Search results for: road traffic emissions

Authors: Siham G. Farag

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The main objective of this paper is to provide a new methodology for road safety assessment in Oman through the development of suitable accident prediction models. GLM technique with Poisson or NBR using SAS package was carried out to develop these models. The paper utilized the accidents data of 31 un-signalized T-intersections during three years. Five goodness-of-fit measures were used to assess the overall quality of the developed models. Two types of models were developed separately; the flow-based models including only traffic exposure functions, and the full models containing both exposure functions and other significant geometry and traffic variables. The results show that, traffic exposure functions produced much better fit to the accident data. The most effective geometric variables were major-road mean speed, minor-road 85th percentile speed, major-road lane width, distance to the nearest junction, and right-turn curb radius. The developed models can be used for intersection treatment or upgrading and specify the appropriate design parameters of T- intersections. Finally, the models presented in this thesis reflect the intersection conditions in Oman and could represent the typical conditions in several countries in the middle east area, especially gulf countries.

Keywords: accidents prediction models (APMs), generalized linear model (GLM), T-intersections, Oman

Procedia PDF Downloads 261

Authors: Vittorio Astarita, Giuseppe Guido, Vincenzo Pasquale Giofre, Alessandro Vitale

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Traffic microsimulation has been used extensively to evaluate consequences of different traffic planning and control policies in terms of travel time delays, queues, pollutant emissions, and every other common measured performance while at the same time traffic safety has not been considered in common traffic microsimulation packages as a measure of performance for different traffic scenarios. Vehicle conflict techniques that were introduced at intersections in the early traffic researches carried out at the General Motor laboratory in the USA and in the Swedish traffic conflict manual have been applied to vehicles trajectories simulated in microscopic traffic simulators. The concept is that microsimulation can be used as a base for calculating the number of conflicts that will define the safety level of a traffic scenario. This allows engineers to identify unsafe road traffic maneuvers and helps in finding the right countermeasures that can improve safety. Unfortunately, most commonly used indicators do not consider conflicts between single vehicles and roadside obstacles and barriers. A great number of vehicle crashes take place with roadside objects or obstacles. Only some recent proposed indicators have been trying to address this issue. This paper introduces a new procedure based on the simulation of potential crash events for the evaluation of safety levels in microsimulation traffic scenarios, which takes into account also potential crashes with roadside objects and barriers. The procedure can be used to define new conflict indicators. The proposed simulation procedure generates with the random perturbation of vehicle trajectories a set of potential crashes which can be evaluated accurately in terms of DeltaV, the energy of the impact, and/or expected number of injuries or casualties. The procedure can also be applied to real trajectories giving birth to new surrogate safety performance indicators, which can be considered as “simulation-based”. The methodology and a specific safety performance indicator are described and applied to a simulated test traffic scenario. Results indicate that the procedure is able to evaluate safety levels both at the intersection level and in the presence of roadside obstacles. The procedure produces results that are expressed in the same unity of measure for both vehicle to vehicle and vehicle to roadside object conflicts. The total energy for a square meter of all generated crash can be used and is shown on the map, for the test network, after the application of a threshold to evidence the most dangerous points. Without any detailed calibration of the microsimulation model and without any calibration of the parameters of the procedure (standard values have been used), it is possible to identify dangerous points. A preliminary sensitivity analysis has shown that results are not dependent on the different energy thresholds and different parameters of the procedure. This paper introduces a specific new procedure and the implementation in the form of a software package that is able to assess road safety, also considering potential conflicts with roadside objects. Some of the principles that are at the base of this specific model are discussed. The procedure can be applied on common microsimulation packages once vehicle trajectories and the positions of roadside barriers and obstacles are known. The procedure has many calibration parameters and research efforts will have to be devoted to make confrontations with real crash data in order to obtain the best parameters that have the potential of giving an accurate evaluation of the risk of any traffic scenario.

Keywords: road safety, traffic, traffic safety, traffic simulation

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Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

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Authors: P. Priya Madhuri, J. Kamini, S. C. Jayanthi

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Assessment of land use and transportation networks is essential for sustainable urban growth, urban planning, efficient public transportation systems, and reducing traffic congestion. The study focuses on land use, population density, and their correlation with the road network for future development. The scope of the study covers inventory and assessment of the road network dataset (line) at the city, zonal, or ward level, which is extracted from very high-resolution satellite data (spatial resolution < 0.5 m) at 1:4000 map scale and ground truth verification. Road network assessment is carried out by computing various indices that measure road coverage and connectivity. In this study, an assessment of the road network is carried out for the study region at the municipal and ward levels. In order to identify gaps, road coverage and connectivity were associated with urban land use, built-up area, and population density in the study area. Ward-wise road connectivity and coverage maps have been prepared. To assess the relationship between road network metrics, correlation analysis is applied. The study's conclusions are extremely beneficial for effective road network planning and detecting gaps in the road network at the ward level in association with urban land use, existing built-up, and population.

Keywords: road connectivity, road coverage, road network, urban land use, transportation analysis

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Authors: Matthew Venunye Fianu, Jerry Fiave, Ebenezer Kye-Mensah, Dacosta Aboagye, Felix Osei-Sarpong

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Introduction: Road traffic accidents involving motorbikes are a priority public health concern in Ghana. While there are local initiatives to address this public health challenge, little is known about motor riders’ knowledge and compliance with road safety regulations (RSR) and their association with RTAs. The aim of this study was, therefore, to assess motorbike riders’ knowledge and compliance with RSRs. Methodology: Motorbike riders in Hohoe Municipality were randomly sampled in a cross-sectional study in June 2022. Data were collected from 237 riders using a questionnaire designed in Kobocollect and administered by ten research assistants. A score of 70% or less is considered low for knowledge and compliance. The data were exported into Excel and imported into STATA 17 for analysis. A chi-square test was performed to generate descriptive and inferential statistics to establish the association between independent and dependent variables. Results: All 237 respondents were male, and each of them completed the questionnaire representing a 100% response rate. Participants who had knowledge about speed limit at different segments of the road were 59(24.9%), the use of helmet were 124 (52.3%), and alcohol use were 152 (64.1%). Participants who complied with regulations on speed limits, helmet use, and alcohol use were 108 (45.6%), 179(75.5%), and 168(70.8%), respectively. Riders who had at least junior high school education were 2.43 times more likely to adhere to RSR [cOR =2.43(95%CI= 1.15-6.33) p= 0.023] than those who had less education. Similarly, riders who had high knowledge about RSR were 2.07 times more likely to comply with RSR than those who had less knowledge [AOR= -2.07 (95% CI= 0.34-0.97), p=0.038]. Conclusion: Motor riders in the Hohoe Municipality had low knowledge as well as low compliance with road safety regulations. This could be a contributor to road traffic accidents. It is therefore recommended that road safety regulatory authorities and relevant stakeholders enhance the enforcement of RSR. There should also be country-specific efforts to increase awareness among all motor riders, especially those with less than junior high school education.

Keywords: compliance, motor riders, road safety regulations, road traffic accident

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Authors: Praveen Vayalamkuzhi, Veeraragavan Amirthalingam

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Studies on safety on highways are becoming the need of the hour as over 400 lives are lost every day in India due to road crashes. In order to evaluate the factors that lead to different levels of crash severity, it is necessary to investigate the level of safety of highways and their relation to crashes. In the present study, an attempt is made to identify the factors that contribute to road crashes and to quantify their effect on the severity of road crashes. The study was carried out on a four-lane divided rural highway in India. The variables considered in the analysis includes components of horizontal alignment of highway, viz., straight or curve section; time of day, driveway density, presence of median; median opening; gradient; operating speed; and annual average daily traffic. These variables were considered after a preliminary analysis. The major complexities in the study are the heterogeneous traffic and the speed variation between different classes of vehicles along the highway. To quantify the impact of each of these factors, statistical analyses were carried out using Logit model and also negative binomial regression. The output from the statistical models proved that the variables viz., horizontal components of the highway alignment; driveway density; time of day; operating speed as well as annual average daily traffic show significant relation with the severity of crashes viz., fatal as well as injury crashes. Further, the annual average daily traffic has significant effect on the severity compared to other variables. The contribution of highway horizontal components on crash severity is also significant. Logit models can predict crashes better than the negative binomial regression models. The results of the study will help the transport planners to look into these aspects at the planning stage itself in the case of highways operated under heterogeneous traffic flow condition.

Keywords: geometric design, heterogeneous traffic, road crash, statistical analysis, level of safety

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Authors: Kayijuka Idrissa

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This work investigates a mathematical study for traffic flow and traffic density in Kigali city roads and the data collected from the national police of Rwanda in 2012. While working on this topic, some mathematical models were used in order to analyze and compare traffic variables. This work has been carried out on Kigali roads specifically at roundabouts from Kigali Business Center (KBC) to Prince House as our study sites. In this project, we used some mathematical tools to analyze the data collected and to understand the relationship between traffic variables. We applied the Poisson distribution method to analyze and to know the number of accidents occurred in this section of the road which is from KBC to Prince House. The results show that the accidents that occurred in 2012 were at very high rates due to the fact that this section has a very narrow single lane on each side which leads to high congestion of vehicles, and consequently, accidents occur very frequently. Using the data of speeds and densities collected from this section of road, we found that the increment of the density results in a decrement of the speed of the vehicle. At the point where the density is equal to the jam density the speed becomes zero. The approach is promising in capturing sudden changes on flow patterns and is open to be utilized in a series of intelligent management strategies and especially in noncurrent congestion effect detection and control.

Keywords: statistical methods, traffic flow, Poisson distribution, car moving technics

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Authors: Gloria Patricia Manurung

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Jakarta Bus Rapid Transit (BRT) system which was established in 2009 to reduce private vehicle usage and ease the rush hour gridlock throughout the Jakarta Greater area, has failed to achieve its purpose. With gradually increasing the number of private vehicles ownership and reduced road space by the BRT lane construction, private vehicle users intuitively invade the exclusive lane of BRT, creating local traffic along the BRT network. Invaded BRT lanes costs become the same with the road network, making BRT which is supposed to be the main public transportation in the city becoming unreliable. Efforts to guard critical lanes with preventing the invasion by allocating traffic agents at several intersections have been expended, lead to the improving congestion level along the lane. Given a set of number of traffic agents, this study uses an analytical approach to finding the best deployment strategy of traffic agent on a simplified Jakarta road network in minimizing the BRT link cost which is expected to lead to the improvement of BRT system time reliability. User-equilibrium model of traffic assignment is used to reproduce the origin-destination demand flow on the network and the optimum solution conventionally can be obtained with brute force algorithm. This method’s main constraint is that traffic assignment simulation time escalates exponentially with the increase of set of agent’s number and network size. Our proposed metaheuristic and heuristic algorithms perform linear simulation time increase and result in minimized BRT cost approaching to brute force algorithm optimization. Further analysis of the overall network link cost should be performed to see the impact of traffic agent deployment to the network system.

Keywords: traffic assignment, user equilibrium, greedy algorithm, optimization

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Authors: A. Miškinytė, A. Dėdelė

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Road traffic is one of the main sources of air pollution in urban areas associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered as traffic-related air pollutant, which concentrations tend to be higher near highways, along busy roads and in city centres and exceedances are mainly observed in air quality monitoring stations located close to traffic. Atmospheric dispersion models can be used to examine emissions from many various sources and to predict the concentration of pollutants emitted from these sources into the atmosphere. The study aim was to compare modelled concentrations of nitrogen dioxide using ADMS-Urban dispersion model with air quality monitoring network in cold and warm seasons in Kaunas city. Modelled average seasonal concentrations of nitrogen dioxide for 2011 year have been verified with automatic air quality monitoring data from two stations in the city. Traffic station is located near high traffic street in industrial district and background station far away from the main sources of nitrogen dioxide pollution. The modelling results showed that the highest nitrogen dioxide concentration was modelled and measured in station located near intensive traffic street, both in cold and warm seasons. Modelled and measured nitrogen dioxide concentration was respectively 25.7 and 25.2 µg/m3 in cold season and 15.5 and 17.7 µg/m3 in warm season. While the lowest modelled and measured NO2 concentration was determined in background monitoring station, respectively 12.2 and 13.3 µg/m3 in cold season and 6.1 and 7.6 µg/m3 in warm season. The difference between monitoring station located near high traffic street and background monitoring station showed that better agreement between modelled and measured NO2 concentration was observed at traffic monitoring station.

Keywords: air pollution, nitrogen dioxide, modelling, ADMS-Urban model

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Authors: Christian Liebchen

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Both from an environmental perspective and with respect to road traffic flow quality, planning so-called green waves along major road axes is a well-established target for traffic engineers. For one-way road axes (e.g. the Avenues in Manhattan), this is a trivial downstream task. For bidirectional arterials, the well-known necessary condition for establishing a green wave in both directions is that the driving times between two subsequent crossings must be an integer multiple of half of the cycle time of the signal programs at the nodes. In this paper, we propose an integer linear optimization model to establish fixed-time green waves in both directions that are as long and as wide as possible, even in the situation where the driving time condition is not fulfilled. In particular, we are considering an arterial along whose nodes separate left-turn signal groups are realized. In our computational results, we show that scheduling left-turn phases before or after the straight phases can reduce waiting times along the arterial. Moreover, we show that there is always a solution with green waves in both directions that are as long and as wide as possible, where absolute priority is put on just one direction. Compared to optimizing both directions together, establishing an ideal green wave into one direction can only provide suboptimal quality when considering prioritized parts of a green band (e.g., first few seconds).

Keywords: traffic light coordination, synchronization, phase sequencing, green waves, integer programming

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Authors: Lu Zhao, Nadir Farhi, Zoi Christoforou, Nadia Haddadou

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The safety test of deploying intelligent connected vehicles (ICVs) on the road network is a critical challenge. Road traffic network simulation can be used to test the functionality of ICVs, which is not only time-saving and less energy-consuming but also can create scenarios with car collisions. However, the relationship between different human driver behaviors and the car-collision occurrences has been not understood clearly; meanwhile, the procedure of car-collisions generation in the traffic numerical simulators is not fully integrated. In this paper, we propose an approach to identify specific driver profiles from real driven data; then, we replicate them in numerical traffic simulations with the purpose of generating inter-vehicular collisions. We proposed three profiles: (i) 'aggressive': short time-headway, (ii) 'inattentive': long reaction time, and (iii) 'normal' with intermediate values of reaction time and time-headway. These three driver profiles are extracted from the NGSIM dataset and simulated using the intelligent driver model (IDM), with an extension of reaction time. At last, the generation of inter-vehicular collisions is performed by varying the percentages of different profiles.

Keywords: vehicular collisions, human driving behavior, traffic modeling, car-following models, microscopic traffic simulation

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Authors: Xuhui Lin, Qiuchen Lu, Yi An, Tao Yang

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As global climate change intensifies, extreme weather events such as floods increasingly threaten urban infrastructure, making the vulnerability of urban road networks a pressing issue. Existing static repair strategies fail to adapt to the rapid changes in road network conditions during flood events, leading to inefficient resource allocation and suboptimal recovery. The main research gap lies in the lack of repair strategies that consider both the dynamic characteristics of networks and the progression of flood propagation. This paper proposes a topology-based dynamic repair strategy that adjusts repair priorities based on real-time changes in flood propagation and traffic demand. Specifically, a novel method is developed to assess and enhance the resilience of urban road networks during flood events. The method combines road network topological analysis, flood propagation modelling, and traffic flow simulation, introducing a local importance metric to dynamically evaluate the significance of road segments across different spatial and temporal scales. Using London's road network and rainfall data as a case study, the effectiveness of this dynamic strategy is compared to traditional and Transport for London (TFL) strategies. The most significant highlight of the research is that the dynamic strategy substantially reduced the number of stranded vehicles across different traffic demand periods, improving efficiency by up to 35.2%. The advantage of this method lies in its ability to adapt in real-time to changes in network conditions, enabling more precise resource allocation and more efficient repair processes. This dynamic strategy offers significant value to urban planners, traffic management departments, and emergency response teams, helping them better respond to extreme weather events like floods, enhance overall urban resilience, and reduce economic losses and social impacts.

Keywords: Urban resilience, road networks, flood response, dynamic repair strategy, topological analysis

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Authors: Satoshi Furukawa, Satomu Morita, Katsuji Nishi, Masahito Hitosugi

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We experience the autopsy cases that the deceased was alive in emergency room on arrival. Bleeding is the leading cause of preventable death after injury. This retrospective study aimed to characterize opportunities for performance improvement identified in patients who died from traffic trauma and were considered by the quality improvement of education system. The Japan Advanced Trauma Evaluation and Care (JATEC) education program was introduced in 2002. We focused the abdominal traffic trauma injury. An autopsy-based cross-sectional study conducted. A purposive sampling technique was applied to select the study sample of 41 post-mortems of road traffic accident between April 1999 and March 2014 subjected to medico-legal autopsy at the department of Forensic Medicine, Shiga University of Medical Science. 16 patients (39.0%) were abdominal trauma injury. The mean period of survival after meet with accident was 13.5 hours, compared abdominal trauma death was 27.4 hours longer. In road traffic accidents, the most injured abdominal organs were liver followed by mesentery. We thought delayed treatment was associated with immediate diagnostic imaging, and so expected to expand trauma management examination.

Keywords: abdominal traffic trauma, preventable death, autopsy, emergency medicine

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Authors: Fares Elturki, Shaban Ismael Albrka Ali Zangena, H. A. M. Yahia

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Safety is an important consideration in the design and operation of streets and highways. Traffic and highway engineers working with law enforcement officials are constantly seeking for better methods to ensure safety for motorists and pedestrians. Also, a highway safety improvement process involves planning, implementation, and evaluation. The planning process requires that engineers collect and maintain traffic safety data, identify the hazards location, conduct studies and establish project priorities. Unfortunately, in Libya, the increase in demand for private transportation in recent years, due to poor or lack of public transportation led to some traffic problems especially in the capital (Tripoli). Also, the growth of private transportation has significant influences on the society regarding road traffic accidents (RTAs). This study investigates the most critical factors affect RTAs in Tripoli the capital city of Libya. Four main classifications 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, the targeted sample size 400 respondents include; drivers, pedestrian and passengers and relative importance index (RII) were used to rank the factors of one group and between all groups. The results show that the human factors have the most significant impacts compared with other factors. Also, 84% of respondents considered the over speeding as the most significant factor cusses of RTAs while 81% considered the disobedience to driving regulations as the second most influential factor in human factors. Also, the results showed that poor brakes or brake failure factor a great impact on the RTAs among the vehicle factors with nearly 74%, while 79% categorized 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. The environmental factors have the slights influences compared with other factors.

Keywords: road traffic accidents, Libya, vehicle factors, human factors, relative importance index

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Authors: Stig H. Jørgensen, Trond Nordfjærn, Øyvind Teige Hedenstrøm, Torbjørn Rundmo

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The aim of the paper is to estimate and forecast road traffic injuries in the coming 10-15 years given new targets in urban transport policy and shifts of mode of transport, including injury cross-effects of mode changes. The paper discusses possibilities and limitations in measuring and quantifying possible injury reductions. Injury data (killed and seriously injured road users) from six urban areas in Norway from 1998-2012 (N= 4709 casualties) form the basis for estimates of changing injury patterns. For the coming period calculation of number of injuries and injury rates by type of road user (categories of motorized versus non-motorized) by sex, age and type of road are made. A prognosticated population increase (25 %) in total population within 2025 in the six urban areas will curb the proceeded fall in injury figures. However, policy strategies and measures geared towards a stronger modal shift from use of private vehicles to safer public transport (bus, train) will modify this effect. On the other side will door to door transport (pedestrians on their way to/from public transport nodes) imply a higher exposure for pedestrians (bikers) converting from private vehicle use (including fall accidents not registered as traffic accidents). The overall effect is the sum of these modal shifts in the increasing urban population and in addition diminishing return to the majority of road safety countermeasures has also to be taken into account. The paper demonstrates how uncertainties in the various estimates (prediction factors) on increasing injuries as well as decreasing injury figures may partly offset each other. The paper discusses road safety policy and welfare consequences of transport mode shift, including reduced use of private vehicles, and further environmental impacts. In this regard, safety and environmental issues will as a rule concur. However pursuing environmental goals (e.g. improved air quality, reduced co2 emissions) encouraging more biking may generate more biking injuries. The study was given financial grants from the Norwegian Research Council’s Transport Safety Program.

Keywords: road injuries, forecasting, reduced private care use, urban, Norway

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Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

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It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

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Authors: Ramana Reddy, Vijay Kothari

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Aircraft provide a fast, reliable mode of transport with no comparable alternative for long distance travel. Throughout the years, technology improvements have been made to aircraft and engines to make them more fuel efficient. Air traffic continues to grow around the world and needs more aircrafts to accommodate such rapid growth. This has direct consequences on two of the most important environmental factors i.e. emissions and noise. Aviation contributes about 2% of global greenhouse gas emissions. Aviation emits a number of pollutants that alter the chemical composition of the atmosphere, changing its radiative balance and hence influencing the climate. In order to reduce or if possible eliminate potential harm to the environment and also make air travel efficient and economical, an environmentally beneficial concept called “Green Aviation System” is required. This is a structured frame work with elements like innovative technologies/tools in engineering design, manufacturing, airport and fleet operations.

Keywords: air traffic, environment, emissions, noise, green aviation system

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Authors: P. Kacejko, M. Wendeker

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The fuel consumption of city buses depends on a number of factors that characterize the technical properties of the bus and driver, as well as traffic conditions. This parameter related to greenhouse gas emissions is regulated by law in many countries. This applies to both fuel consumption and exhaust emissions. Simulation studies are a way to reduce the costs of optimization studies. The paper describes simulation research of fuel consumption city bus driving. Parameters of the developed model are based on experimental results obtained on chassis dynamometer test stand and road tests. The object of the study was a city bus equipped with a compression-ignition engine. The verified model was applied to simulate the behavior of a bus during the CUEDC Australian Driving Cycle. The results of the calculations showed a direct influence of driving dynamics on fuel consumption.

Keywords: Australian Driving Cycle, city bus, diesel engine, fuel consumption

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Authors: Tania Viju, Bimal P., Naseer M. A.

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This study aims to develop a conceptual framework for the decision support system (DSS), that helps the decision-makers to dynamically choose appropriate safety measures for each identified accident blackspot. An accident blackspot is a segment of road where the frequency of accident occurrence is disproportionately greater than other sections on roadways. According to a report by the World Bank, India accounts for the highest, that is, eleven percent of the global death in road accidents with just one percent of the world’s vehicles. Hence in 2015, the Ministry of Road Transport and Highways of India gave prime importance to the rectification of accident blackspots. To enhance road traffic safety and reduce the traffic accident rate, effectively identifying and rectifying accident blackspots is of great importance. This study helps to understand and evaluate the existing methods in accident blackspot identification and prediction that are used around the world and their application in Indian roadways. The decision support system, with the help of IoT, ICT and smart systems, acts as a management and planning tool for the government for employing efficient and cost-effective rectification strategies. In order to develop a decision criterion, several factors in terms of quantitative as well as qualitative data that influence the safety conditions of the road are analyzed. Factors include past accident severity data, occurrence time, light, weather and road conditions, visibility, driver conditions, junction type, land use, road markings and signs, road geometry, etc. The framework conceptualizes decision-making by classifying blackspot stretches based on factors like accident occurrence time, different climatic and road conditions and suggesting mitigation measures based on these identified factors. The decision support system will help the public administration dynamically manage and plan the necessary safety interventions required to enhance the safety of the road network.

Keywords: decision support system, dynamic management, road accident blackspots, road safety

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Authors: Ami Nkumbuye

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Background: Every year 1.3 million people die due to Road crashes, according to the Global status report. Road crashes remain the greatest killer aged between 15-29 years. Young people are paying an unacceptable price for their own safer mobility. 23,498 students attending class daily from home crossing the roads of 3 districts Kigali and Southern province is showing a similar trend with 40320 cross road daily. As most of them don't have any idea about the safety, they should have when they are crossing roads and traffic rules and signs as well. Despite the high number of mortality related to road crashes in Rwanda, we don't have any approved calendar to teach young people road safety as the most affected age group. Objective: The objective of this study was to identify the causes of road crashes and the outcome of victims after being involved in road crashes over a period of two years, from January 2020 to December 2021, in Huye district and Kigali City. Methods: A retrospective descriptive study with open questions and then data analysis, students were identified from 15 schools in Kigali City and Southern Province and through the Local Action Project supported by Global Youth Coalition for Road Safety and Youth for Road Safety (YOURS), students asked about the cause of road crashes through open and closed question and data analyzed. Result: There were 354 students from 15 schools: 198 males and 156 females. Their age ranged from 10 to 25 years. The commonest cause of road crashes among students attending schools daily was: high speed, lack of education on safe behavior on the road, drinking and driving, and poor road infrastructures, with 47%, 32%, 13% and 8 %, respectively. The hospital admission after road crashes for the victims was 32.3%. In most scenes where road crashes occur, students report that they didn't see any person who could provide post-crash care until the ambulance came, in some cases, resulted in bad outcomes for the victims after road crashes. Conclusion: This study revealed that high speed and lack of education n road safety are the major cause of road crashes among young people in Rwanda. If local Non-Governmental Organization and Decision makers work on these issues like never before, we can see a decrease in road crash among young people and adult as well. We would like to give a recommendation to two institutions: the first is the Rwanda National Police Traffic department to set 30km/m as the maximum speed limit in City and near schools. The second is for the Ministry of Education to put Road Safety and Post Crash Care curricula in both Primary and Secondary schools.

Keywords: road safety, post-crash care, young people, students

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Authors: Richard Maguire

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This research evaluates the efficiency of using mobile HEPA filters to reduce localized Particulate Matter (PM), Total Volatile Organic Chemical (TVOC) and Formaldehyde (HCHO) Air Pollution. The research is being performed using a standard HEPA filter that is tube fitted and attached to a motor vehicle. The velocity of the vehicle is used to generate the pressure difference that allows the filter to remove PM, VOC and HCOC pollution from the localized atmosphere of a road transport traffic route. The testing has been performed on a sample of traffic routes in Non-Sparse and Sparse urban environments within the UK. Pre and Post filter measuring of the PM2.5 Air Quality has been carried out along with demographics of the climate environment, including live filming of the traffic conditions. This provides a base line for future national and international research. The effectiveness measurement is generated through evaluating the difference in PM2.5 Air Quality measured pre- and post- the mobile filter test equipment. A series of further research opportunities and future exploitation options are made based on the results of the research.

Keywords: high efficiency particulate air, HEPA filter, particulate matter, traffic pollution

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Authors: Rachmat Mudiyono, Siti Sumiati

Abstract:

In the next few years, traffic will happen most of the time. This was triggered by the growing rate of vehicles againts the road capacity which is not balance. All the time the congestion in the city of Semarang has been occured at peak hours. Congestion also occured in between Teuku Umar and Setia Budi road Jatingaleh because of a plot intersection (Kesatrian intersection, PLN intersection and Jatingaleh intersection) with the Toll Road. Jatingaleh is located in the southern city of Semarang which is a central meeting point between the upper and lower Semarang where the vehicle flows in through a combination of local current and regional traffic, and the flow of vehicles coming in and out from highway. The main cause of the problems that occurred in the area of Jatingaleh is due to the numbers of vehicles movement that occurs at the intersections. With the above issues, it is necessary to analyse the existing conditions and look into some solutions. Before carrying out an analysis of field surveys at peak hours for example morning (06:00 to 08:00 am) and for the afternoon (04:00 to 06:00 pm)should be conducted, then the number of vehicles is counted manually with “short-breakcounting” according to types of vehicles. From the analysis we found that the degree of saturation (DS) is 1.61 between Teuku Umar and Setia Budi road during the morning peak hours and 1.56 during the afternoon peak hours. This means that the capacity of the existing road is no longer able to accommodate the traffic flow. One of the solutions for the congestion that occurs at the intersection of Jatingaleh is to apply the efficiency of the intersection that is not in a plot with a Fly over, Underpass and the combination of Fly Over-Underpass. Base on the flow reduction calculation with 3 comparative modeling it shows that the Fly Over is the most technically efficient to be applied in this research.

Keywords: single fly over, congestion, intersection, interchange

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Authors: Wang Qian, Bian Cheng Xiang

Abstract:

In recent years, with the improvement of China's urbanization level, the number of urban motor vehicles has grown rapidly. As residents' daily commuting necessities, cars cause a lot of exhaust emissions and urban traffic congestion. In the "Fourteenth Five Year Plan" of China, it is proposed to strive to reach the peak of carbon dioxide emissions by 2030 and achieve carbon neutrality by 2060. Urban transport accounts for a high proportion of carbon emission sources. It is an important driving force for the realization of China's carbon peak strategy. Some cities have introduced and implemented the policy of "car restriction" to solve related urban problems by reducing the use of cars. This paper analyzes the implementation of the "automobile restriction" policy, evaluates the relevant effects of the automobile restriction policy, and discusses how to better optimize the "automobile restriction" policy in the process of urban governance.

Keywords: carbon emission, traffic jams, vehicle restrictions, evaluate

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Authors: Prabhat Kashyap, Krishan Kumar

Abstract:

Delhi, the capital of India, is one of the most populated and polluted city among the world. In terms of air quality, Delhi’s air is degrading day by day & becomes worst of any major city in the world. The role of biogenic volatile organic compounds (BVOCs) is not much studied in cities like Delhi as a culprit for degraded air quality. They not only play a critical role in rural areas but also determine the atmospheric chemistry of urban areas as well. Particularly, Isoprene (2-methyl 1,3-butadiene, C5H8) is the single largest emitted compound among other BVOCs globally, that influence the tropospheric ozone chemistry in urban environment as the ozone forming potential of isoprene is very high. It is mainly emitted by vegetation & a small but significant portion is also released by vehicular exhaust of petrol operated vehicles. This study investigates the spatial and temporal variations of quantitative measurements of isoprene emissions along with different traffic tracers in 2 different seasons (post-monsoon & winter) at four different locations of Delhi. For the quantification of anthropogenic and biogenic isoprene, two sites from traffic intersections (Punjabi Bagh & CRRI) and two sites from vegetative locations (JNU & Yamuna Biodiversity Park) were selected in the vicinity of isoprene emitting tree species like Ficus religiosa, Dalbergia sissoo, Eucalyptus species etc. The concentrations of traffic tracers like benzene, toluene were also determined & their robust ratios with isoprene were used to differentiate anthropogenic isoprene with biogenic portion at each site. The ozone forming potential (OFP) of all selected species along with isoprene was also estimated. For collection of intra-day samples (3 times a day) in each season, a pre-conditioned fenceline monitoring (FLM) carbopack X thermal desorption tubes were used and further analysis was done with Gas chromatography attached with mass spectrometry (GC-MS). The results of the study proposed that the ambient air isoprene is always higher in post-monsoon season as compared to winter season at all the sites because of high temperature & intense sunlight. The maximum isoprene emission flux was always observed during afternoon hours in both seasons at all sites. The maximum isoprene concentration was found to be 13.95 ppbv at Biodiversity Park during afternoon time in post monsoon season while the lower concentration was observed as low as 0.07 ppbv at the same location during morning hours in winter season. OFP of isoprene at vegetation sites is very high during post-monsoon because of high concentrations. However, OFP for other traffic tracers were high during winter seasons & at traffic locations. Furthermore, high correlation between isoprene emissions with traffic volume at traffic sites revealed that a noteworthy share of its emission also originates from road traffic.

Keywords: biogenic VOCs, isoprene emission, anthropogenic isoprene, urban vegetation

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Authors: Celso L. Fernando, Toshio Yoshii, Takahiro Tsubota

Abstract:

Understanding the causes of a road accident and predicting their occurrence is key to preventing deaths and serious injuries from road accident events. Traditional statistical methods such as the Poisson and the Logistics regressions have been used to find the association of the traffic environmental factors with the accident occurred; recently, an artificial neural network, ANN, a computational technique that learns from historical data to make a more accurate prediction, has emerged. Although the ability to make accurate predictions, the ANN has difficulty dealing with highly unbalanced attribute patterns distribution in the training dataset; in such circumstances, the ANN treats the minority group as noise. However, in the real world data, the minority group is often the group of interest; e.g., in the road traffic accident data, the events of the accident are the group of interest. This study proposes a combination of the k-means with the ANN to improve the predictive ability of the neural network model by alleviating the effect of the unbalanced distribution of the attribute patterns in the training dataset. The results show that the proposed method improves the ability of the neural network to make a prediction on a highly unbalanced distributed attribute patterns dataset; however, on an even distributed attribute patterns dataset, the proposed method performs almost like a standard neural network.

Keywords: accident risks estimation, artificial neural network, deep learning, k-mean, road safety

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Authors: Muhammad Jahanzaib, Muhammad Z. A. Khan, Junaid Khayyam

Abstract:

Islamabad is the capital of Pakistan with the population of 1.365 million people and with a vehicular fleet size of 0.75 million. The vehicular fleet size is growing annually by the rate of 11%. Vehicular emissions are major source of Black carbon (BC). In developing countries like Pakistan, most of the vehicles consume conventional fuels like Petrol, Diesel, and CNG. These fuels are the major emitters of pollutants like CO, CO2, NOx, CH4, VOCs, and particulate matter (PM10). Carbon dioxide and methane are the leading contributor to the global warming with a global share of 9-26% and 4-9% respectively. NOx is the precursor of nitrates which ultimately form aerosols that are noxious to human health. In this study, COPERT (Computer program to Calculate Emissions from Road Transport) was used for vehicular emission estimation in Islamabad. COPERT is a windows based program which is developed for the calculation of emissions from the road transport sector. The emissions were calculated for the year of 2016 include pollutants like CO, NOx, VOC, and PM and energy consumption. The different variable was input to the model for emission estimation including meteorological parameters, average vehicular trip length and respective time duration, fleet configuration, activity data, degradation factor, and fuel effect. The estimated emissions for CO, CH4, CO2, NOx, and PM10 were found to be 9814.2, 44.9, 279196.7, 3744.2 and 304.5 tons respectively.

Keywords: COPERT Model, emission estimation, PM10, vehicular emission

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Authors: Mahshid Hatamzad, Geanette Polanco

Abstract:

Improving the performance of Winter Road Maintenance (WRM) can increase the traffic safety and reduce the cost as well as environmental impacts. This study evaluates the efficiency of WRM technique, named salting, in the Arctic area by using Data Envelopment Analysis (DEA), which is a non-parametric linear method to measure the efficiencies of decision-making units (DMUs) based on handling multiple inputs and multiple outputs at the same time that their associated weights are not known. Here, roads are considered as DMUs for which the efficiency must be determined. The three input variables considered are traffic flow, road area and WRM cost. In addition, the two output variables included are level of safety in the roads and environment impacts resulted from WRM, which is also considered as an uncontrollable factor in the second scenario. The results show the performance of DMUs from the most efficient WRM to the inefficient/least efficient one and this information provides decision makers with technical support and the required suggested improvements for inefficient WRM, in order to achieve a cost-effective WRM and a safe road transportation during wintertime in the Arctic areas.

Keywords: environmental impacts, DEA, risk and safety, WRM

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Authors: Sang-Tae Ji, Jeong-Woo Park, Jun-Ho Park, Kwang-Woo Nam

Abstract:

This study aims is to suggest the basic factors by considering the priority of intersection in the diffusion project of Smart intersection. Busan Metropolitan City is conducting a smart intersection project for efficient traffic management. The smart intersection project aims to make breakthrough improvement of the intersection congestion by optimizing the signal system using CCTV (closed-circuit television camera) image analysis technology. This study investigated trends of existing researches and analyzed by setting three things of traffic volume, characteristics of intersection road, and whether or not to conduct the main arterial road as factors for selecting new intersection when spreading smart intersection. Using this, we presented the priority of the newly installed intersection through the present situation and analysis for the Busan Metropolitan City which is the main destination of the spreading project of the smart intersection. The results of this study can be used as a consideration in the implementation of smart intersection business.

Keywords: CCTV, GIS, ICT, Smart City, smart intersection

Procedia PDF Downloads 378

Authors: Tesfaye Dagne, Dagmawit Solomon, Firmaye Bogale, Yosef Gebreyohannes, Samson Mideksa, Mamuye Hadis, Desalegn Ararso, Ermias Woldie, Tsegaye Getachew, Sabit Ababor, Zelalem Kebede

Abstract:

Globally, road traffic accident (RTA) is causing millions of deaths and injuries every year. It is one of the leading causes of death among people of all age groups and the problem is worse among young reproductive age group. Moreover the problem is increasing with an increasing number of vehicles. The majority of the problem happen in low and middle income countries (LMIC), even if the number of vehicles in these countries is low compared to their population. So, the objective of this paper is to summarize the best available evidence on interventions that can reduce road traffic accidents in low and middle income countries (LMIC). Method: A rapid evidence synthesis approach adapted from the SURE Rapid Response Service was applied to search, appraise and summarize the best available evidence on effective intervention in reducing road traffic injury. To answer the question under review, we searched for relevant studies from databases including PubMed, the Cochrane Library, TRANSPORT, Health system evidence, Epistemonikos, and SUPPORT summary. The following key terms were used for searching: Road traffic accident, RTA, Injury, Reduc*, Prevent*, Minimiz*, “Low and middle-income country”, LMIC. We found 18 articles through a search of different databases mentioned above. After screening for the titles and abstracts of the articles, four of them which satisfy the inclusion criteria were included in the final review. Then we appraised and graded the methodological quality of systematic reviews that are deemed to be highly relevant using AMSTAR. Finding: The identified interventions to reduce road traffic accidents were legislation and enforcement, public awareness/education, speed control/ rumble strips, road improvement, mandatory motorcycle helmet, graduated driver license, street lighting. Legislation and Enforcement: Legislation focusing on mandatory motorcycle helmet usage, banning cellular phone usage when driving, seat belt laws, decreasing the legal blood alcohol content (BAC) level from 0.06 g/L to 0.02 g/L bring the best result where enforcement is there. Public Awareness/Education: focusing on seat belt use, child restraint use, educational training in health centers and schools/universities, and public awareness with media through the distribution of videos, posters/souvenirs, and pamphlets are effective in the short run. Speed Control: through traffic calming bumps, or speed bumps, rumbled strips are effective in reducing accidents and fatality. Mandatory Motorcycle Helmet: is associated with reduction in mortality. Graduated driver’s license (GDL): reduce road traffic injury by 19%. Street lighting: is a low-cost intervention which may reduce road traffic accidents.

Keywords: evidence synthesis, injury, rapid review, reducing, road traffic accident

Procedia PDF Downloads 157

Authors: Xiang Li, Jian-Qiao Sun

Abstract:

As the crucial component of city traffic network, intersections have significant impacts on urban traffic performance. Despite of the rapid development in transportation systems, increasing traffic volumes result in severe congestions especially at intersections in urban areas. Effective regulation of vehicle flows at intersections has always been an important issue in the traffic control system. This study presents a multi-objective optimization method at intersections with cellular automata to achieve better traffic performance. Vehicle conflicts and pedestrian interference are considered. Three categories of the traffic performance are studied including transportation efficiency, energy consumption and road safety. The left-turn signal type, signal timing and lane assignment are optimized for different traffic flows. The multi-objective optimization problem is solved with the cell mapping method. The optimization results show the conflicting nature of different traffic performance. The influence of different traffic variables on the intersection performance is investigated. It is observed that the proposed optimization method is effective in regulating the traffic at the intersection to meet multiple objectives. Transportation efficiency can be usually improved by the permissive left-turn signal, which sacrifices safety. Right-turn traffic suffers significantly when the right-turn lanes are shared with the through vehicles. The effect of vehicle flow on the intersection performance is significant. The display pattern of the optimization results can be changed remarkably by the traffic volume variation. Pedestrians have strong interference with the traffic system.

Keywords: cellular automata, intersection, multi-objective optimization, traffic system

Procedia PDF Downloads 574