This open access book presents the mathematical methods for huge data and network analysis. The automotive industry has made steady progress in technological innovations under the names of Connected ...Autonomous-Shared-Electric (CASE) and Mobility as a Service (MaaS). Needless to say, mathematics and informatics are important to support such innovations. As the concept of cars and movement itself is diversifying, they are indispensable for grasping the essence of the future mobility society and building the foundation for the next generation. Based on this idea, Research unit named "Advanced Mathematical Science for Mobility Society" was established at Kyoto University as a base for envisioning a future mobility society in collaboration with researchers led by Toyota Motor Corporation and Kyoto University. This book contains three main contents. 1. Mathematical models of flow 2. Mathematical methodsfor huge data and network analysis 3. Algorithm for mobility society The first one discusses mathematical models of pedestrian and traffic flow, as they are important for preventing accidents and achieving efficient transportation. The authors mainly focus on global dynamics caused by the interaction of particles. The authors discuss many-body particle systems in terms of geometry and box-ball systems. The second one consists of four chapters and deals with mathematical technologies for handling huge data related to mobility from the viewpoints of machine learning, numerical analysis, and statistical physics, which also includes blockchain techniques. Finally, the authors discuss algorithmic issues on mobility society. By making use of car-sharing service as an example of mobility systems, the authors consider how to construct and analyze algorithms for mobility system from viewpoints of control, optimization, and AI.
The Golden Triangle region that joins Burma, Thailand, and Laos is one of the global centers of opiate and methamphetamine production. Opportunistic Chinese businessmen and leaders of various armed ...groups are largely responsible for the manufacture of these drugs. The region is defined by the apparently conflicting parallel strands of criminality and efforts at state building, a tension embodied by a group of individuals who are simultaneously local political leaders, drug entrepreneurs, and members of heavily armed militias.
Ko-lin Chin, a Chinese American criminologist who was born and raised in Burma, conducted five hundred face-to-face interviews with poppy growers, drug dealers, drug users, armed group leaders, law-enforcement authorities, and other key informants in Burma, Thailand, and China.The Golden Triangleprovides a lively portrait of a region in constant transition, a place where political development is intimately linked to the vagaries of the global market in illicit drugs.
Chin explains the nature of opium growing, heroin and methamphetamine production, drug sales, and drug use. He also shows how government officials who live in these areas view themselves not as drug kingpins, but as people who are carrying the responsibility for local economic development on their shoulders.
This study is aimed at investigating the resilience degradation caused by traffic accidents and developing relevant resilience optimization strategies. A two-stage accident resilience triangle ...framework was proposed by comparing the differences between natural disasters and traffic accidents. To maximize system resilience, a network-wide traffic signal optimization model was presented. Spillback constraints and equilibrium constraints were established to enhance the capacity of urban-road networks to minimize congestion escalation, in addition to rapid recovery. A two-level algorithm based on greedy strategy and gradient descent was designed to solve the proposed non-linear programming model. In the experiment, a virtual road network was constructed based on the Simulation of Urban Mobility (SUMO) platform for validation and sensitivity analysis. The experimental results revealed that: (1) Compared to the traditional resilience framework, the proposed two-stage accident resilience framework can more reasonably describe the change mechanism of road network resilience under disturbance. (2) The proposed resilience-based traffic signal optimization model improved the system resilience under different conditions of traffic demand, accident severity, and rescue time in terms of the maximum performance degradation and recovery time. Precisely, the resilience loss is reduced by a maximum of 1.4%. Finally, the proposed model was further implemented with field data. The resilience improvement was significant during the evening rush hour. The results of this study contribute toward transportation resilience research and accident rescue strategies with respect to traffic management and control.
► Network fundamental diagram is exploited to improve mobility in saturated traffic conditions. ► Based on a simple but efficient feedback control structure, gating is applied to control urban ...congestion. ► Application of the gating strategy leads to substantial improvements compared to the non-gating case.
Traffic signal control for urban road networks has been an area of intensive research efforts for several decades, and various algorithms and tools have been developed and implemented to increase the network traffic flow efficiency. Despite the continuous advances in the field of traffic control under saturated conditions, novel and promising developments of simple concepts in this area remains a significant objective, because some proposed approaches that are based on various meta-heuristic optimization algorithms can hardly be used in a real-time environment. To address this problem, the recently developed notion of network fundamental diagram for urban networks is exploited to improve mobility in saturated traffic conditions via application of gating measures, based on an appropriate simple feedback control structure. As a case study, the proposed methodology is applied to the urban network of Chania, Greece, using microscopic simulation. The results show that the total delay in the network decreases significantly and the mean speed increases accordingly.
South Korea is ranked as 4th among 34 nations of the Organization for Economic Cooperation and Development with 102 deaths in road accidents per one million population. This paper aims to investigate ...the factors associated with road accidents in South Korea. The rainfall data of the Korea Meteorological Administration and road accidents data of Traffic Accident Analysis System of Korea Road Traffic Authority is analyzed for this purpose. In this connection, multivariate regression analysis and ratio analysis with the descriptive analysis are performed to uncover the catastrophic factors involved. In turn, the results reveal that traffic volume is the leading factor in road accidents. The limited road extension of 1.47% compared to the 4.14% per annum growth of the vehicles is resulting in road accidents at such a large scale. The increasing proportion of passenger cars accelerate road accidents as well. 56% of accidents occur by the infringement of safety driving violations. The drivers with higher driving experience tend to have a higher accident ratio. The collected data is analyzed in terms of gender, driver experience, type of violations and accidents as well as the associated time of the accidents when they happen. The results indicate that 36.29% and 53.01% of accidents happen by male drivers in the day and night time, respectively. 29.15% of crashes happen due to safety infringement and violations of 41 to 60 years old drivers. The results demonstrate that population density is associated with the accidents frequency and lower density results in an increased number of accidents. The necessity of the state-of-the-art regulations to govern the urban road traffic is beyond dispute, and it becomes even more crucial for citizens' relief since in our daily lives road accidents are getting more diverse.
A queuing system resulting from a signalized intersection regulated by pretimed control in a network of urban traffic is considered. Modeling the queue length and the delay of vehicles is crucial to ...evaluate the performance of intersections equipped with traffic signals. Air quality and rational use of energy also depend on an efficient management of the intersections. These traffic systems have the specificity that the server (green signal) is deactivated (red signal) during a fixed period of time. In the present work, an
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/1 queue with a server that occasionally takes vacations is analyzed. The mean delays of vehicles and the mean queue length are computed and compared with those obtained by using a detailed simulation model in a case study. We find that, in general, the mean delays of vehicles given by the proposed queuing model provide a good approximation, but the model can provide slightly smaller values than those obtained in the simulation model for large traffic flows. This result is of interest for traffic engineers, as the approaches one can find in the literature for large signalized urban traffic flows are subject to criticism.
•A Two-state Safe-speed Model is developed to simulate empirical and experimental findings.•The concave growth pattern of traffic oscillations is well replicated.•The empirical NGSIM detector data ...can be simulated with a quantitative agreement.•The observed spatiotemporal patterns and phase transitions of traffic flow are reproduced.
This paper firstly shows that a recent model (Tian et al., Transpn. Res. B 71, 138–157, 2015) is not able to replicate well the concave growth pattern of traffic oscillations (i.e., the standard deviation of speed is a concave function of the vehicle number in the platoon) observed from car following experiments. We propose an improved model by introducing a safe speed and the logistic function for the randomization probability. Simulations show that the improved model can reproduce well the metastable state, the spatiotemporal patterns, and the phase transitions of traffic flow. Calibration and validation results show that the concave growth pattern of oscillations and the empirical detector data can be simulated with a quantitative agreement.
Traffic analysis is a compound of strategies intended to find relationships, patterns, anomalies, and misconfigurations, among others things, in Internet traffic. In particular, traffic ...classification is a subgroup of strategies in this field that aims at identifying the application's name or type of Internet traffic. Nowadays, traffic classification has become a challenging task due to the rise of new technologies, such as traffic encryption and encapsulation, which decrease the performance of classical traffic classification strategies. Machine learning (ML) gains interest as a new direction in this field, showing signs of future success, such as knowledge extraction from encrypted traffic, and more accurate Quality of Service management. ML is fast becoming a key tool to build traffic classification solutions in real network traffic scenarios; in this sense, the purpose of this investigation is to explore the elements that allow this technique to work in the traffic classification field. Therefore, a systematic review is introduced based on the steps to achieve traffic classification by using ML techniques. The main aim is to understand and to identify the procedures followed by the existing works to achieve their goals. As a result, this survey paper finds a set of trends derived from the analysis performed on this domain; in this manner, the authors expect to outline future directions for ML-based traffic classification.
Traffic pattern analysis is an active and essential part of transportation research. When traffic condition is adverse and unprecedented, traffic sequences are useful in the analysis of traffic ...behaviour. The sequence through which traffic congestion has arisen can be predicted using sequence rules from the generated traffic sequence. This work aims at mining traffic sequence pattern and prediction of traffic volume based on traffic sequence rules. To mine peak hour traffic sequences in order to make better travel decision, travel time based PrefixSpan (TT-PrefixSpan) algorithm is proposed to analyse traffic flow on highways. As a result, the prediction of traffic volume is effected by the generated traffic sequences. Such analysis would pave the way for devising data driven computational methods in reducing traffic congestion. Real-time traffic volume data for 53 weeks is collected at a centralised toll system comprising toll collections centres at three different sites. To show the significance of this problem-solving approach, TT-PrefixSpan is experimented on three different sites. The extraction of a frequent traffic sequence pattern is reported with experimental analysis. The evaluation of different traffic condition present at each site has shown promising results. Towards the end, a summary of results is presented with directions for future research.
Abstract
Urban streets are essential parts in cities and their development can enhance various aspects of economic life and social activities. Al-Najaf city is one of the Iraqi developing cities that ...has been suffering from traffic congestion at various sections of its street network. The reasons, locations and intensities of these congestions are important to be regularly diagnosed for two key reasons: first, in order to choose the right traffic engineering solutions and second to adequately prioritize the funding required for planning and implementing the traffic management programs for these congested sections. This paper attempts to evaluate the performance of the main urban streets located within the southern part of Al-Najaf city street network during evening peak hours. The methodology includes collecting field data and conducting traffic surveys such as traffic volume, travel time and free flow speed surveys. The evaluating approaches illustrated in the U.S Highway Capacity Manual are adopted as a tool for assessing the operational performance for the selected urban streets. The results reveal that there are several segments that operate at their capacity (LOS E) or even under congested flow condition (LOS F). The analysis also shows that whereas some segments are with good LOS using volume-capacity ratio (v/c) criterion, they are actually with low LOS based on field observations or when using travel time as a performance measure. This indicates the inadequacy of using v/c ratio alone in evaluating urban streets because part of the congestion at such streets is due to side friction operational delays rather than over traffic demand.
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