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Road traffic congestion in the developing world
Abstract and Figures
Road traffic jams continue to remain a major problem in most cities around the world, especially in developing regions resulting in massive delays, increased fuel wastage and monetary losses. Due to the poorly planned road networks, a common outcome in many developing regions is the presence of small critical areas which are common hot-spots for congestion; poor traffic management around these hotspots potentially results in elongated traffic jams. In this paper, we first present a simple automated image processing mechanism for detecting the congestion levels in road traffic by processing CCTV camera image feeds. Our algorithm is specifically designed for noisy traffic feeds with poor image quality. Based on live CCTV camera feeds from multiple traffic signals in Kenya and Brazil, we show evidence of this congestion collapse behavior lasting long time-periods across multiple locations. To partially alleviate this problem, we present a local de-congestion protocol that coordinates traffic signal behavior within a small area and can locally prevent congestion collapse sustaining time variant traffic bursts. Based on a simulation based analysis on simple network topologies, we show that our local de-congestion protocol can enhance road capacity and prevent congestion collapse in localized settings.
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... Traffic congestion disturbs nearly everyone in the world due to the environmental damage and the transportation delay it causes [9] [13]. In Nigeria, traffic congestion in the major cities has remained part of the operating transportation systems, attempts made by governments to ensure that congestion is managed through various traffic management techniques have not yielded the desired result [10] [16]. ...
It is a well known fact that road traffic congestion has been a menace with perceived negative impact to the economic activities of our nation. To this ends, this research work aimed at investigating the Economic Implication of Road Traffic Congestion on the Economy of Kebbi State. Five objectives were specifically drafted and five corresponding research questions were formulated to guide the study. Descriptive survey research design was considered suitable for this stud. The population of the study comprised of related agencies in Birnin Kebbi Metropolis including the staff of Kebbi State Transport Authority, Kebbi State Ministry of planning and Budget commission, Ministry of Works, Housing and Transport, the Road Traffic Unit of the Nigerian Police Force, Bindawa Shopping Complex Authority Birnin Kebbi, NARTO Motor Park Official and leadership of New Garage in Birnin Kebbi. The sample for the study was 350 drawn from population area using random sampling technique. The questionnaire titled "IEIRTCEKS" was employed as the instruments. The questionnaire was administered to the respondent with aid of trained research assistance and co-researchers. SPPSS 2.1 version was used for data analysis with Four Likert scale criterion used to determine respondents response be using tables and percentages to simplify the analysis. Result from the study indicate that road traffic congestion has un-measurable impact on the economy of Kebbi State by causing a reduction in economic productivity. It leads to high fuel consumption there by increasing the cost of goods and services. It is also found to cause increase in air pollution, cost of freight movement and travelers which often leads to wastage of fuel, wear and tear of vehicle as a result, frequent repair of vehicles eminent. I was however recommended that the state government should rehabilitate the bad road that causes the traffic congestion throughout the state and that strict condition should be put in place to reduce traffic congestion in areas which can easily be over crowded.
... Traffic congestion disturbs nearly everyone in the world due to the environmental damage and the transportation delay it causes [9] [13]. In Nigeria, traffic congestion in the major cities has remained part of the operating transportation systems, attempts made by governments to ensure that congestion is managed through various traffic management techniques have not yielded the desired result [10] [16]. ...
It is a well known fact that road traffic congestion has been a menace with perceived negative impact to the economic activities of our nation. To this ends, this research work aimed at investigating the Economic Implication of Road Traffic Congestion on the Economy of Kebbi State. Five objectives were specifically drafted and five corresponding research questions were formulated to guide the study. Descriptive survey research design was considered suitable for this stud. The population of the study comprised of related agencies in Birnin Kebbi Metropolis including the staff of Kebbi State Transport Authority, Kebbi State Ministry of planning and Budget commission, Ministry of Works, Housing and Transport, the Road Traffic Unit of the Nigerian Police Force, Bindawa Shopping Complex Authority Birnin Kebbi, NARTO Motor Park Official and leadership of New Garage in Birnin Kebbi. The sample for the study was 350 drawn from population area using random sampling technique. The questionnaire titled "IEIRTCEKS" was employed as the instruments. The questionnaire was administered to the respondent with aid of trained research assistance and co-researchers. SPPSS 2.1 version was used for data analysis with Four Likert scale criterion used to determine respondents response be using tables and percentages to simplify the analysis. Result from the study indicate that road traffic congestion has un-measurable impact on the economy of Kebbi State by causing a reduction in economic productivity. It leads to high fuel consumption there by increasing the cost of goods and services. It is also found to cause increase in air pollution, cost of freight movement and travelers which often leads to wastage of fuel, wear and tear of vehicle as a result, frequent repair of vehicles eminent. I was however recommended that the state government should rehabilitate the bad road that causes the traffic congestion throughout the state and that strict condition should be put in place to reduce traffic congestion in areas which can easily be over crowded.
... Menurut Jain (2012:2) menjelaskan bahwa alasan kemacetan yang pada umumnya terjadi di dunia, yaitu: (1) Unplanned cities (kota tanpa perencanaan), kondisi dimana kota tidak memiliki perencanaan skala kapasitas jalan, sehingga jika pada jangka waktu yang lama terjadi peningkatan jumlah populasi, lebar jalan tidak dapat menampung kebutuhan. Hal ini terjadi akibat kegagalan konvensional stategi manajemen jalan; (2) Poor discipline (Rendahnya kedisiplinan), rendahnya kedisplinan pengguna jalan; (3) Alternate traffic (Lalu lintas cadangan), kondisi dimana kota-kota jarang memiliki sistem transportasi massal yang efisien, sehingga memaksa masyarakat untuk mengoperasikan kendaraan pribadi. ...
Research Study Club Fakultas Ilmu Administrasi Universitas Brawijaya Malang Jl. MT Haryono 163, Malang 65145 Telp. 5537373 Fax. 553737 1 ABSTRAK Meningkatnya kemacetan di Kota Malang mendorong dilakukannya penetapan Rencana Sistem Jaringan Jalan untuk mengatasi masalah ini. Dalam hal ini, yaitu wilayah sekitar Jalan Kolonel Sugiono, dimana kondisi wilayah sekitar Jalan Kolonel Sugiono diperparah dengan adanya Terminal Gadang yang berdekatan dengan Pasar Induk Gadang. Tujuan penelitian ini adalah mengetahui dan menjelaskan implementasi kebijakan perpindahan Terminal Gadang ke Terminal Hamid Rusdi di Kota Malang. Jenis penelitian ini adalah deskriptif dengan pendekatan kualitatif. Implementasi kebijakan perpindahan Terminal Gadang ke Terminal Hamid Rusdi dalam penelitian ini difokuskan pada pengaruh kinerja kebijakan yang meliputi: ukuran dan tujuan kebijakan, sumber daya dalam implementasi kebijakan, karakteristik agen pelaksana kebijakan, sikap/kecenderuangan para pelaksana kebijakan, komunikasi antarorganisasi dan aktifitas pelaksana kebijakan, lingkungan ekonomi, sosial dan politik yang mempengaruhi implementasi kebijakan. Hasil penelitian menunjukkan bahwa perpindahan Terminal Gadang ke Terminal Hamid Rusid memiliki kendala dalam sumber daya khususnya sumber daya alat dan manusia yaitu infrastruktur pendukung kelancaran operasi terminal, seperti jalan raya dan koordinasi antar aktor, sehingga solusi dalam masalah implementasi kebijakan ini, yaitu percepatan pembangunan infrastruktur jalan di lingkar timur Kota Malang. ABSTRACT Increasing stagnation in cities unfortunate encourage the establishment plan of the road network system to solve this problem. In this case, the area around Kolonel Sugiono street, where the condition of the area around the Kolonel Sugiono street exacerbated by the large sieve bus station adjacent to the main Gadang Market. The purpose of this research was to determine and describes the implementation of the resettlement policy of Gadang Bus station to Hamid Rusdi Bus Station in Malang. This type of research is descriptive qualitative approach. Policy implementation displacement of Gadang Bus station to Hamid Rusdi Bus Station have constraint in human resources and tools resources that support the operation of the bus station infrastructure such as highway and coordination among actors. So that solutions in problems of implementating this policy, namely the acceleration of infrastructure development in the east ring road of Malang City.
... Due to the widespread use of private automobiles, which affects how people move and shapes the design of cities themselves, the global urban transport sector is currently at a critical crossroads. Whether a country is developed or not, traffic congestion has been on the rise and will only worsen, endangering the quality of urban life (Jain, Sharma & Subramanian, 2012). Between 2005 and 2050, 2.3 billion new cars are anticipated globally at the current rate of motorization, with more than 80% of those cars likely to wind up on the roads of emerging nations (Chamon, Mauro & Okawa, 2008). ...
This research aimed to analyze the economic and environmental impacts of traffic congestion in Addis Ababa, the case of Ayat-Mexico road corridor, one of the city's busiest road corridors. To this end, a survey research design was employed, and 384 sample passengers were taken using convenient sampling. The data were collected primarily using a questionnaire and substantiated by interviews and document review. Then the data were analyzed using descriptive statistics such as frequency, mean and standard deviation. Based on the findings of the vstudy, the study corridor is highly congested, mainly in the morning and afternoon peak hours. The most significant causes of road traffic congestion in this study corridor are intersection bottlenecks, job centralization, poor traffic management, inadequate public transport, a large volume of private cars, and the presence of on-street parking. The result also showed that the congestion situation in the study area resulted in adverse economic and environmental impacts such as reduced productivity, increased fuel consumption , increased vehicle operation cost, discomfort, and health and traffic accident-related problems. The study thus suggests the provision of adequate mass transport, on-street parking restrictions, priority schemes for walking and cycling, and discouraging private car use during rush hours as alternative solutions.
... In road networks, it is possible to incorporate flood hazard and traffic information in order to uncover vulnerable stretches of road, especially those with few alternative routes [314]. If traffic data are not directly available, it is possible to construct proxies from mobile phone usage and city-wide CCTV streams-these are promising in rapidly developing urban centers [252,381]. Overall flood hazard maps can be improved using ML [455], and it is also possible to leverage data from real-world flooding events [616], and to send localized predictions to those at risk [841]. For electrical, water, and waste collection networks, the same principle can guide investments in resilience-using proxy or historical data about disruptions to anticipate vulnerabilities [564,574,600,609]. ...
Climate change is one of the greatest challenges facing humanity, and we, as machine learning (ML) experts, may wonder how we can help. Here we describe how ML can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by ML, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the ML community to join the global effort against climate change.
... It represents the sudden appearance of real-world matters and has many practical applications. For example, the BCS can represent an emergency disaster (e.g., earthquake [11] ) that is suddenly and widely spread in social media, a traffic congestion where there is a sudden and dramatic increase in the number of vehicles waiting at intersections or along the streets in road networks [12] , and an epidemic outbreak like COVID-19 having a rapid spread in the communitybased network [13] . ...
Unlabelled:
Temporal networks are an effective way to encode temporal information into graph data losslessly. Finding the bursting cohesive subgraph (BCS), which accumulates its cohesiveness at the fastest rate, is an important problem in temporal networks. The BCS has a large number of applications, such as representing emergency events in social media, traffic congestion in road networks and epidemic outbreak in communities. Nevertheless, existing methods demand the BCS lasting for a time interval, which neglects the timeliness of the BCS. In this paper, we design an early bursting cohesive subgraph (EBCS) model based on the k-core to enable identifying the burstiness as soon as possible. To find the EBCS, we first construct a time weight graph (TWG) to measure the bursting level by integrating the topological and temporal information. Then, we propose a global search algorithm, called GS-EBCS, which can find the exact EBCS by iteratively removing nodes from the TWG. Further, we propose a local search algorithm, named LS-EBCS, to find the EBCS by first expanding from a seed node until obtaining a candidate k-core and then refining the k-core to the result subgraph in an optimal time complexity. Subsequently, considering the situation that the massive temporal networks cannot be completely put into the memory, we first design an I/O method to build the TWG and then develop I/O efficient global search and local search algorithms, namely I/O-GS and I/O-LS respectively, to find the EBCS under the semi-external model. Extensive experiments, conducted on four real temporal networks, demonstrate the efficiency and effectiveness of our proposed algorithms. For example, on the DBLP dataset, I/O-LS and LS-EBCS have comparable running time, while the maximum memory usage of I/O-LS is only 6.5 MB, which is much smaller than that of LS-EBCS taking 308.7 MB.
Supplementary information:
The online version contains supplementary material available at 10.1007/s11390-022-2367-3.
The huge increase of vehicles on our highways with increased numbers of heavy goods vehicles in recent years, has led to traffic congestion and higher delays and also could lead to a higher rate of traffic accidents. To overcome such situations and to improve the efficiency and safety of the highways, a good understanding of the traffic operations on those highways is needed. This paper presents a newly developed model to compute vehicles' numbers and classify them and also to determine their speeds based on video cameras. For the purpose of this study, the new model has been built from scratch by using the PYTHON programing language. Several sets of field traffic data taken from different highway sites in Basra City were collected and analyzed. The collected data was used in the development and verification processes of the developed model. The experimental results are promising and showed that the proposed model can compute vehicles, classify them, and determine their speeds, with an average error not exceeding 3%.
This paper analyses the problems of passenger transport management in the context of sustainable mobility and multimodality in major Lithuanian cities. The urban transport system, development, and problem areas in meeting consumer needs are discussed. The article also discusses the ways to promote the use of public transport services in sustainable mobility and multimodality by solving the problem areas of passenger transport management. The article analyses the attitude of residents of major Lithuanian cities towards the importance of sustainable mobility and multimodality. The factors that determine the decision of the inhabitants of the major Lithuanian cities to use sustainable mobility and multimodality are presented, and ways to improve the quality in this area are considered. A quantitative method is applied to study the previously described attitudes and confirm the hypothesis that there are specific management difficulties related to sustainable mobility and multimodality. According to the study, most residents of Vilnius and other major cities do not combine public transport with other modes. Only less than one-third of survey participants combine multiple modes of transport on their trips. Implementing public transport management solutions in the context of sustainable mobility and multimodality should become a model.
It is important to know the road traffic density real time especially in mega cities for signal control and effective traffic management. In recent years, video monitoring and surveillance systems have been widely used in traffic management. Hence, traffic density estimation and vehicle classification can be achieved using video monitoring systems. In most vehicle detection methods in the literature, only the detection of vehicles in frames of the given video is emphesized. However, further analysis is needed in order to obtain the useful information for traffic management such as real time traffic density and number of vehicle types passing these roads. This paper presents vehicle classification and traffic density calculation methods using neural networks. The paper also reports results from real traffic videos obtained from Istanbul Traffic Management Company (ISBAK).
In this contribution we address the problem of using cellular network signaling for inferring real-time road traffic information. We survey and categorize the approaches that have been proposed in the literature for a cellular-based road monitoring system and identify advantages and limitations. We outline a unified framework that encompasses UMTS and GPRS data collection in addition to GSM, and prospectively combines passive and active monitoring techniques. We identify the main research challenges that must be faced in designing and implementing such an intelligent road traffic estimation system via third-generation cellular networks.
A real-time system is presented for automatically monitoring a highway when the camera is relatively low to the ground and on the side of the road. In such a case, occlusion and the perspective effects due to the heights of the vehicles cannot be ignored. The system presented in this paper is based on a novel technique of detecting and tracking the base fronts of vehicles. Compared with the authors' previous approach, the proposed technique involves a simplified problem formulation, operates in real time, and requires only a small number of parameters to calibrate. Experimental results of a camera mounted at a height of 26 ft and a lateral distance of 12 ft from the edge of the pavement reveal accuracy as high as 98% with few false detections. The system can collect a variety of traffic data, including volume, time-mean speed and space-mean speed, density, vehicle classification, and lane change activities. By handling perspective effects and vehicle occlusions, the system overcomes some of the limitations of commercially available machine vision-based traffic monitoring systems that are used in many intelligent transportation systems applications.
In this paper, we introduce a routing solution called "landmark overlays for urban vehicular routing environments" (LOUVRE), an approach that efficiently builds a landmark overlay network on top of an urban topology. We define urban junctions as overlay nodes and create an overlay link if and only if the traffic density of the underlying network guarantees the multi-hop vehicular routing between the two overlay nodes. LOUVRE contains a distributed traffic density estimation scheme which is used to evaluate the existence of an overlay link. Then, efficient routing is performed on the overlay network, guaranteeing a correct delivery of each packet. We evaluate LOUVRE against the benchmark routing protocols of GPSR and GPCR and show that LOUVRE performs higher in packet delivery and achieves lower hop count.
The paper proposes the histogram-based density discovery scheme as an alternative complement in obtaining density to LOUVRE, a landmark-based routing in the vehicular urban environment. The histogram-based scheme does not have the scalability problem as the P2P density scheme. Furthermore, it better accurately determines the road connectivity by considering non-uniform density. The paper makes the contribution of finding the optimal segment size to guarantee density and connectivity accuracy by evaluating thousands of mobility traces from a realistic mobility generator. Results have verified the scheme's accuracy and its scalability.
Finding hot routes (traffic flow patterns) in a road network is an important problem. They are beneficial to city planners, police departments, real estate developers, and many others. Knowing the hot routes allows the city to better direct traffic or analyze congestion causes. In the past, this problem has largely been addressed with domain knowledge of city. But in recent years, detailed information about vehicles in the road network have become available. With the development and adoption of RFID and other location sensors, an enormous amount of moving object trajectories are being collected and can be used towards finding hot routes.
This is a challenging problem due to the complex nature of the data. If objects traveled in organized clusters, it would be straightforward to use a clustering algorithm to find the hot routes. But, in the real world, objects move in unpredictable ways. Variations in speed, time, route, and other factors cause them to travel in rather fleeting “clusters.” These properties make the problem difficult for a naive approach. To this end, we propose a new density-based algorithm named FlowScan. Instead of clustering the moving objects, road segments are clustered based on the density of common traffic they share. We implemented FlowScan and tested it under various conditions. Our experiments show that the system is both efficient and effective at discovering hot routes.
This article presents a model and a procedure for determining traffic assignment and optimizing signal timings in saturated road networks. Both queuing and congestion are explicitly taken into account in predicting equilibrium flows and setting signal split parameters for a fixed pattern of origin-to-destination trip demand. The model is formulated as a bilevel programming problem. The lower-level problem represents a network equilibrium model involving queuing explicitly on saturated links, which predicts how drivers will react to any given signal control pattern. The upper-level problem is to determine signal splits to optimize a system objective function, taking account of drivers' route choice behavior in response to signal split changes. Sensitivity analysis is implemented for the queuing network equilibrium problem to obtain the derivatives of equilibrium link flows and equilibrium queuing delays with respect to signal splits. The derivative information is then used to develop a gradient descent algorithm to solve the proposed bilevel traffic signal control problem. A numerical example is included to demonstrate the potential application of the assignment model and signal optimization procedure.
The need for traffic information service systems that warn about traffic congestion and accidents through mobile devices, such as cellular phones, is increasing greatly now. To display clearly these informations for these services, a well-formed map is more useful than a detailed one in many cases. Although methods to generate well-formed map automatically are known as map summarization methods, summarization of road maps that cover wide areas has not been studied sufficiently. Therefore, we developed a new algorithm that summarizes the network structure of a detailed road network into a simple macroscopic structure. Further, we evaluated this algorithms effectiveness by experiments with 40 samples of road routes from the main road networks in Japan. The proposed method reduced the link number by 41.3% and reduced the fractal indices by 62.6%, and this proved simplification. And the proposed method improved the well-formed map by user evaluation. From these results obtained by our evaluation, we found that our method is effective for constructing a system for providing practical mobile traffic information services.
Sigmal Timing Optimization Software
- Passer Tm
PASSER TM : Sigmal Timing Optimization Software.
http://ttisoftware.tamu.edu/.
Traffic density estimation for noisy camera sources
- V Jain
- A Sharma
- A Dhananjay
- L Subramanian
V. Jain, A. Sharma, A. Dhananjay, and L. Subramanian. Traffic density
estimation for noisy camera sources. In TRB 91st Annual Meeting, Washington
D.C., January 2012.