diversity ◽  
Population Decline ◽  
Traffic Density ◽  
Vehicular Traffic ◽  
Road Mortality ◽  
Positive Direction ◽  
The Road ◽  
Anuran Species ◽  
Significant Difference ◽  
On The Road

The effect of road kills of anuran species by vehicular traffic on the Ikorodu-Epe/Ejirin-Ijebu Ode road in Lagos and Ogun States was investigated. The mean traffic density on the road during the survey (between 18:30-20:30hr and 06:00 and 07:00hr) was 127±45 vehicles/hr, which ranged between 72 and 216 vehicles/hr. A total of 738 anuran road mortalities among eight species were recorded [661 (89.6%) were identifiable, while 77 (10.4%) were not]. Ptychadena pumilio had the highest mortality of 67±27.1 individuals, while Xenopus muelleri and Aubria subsigillata were the least susceptible to road kills. This respectively represented 2.66±1.5 and 2.66±3 individuals each. Most mortality (256 individuals) occurred on the section of the road bordered by grassland/tertiary vegetation. However there was no significant difference (at P> 0.05) between the anurans killed along the different vegetation structures bordering the road (F2,21 = 0.415). About 473 live anurans belonging to five species were observed of which P. pumilio, the highest constituted the greatest number (81±42.9), while the least Hoplobatrachus occipitalis 7.3±4.2 was recorded. Both species had greater live counts than road kills compared to other anuran species that had greater road kills than live counts recorded. The greatest number of live anurans was recorded at where grassland/tertiaryvegetation occurred. This constituted a total of 198 individuals (41.8%), while the least occurred at the secondary/primaryvegetation which had 95 individuals (20%). However, the difference was not significant (F2,12 = 0.600) at P> 0.05. It is evident that anuran migration is an integral part of their biological activity. However vehicular traffic sadly possesses a negative effect on this activity. Precautionary measures are necessary to reduce population decline and possible extinction of not only the anuran species but also other wildlife species, which is a positive direction in the conservation of biological diversity.  Keywords: Vehicular traffic, anuran, mortality, vegetation, road kill, conservation 

scholarly journals Validation of CO dispersion model due to the road position on the dominant wind direction on transport sector

2018 ◽  
Vol 197 ◽  
pp. 13017 ◽  
Author(s):  
Vera Surtia Bachtiar ◽  
Purnawan ◽  
Reri Afrianita ◽  
Randa Anugerah
Keyword(s):  
Wind Direction ◽  
Dispersion Model ◽  
Transport Sector ◽  
The Road ◽  
Validation Test ◽  
Traffic Characteristics ◽  
Significant Difference ◽  
Co Concentration ◽  
On The Road ◽  
Co Dispersion

This study aims to validate CO dispersion model due to the position of the road toward the dominant wind direction on the transport sector. Sampling for modelling was done on the road with the road angle to wind direction is 0 degree (Jend. A. Yani Road), 30 degree (Andalas Road) and 60 degree (Prof. Dr. Hamka Road). CO dispersion model was obtained from the relations between CO concentration with traffic volume, traffic speed, wind speed and dominant wind direction. Sampling for validation was done at three location points, i.e. Jend. Ahmad Yani Road, By Pass Road and Dr. Wahidin Road, each of which has a position of 0, 45 and 90 degrees toward dominant wind direction. Sampling for CO was done using impinger. Measurement of traffic characteristics and meteorological conditions was performed in conjunction with CO sampling. Validation test was done by using Pearson Product Moment formula and Test of Two Variance. Results of the Two-Variance Test showed no significant difference between two concentrations of CO model and CO measurement. It showed the Test Ratio (RUf) smaller than the Critical Point. Validation test using Pearson Product Moment showed that the CO model can be used for predicting CO dispersion.

TRAFFIC FLOWS MODELING WITH INACCESSIBLE FOR DRIVING ROAD SECTIONS

2021 ◽  
pp. 19-36
Author(s):  
Anastasiya N. Zhukova ◽  
◽  
Marina S. Shapovalova ◽  
Keyword(s):  
Network Formation ◽  
Road Transport ◽  
Traffic Density ◽  
Traffic Flows ◽  
The Road ◽  
Model Modification ◽  
Road Section ◽  
Transport Line ◽  
On The Road ◽  
Python Programming

Computerized traffic modeling makes it possible to find out the modification needs to assess the traffic flow on the roads and detect likely problem areas in order to take timely measures to eliminate them. Competent preparation of a road network formation plan based on the acquired information makes it possible to reduce the load on the road transport line, avoid traffic jams, and also reduce the average time spent by drivers on the roads. The macroscopic and microscopic models of the cars flow were analyzed by authors to implement the computer model. The article considered the model of the cellular automata by Nagel–Schreckenberg, with the author’s addition that takes into account the presence of the road sections inaccessible for driving in. The need to modify the lane change algorithm was implemented: the condition of the need to change the lane when car is meeting an inaccessible road section was added. And also the “polite” drivers algorithm for bypassing inaccessible areas with a high density of the traffic flows was proposed. Such a model is realized on Python programming language. An analysis of vehicles behavior with different traffic density and location of inaccessible road sections for two- and three-lane roads was carried out based on that model modification.

Influence of Autonomous Vehicles on Car-Following Behavior of Human Drivers

2019 ◽  
Vol 2673 (12) ◽  
pp. 367-379 ◽  
Author(s):  
Yalda Rahmati ◽  
Mohammadreza Khajeh Hosseini ◽  
Alireza Talebpour ◽  
Benjamin Swain ◽  
Christopher Nelson
Keyword(s):  
Autonomous Vehicles ◽  
Simulation Models ◽  
Driving Behavior ◽  
Data Driven ◽  
Microscopic Simulation ◽  
Car Following ◽  
The Road ◽  
Human Driver ◽  
Significant Difference ◽  
On The Road

Despite numerous studies on general human–robot interactions, in the context of transportation, automated vehicle (AV)–human driver interaction is not a well-studied subject. These vehicles have fundamentally different decision-making logic compared with human drivers and the driving interactions between AVs and humans can potentially change traffic flow dynamics. Accordingly, through an experimental study, this paper investigates whether there is a difference between human–human and human–AV interactions on the road. This study focuses on car-following behavior and conducted several car-following experiments utilizing Texas A&M University’s automated Chevy Bolt. Utilizing NGSIM US-101 dataset, two scenarios for a platoon of three vehicles were considered. For both scenarios, the leader of the platoon follows a series of speed profiles extracted from the NGSIM dataset. The second vehicle in the platoon can be either another human-driven vehicle (scenario A) or an AV (scenario B). Data is collected from the third vehicle in the platoon to characterize the changes in driving behavior when following an AV. A data-driven and a model-based approach were used to identify possible changes in driving behavior from scenario A to scenario B. The findings suggested there is a statistically significant difference between human drivers’ behavior in these two scenarios and human drivers felt more comfortable following the AV. Simulation results also revealed the importance of capturing these changes in human behavior in microscopic simulation models of mixed driving environments.

scholarly journals Does the shape of the road influences wildlife roadkills? Evidence from a highway in Central Andes of Colombia

2020 ◽  
Vol 6 (1) ◽  
pp. 58-70
Author(s):  
Julián Arango Lozano ◽  
Dahian Patiño-Siro
Keyword(s):  
Central Andes ◽  
Traffic Density ◽  
Highway Infrastructure ◽  
The Road ◽  
Road Design ◽  
On The Road ◽  
Conservation Plans ◽  
Straight Lines ◽  
Transition Curves ◽  
Wildlife Mortality

Highway infrastructure is a source of multiple environmental problems, where wildlife roadkills is the most noticeable impact. Most of research in roadkills have focused in how different aspects as seasons, traffic density, location of roads, among others, have implications in the wildlife mortality on roads. However, little research have been developed on understanding how geometrical road design affects wildlife mortality. On a highway in the central Andes of Colombia, we tested whether the geometric design, it is horizontal alignment and vertical curves influence the mortality of vertebrate animals on the road. We determined the number of straight lines, circular, transition curves and vertical convex curves along the entire route of the highway (13.9 km), and between April 2018 and December 2019 we made 4 weekly tours in search of wildlife roadkills. With records, we related and compared groups of animal deaths and road shapes. We got 95 roadkills where reptile’s deaths were more than the 47% of total. We found no dependence in the distribution of deaths by Class of animals on the road shapes; the shape in which most deaths occurred was straight line (58 deaths). However, when the mortality rate per meter of route was obtained on the shape units, we found that the circular and transition curves presented two and three times (respectively) higher mortality rates than straight lines. Curved sections are presented as more dangerous geometric designs than straight lines for wildlife, regardless of their length on the road. Our research provides information necessary to take into account the relationship of geometric road design in the development of management and conservation plans of altered ecosystems with road infrastructure.

scholarly journals Tyre Weights an Overlooked Diffuse Source of Lead and Antimony to Road Runoff

2020 ◽  
Vol 12 (17) ◽  
pp. 6790
Author(s):  
Matthew Taylor ◽  
Niklas Kruger
Keyword(s):  
Urban Areas ◽  
Motor Vehicle ◽  
Environmentally Benign ◽  
Motor Vehicles ◽  
Traffic Density ◽  
Road Runoff ◽  
Diffuse Source ◽  
The Road ◽  
Roadside Dust ◽  
On The Road

Lead (Pb) remains elevated in road runoff and roadside dust, which has been attributed to legacy lead in surface soils from leaded petrol. However, “lead” tyre weights, an alloy of 95% Pb and 5% Sb, may be a relatively unrecognised diffuse source of Pb and Sb as they are still used in many countries. An unknown number of these weights drop off tyre rims and deposit on the road where they are abraded and dispersed, potentially causing adverse environmental effects. The type, number and weight of tyre weights lost from motor vehicles were characterised for a range of roading infrastructures and motor vehicle intensities in a 38 month long study of a 6.9 km length of road in Hamilton City, New Zealand. Overall, 1070 tyre weights with a combined mass of 18.6 kg were collected. About 96.4% of the collected weights were made of “lead”, which is an alloy of 95% Pb and 5% Sb, indicating tyre weights can be a major source of Pb and Sb in urban areas. The tyre weight distribution on roads used in this study depended mainly on traffic density and the prevalence of “start stop” patterns in traffic flow influenced by roundabouts and intersections. “Lead” tyre weights should be phased out and replaced with environmentally benign materials.

scholarly journals Understanding Air Pollution from Induced Traffic during and after the Construction of a New Highway: Case Study of Highway 25 in Montreal

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Md. Shohel Reza Amin ◽  
Umma Tamima ◽  
Luis Amador Jimenez
Keyword(s):  
Air Pollution ◽  
Metropolitan Area ◽  
Road Network ◽  
Traffic Density ◽  
Air Contaminants ◽  
Construction Period ◽  
Close Vicinity ◽  
The Road ◽  
On The Road

This study demonstrates through a case study that detailed analyses, even after the construction of a project, are feasible using current technologies and available data. A case study of highway 25 is used to illustrate the method and verify the levels of air contaminants from additionally induced traffic during and after the construction of highway. Natural traffic growth was removed from the effect of observed gas emissions by comparing observed levels on other further locations in the same metropolitan area. This study estimates air pollution from the additional traffic during and after the construction of A-25 extension project. NO2 levels were spatially interpolated during peak and off-peak hour traffic and traffic density simulated on the road network for four scenarios. Comparing the four scenarios, it was found that levels of NO2 concentrations were reduced at neighbor areas due to less traffic during the construction period. Levels of NO2 after the construction were higher than those in 2008. The simulated traffic density for four scenarios revealed that traffic density was significantly increased on both arterial and access roads within the close vicinity of the extension project during and after its construction.

scholarly journals Traffic Density Classification Using Twitter Data and GPS Based On Android Application

2020 ◽  
Vol 14 (2) ◽  
pp. 113
Author(s):  
Mohammad Afrizal ◽  
Idham Ananta Timur
Keyword(s):  
Public Transportation ◽  
Traffic Density ◽  
The Public ◽  
The Road ◽  
Twitter Data ◽  
Average Accuracy ◽  
Android Applications ◽  
On The Road ◽  
The City ◽  
Special Region

Increasing the number of vehicles in Special Region of Yogyakarta caused by congestion occurred at various traffic points in Special Region of Yogyakarta. The solution to reducing congestion is by increasing the use of public transportation within the city, but it still not in demand by the public. Optimizing daily activities, community always tries to avoid the traffic density on the road to be bypassed.Some research on social media has been used to detect traffic density anomalies. However, the system still cannot provide traffic density information on roads that will be passed by the user because it is just a mapping. Based on this problem, this study aims to classify the traffic density on the road that will be passed by users in the Special Region of Yogyakarta into the category of high traffic and low traffic by utilizing Twitter and GPS data.The results show that Android Applications are able to classify traffic density on the road to be traversed using Geonames.org API. Using the naïve bayes classification algorithm, the system can classify traffic density on 14 streets with an average accuracy of 77.5%, 90% precision, 79.1% recall, and 82.8% f-score.

scholarly journals Detection of Coordinate Based Accident-Prone Areas on Road Surface using Machine Learning Methods

2020 ◽  
Vol 12 (3) ◽  
pp. 19-25
Author(s):  
Anitha Kumari Dara ◽  
Dr. A. Govardhan
Keyword(s):  
Spatial Data ◽  
Surface Defects ◽  
Road Accident ◽  
Road Surface ◽  
The Other ◽  
Work Outcomes ◽  
Traffic Density ◽  
Surface Conditions ◽  
The Road ◽  
On The Road

The growth in the road networks in India and other developing countries have influenced the growth in transport industry and other industries, which depends on the road network for operations. The industries such as postal services or mover services have influenced the similar growths in these industries as well. However, the dependency of these industries is high on the road surface conditions and any deviation on the road surface conditions can also influence the performance of the services provided by the mentioned services. Nonetheless, the conditions of the road surface are one of the prime factors for road safety and number of evidences are found, which are discussed in subsequent sections of this work, that the bad road surface conditions are increasing the road accidents. Several parallel research attempts are deployed in order to find out, the regions where the road surface conditions are not proper, and the traffic density is higher. Nevertheless, outcomes of these parallel works are highly criticised due to the lack of accuracy in detection of the road surface defects, detection of accurate location of the defects and detection of the traffic density data from various sources. Thus, this work proposes a novel framework for detection of the road defect and further mapping to the spatial data coordinates resulting into the detection of the accident-prone zones or accident affinities of the roads. This work deploys a self-adjusting parametric coefficient-based regression model for detection of the risk factors of the road defects and in the other hand, extracts the traffic density of the road regions and further maps the accident affinities. This work outcomes into 97.69% accurate detection of the road accident affinity and demonstrates less complexity compared with the other parallel research outcomes

scholarly journals Perbedaan Penyerapan Pb pada Berbagai Jenis Tanaman

2020 ◽  
Vol 15 (1) ◽  
pp. 140-148
Author(s):  
Sucia Elsa Azzahri ◽  
Burhan Muslim ◽  
Muchsin Riviwanto
Keyword(s):  
Motor Vehicles ◽  
P Value ◽  
The Road ◽  
Study Approach ◽  
Significant Difference ◽  
Lead Levels ◽  
Wet Ashing ◽  
Analytical Research ◽  
The Government ◽  
On The Road

Air pollution comes from many factors, one of which comes from vehicles where the smoke produced by motor vehicles contains dangerous heavy metals, Pb. Ujung Gurun Road is one of the densely populated roads which has many pollutant-absorbing plants that line the roadside. This research was conducted with the aim to determine differences in plant types in absorbing lead content (Pb) of air on the road. Analytical research with a comparative study approach. The measurement used is the Wet Ashing Method (wet ashing) for the destruction of the sample, then analyzed using the Atomic Absorption Spectrophotometer (AAS). Data were analyzed using Anova test to see whether there were differences in Glondokan, Mahogany and Angsana plants in absorbing lead air. The results showed lead levels in leaves of glondokan plants were 0.9134 μg / g higher than leaves of mahogany plants as much as 0.764 ug / g and angsana 0.40 ug / g. There is a significant difference in the types of plants in the absorption of air Pb levels in Jalan Ujung Gurun Padang City with p value 0.002 where p <a. For this reason, the monday plant can be used as one of the plants that can be used as one of the government program plants for the absorption of Pb content of air produced by motor vehicles other than mahogany and angsana.

scholarly journals ANALYSIS OF DELAY ENTRY AND PLANNING OF PARKING GATES QMALL BANJARBARU

CERUCUK ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 121
Author(s):  
Ali Charoenplien ◽  
Puguh Budi Prakoso
Keyword(s):  
Data Analysis ◽  
Time Delay ◽  
Road Network ◽  
Field Survey ◽  
Traffic Density ◽  
Volume Data ◽  
The Road ◽  
On The Road ◽  
The Impact ◽  
Realistic Data

Qmall Banjarbaru is located at Jalan Ahmad Yani KM. 37. The existence of Qmall Banjarbaru caused the impact of increased traffic density and decreased speed in the surrounding road network. With the increasing movements that occur from Qmall Banjarbaru, it will potentially be the cause of congestion between vehicles that will enter the Qmall Banjarbaru with vehicles moving straight on Jalan Ahmad Yani KM. 37. The purpose of this research is to know the influence of delay entrance parking Qmall Banjarbaru against the performance of Jalan Ahmad Yani KM. 37.This research conducted a field survey that aims to find volume data on the road, the time of parking door service, the number of vehicles that enter the parking, the time delay the parking door, and the length of the delay that occurs on the parking door. From the results of data analysis using the Calculation of field survey (realistic) data obtained the distance of the parking door previously 16.5 meters to be redated to 25 meters and the parking door that originally had two doors of parking service made into three doors parking service. This change was made to delay enter parking Qmall Banjarbaru does not reach Jalan Ahmad Yani Km. 37.

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