A microscopic simulation model to estimate bus rapid transit station bus capacity

The Bus Rapid Transit (BRT) station is the interface between passengers and services. The station is crucial to line operation as it is typically the only location where buses can pass each other. Congestion may occur here when buses maneuvering into and out of the platform lane interfere with bus flow, or when a queue of buses forms upstream of the platform lane blocking the passing lane. Further, some systems include operation where express buses do not observe the station, resulting in a proportion of non-stopping buses. It is important to understand the operation of the station under this type of operation and its effect on BRT line capacity. This study uses microscopic traffic simulation modeling to treat the BRT station operation and to analyze the relationship between station bus capacity and BRT line bus capacity. First, the simulation model is developed for the limit state scenario and then a statistical model is defined and calibrated for a specified range of controlled scenarios of dwell time characteristics. A field survey was conducted to verify the parameters such as dwell time, clearance time and coefficient of variation of dwell time to obtain relevant station bus capacity. The proposed model for BRT bus capacity provides a better understanding of BRT line capacity and is useful to transit authorities in BRT planning, design and operation.

Traffic safety risks trends and patterns analysis on motorways

Crashes that occur on motorways contribute to a significant proportion (40-50%) of non-recurrent motorway congestion. Hence, reducing the frequency of crashes assist in addressing congestion issues (Meyer, 2008). Analysing traffic conditions and discovering risky traffic trends and patterns are essential basics in crash likelihood estimations studies and still require more attention and investigation. In this paper we will show, through data mining techniques, that there is a relationship between pre-crash traffic flow patterns and crash occurrence on motorways, compare them with normal traffic trends, and that this knowledge has the potentiality to improve the accuracy of existing crash likelihood estimation models, and opens the path for new development approaches. The data for the analysis was extracted from records collected between 2007 and 2009 on the Shibuya and Shinjuku lines of the Tokyo Metropolitan Expressway in Japan. The dataset includes a total of 824 rear-end and sideswipe crashes that have been matched with crashes corresponding traffic flow data using an incident detection algorithm. Traffic trends (traffic speed time series) revealed that crashes can be clustered with regards to the dominant traffic patterns prior to the crash occurrence. K-Means clustering algorithm applied to determine dominant pre-crash traffic patterns. In the first phase of this research, traffic regimes identified by analysing crashes and normal traffic situations using half an hour speed in upstream locations of crashes. Then, the second phase investigated the different combination of speed risk indicators to distinguish crashes from normal traffic situations more precisely. Five major trends have been found in the first phase of this paper for both high risk and normal conditions. The study discovered traffic regimes had differences in the speed trends. Moreover, the second phase explains that spatiotemporal difference of speed is a better risk indicator among different combinations of speed related risk indicators. Based on these findings, crash likelihood estimation models can be fine-tuned to increase accuracy of estimations and minimize false alarms.

Methodology for developing real-time motorway traffic risk identification models using individual-vehicle data

Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.

Incorporating human-factors in car-following models : a review of recent developments and research needs

Over the past decades there has been a considerable development in the modeling of car-following (CF) behavior as a result of research undertaken by both traffic engineers and traffic psychologists. While traffic engineers seek to understand the behavior of a traffic stream, traffic psychologists seek to describe the human abilities and errors involved in the driving process. This paper provides a comprehensive review of these two research streams. It is necessary to consider human-factors in {CF} modeling for a more realistic representation of {CF} behavior in complex driving situations (for example, in traffic breakdowns, crash-prone situations, and adverse weather conditions) to improve traffic safety and to better understand widely-reported puzzling traffic flow phenomena, such as capacity drop, stop-and-go oscillations, and traffic hysteresis. While there are some excellent reviews of {CF} models available in the literature, none of these specifically focuses on the human factors in these models. This paper addresses this gap by reviewing the available literature with a specific focus on the latest advances in car-following models from both the engineering and human behavior points of view. In so doing, it analyses the benefits and limitations of various models and highlights future research needs in the area.

Influence of traffic characteristics on polycyclic aromatic hydrocarbon build-up on urban road surfaces

Traffic is one of the prominent sources of polycyclic aromatic hydrocarbons (PAHs) and road surfaces are the most critical platform for stormwater pollution. Build-up of pollutants on road surfaces was the focus of this research study. The study found that PAHs build-up on road surfaces primarily originate from traffic activities, specifically gasoline powered vehicles. Other sources such as diesel vehicles, industrial oil combustion and incineration were also found to contribute to the PAH build-up. Additionally, the study explored the linkages between concentrations of PAHs and traffic characteristics such as traffic volume, vehicle mix and traffic flow. While traffic congestion was found to be positively correlated with 6- ring and 5- ring PAHs in road build-up, it was negatively correlated with 3-ring and 4 ring PAHs. The absence of positive correlation between 3-ring and 4-ring PAHs and traffic parameters is attributed to the propensity of these relatively volatile PAHs to undergo re-suspension and evaporation. The outcomes of this study are expected to contribute effective transport and land use planning for the prevention of PAH pollution in the urban environment.

Cellular Automata Models of Traffic Behavior in Presence of Speed Breaking Structures

In this article, we study traffic flow in the presence of speed breaking structures. The speed breakers are typically used to reduce the local speed of vehicles near certain institutions such as schools and hospitals. Through a cellular automata model we study the impact of such structures on global traffic characteristics. The simulation results indicate that the presence of speed breakers could reduce the global flow under moderate global densities. However, under low and high global density traffic regime the presence of speed breakers does not have an impact on the global flow. Further the speed limit enforced by the speed breaker creates a phase distinction. For a given global density and slowdown probability, as the speed limit enforced by the speed breaker increases, the traffic moves from the reduced flow phase to maximum flow phase. This underlines the importance of proper design of these structures to avoid undesired flow restrictions.

Macroscopic model of city traffic using bond graph modelling

Modelling of city traffic involves capturing of all the dynamics that exist in real-time traffic. Probabilistic models and queuing theory have been used for mathematical representation of the traffic system. This paper proposes the concept of modelling the traffic system using bond graphs wherein traffic flow is based on energy conservation. The proposed modelling approach uses switched junctions to model complex traffic networks. This paper presents the modelling, simulation and experimental validation aspects.

Modelagem matemática determinística do fluxo do tráfego veicular

Nesta dissertação consideramos duas abordagens para o tráfego de veículos: a macroscópica e a microscópica. O tráfego é descrito macroscopicamente por três grandezas físicas interligadas entre si, a saber, a velocidade, a densidade e o fluxo, descrevendo leis de conservação do número de veículos. Há vários modelos para o tráfego macroscópico de veículos. A maioria deles trata o tráfego de veículos como um fluido compressível, traduzindo a lei de conservação de massa para os veículos e requer uma lei de estado para o par velocidade-densidade, estabelecendo uma relação entre eles. Já o modelo descrito pela abordagem microscópica considera os veículos como partículas individuais. Consideramos os modelos da classe "car - following". Estes modelos baseiam-se no princípio de que o (n - 1)-ésimo veículo (denominado de "following-car") acelera em função do estímulo que recebe do n-ésimo veículo. Analisamos a equação de conservação do número de veículos em modelos macroscópicos para fluxo de tráfego. Posteriormente resolvemos esta equação através da linearização do modelo, estudando suas retas características e apresentamos a resolução do problema não linear em domínios limitados utilizando o método das características

Road Traffic Injury Prevention Initiatives: A Systematic Review and Metasummary of Effectiveness in Low and Middle Income Countries.

BACKGROUND: Road traffic injuries (RTIs) are a growing but neglected global health crisis, requiring effective prevention to promote sustainable safety. Low- and middle-income countries (LMICs) share a disproportionately high burden with 90% of the world's road traffic deaths, and where RTIs are escalating due to rapid urbanization and motorization. Although several studies have assessed the effectiveness of a specific intervention, no systematic reviews have been conducted summarizing the effectiveness of RTI prevention initiatives specifically performed in LMIC settings; this study will help fill this gap. METHODS: In accordance with PRISMA guidelines we searched the electronic databases MEDLINE, EMBASE, Scopus, Web of Science, TRID, Lilacs, Scielo and Global Health. Articles were eligible if they considered RTI prevention in LMICs by evaluating a prevention-related intervention with outcome measures of crash, RTI, or death. In addition, a reference and citation analysis was conducted as well as a data quality assessment. A qualitative metasummary approach was used for data analysis and effect sizes were calculated to quantify the magnitude of emerging themes. RESULTS: Of the 8560 articles from the literature search, 18 articles from 11 LMICs fit the eligibility and inclusion criteria. Of these studies, four were from Sub-Saharan Africa, ten from Latin America and the Caribbean, one from the Middle East, and three from Asia. Half of the studies focused specifically on legislation, while the others focused on speed control measures, educational interventions, enforcement, road improvement, community programs, or a multifaceted intervention. CONCLUSION: Legislation was the most common intervention evaluated with the best outcomes when combined with strong enforcement initiatives or as part of a multifaceted approach. Because speed control is crucial to crash and injury prevention, road improvement interventions in LMIC settings should carefully consider how the impact of improvements will affect speed and traffic flow. Further road traffic injury prevention interventions should be performed in LMICs with patient-centered outcomes in order to guide injury prevention in these complex settings.

Assessment Of various sensors for structural health monitoring for bridge weigh-in-motion (B-WIM).

In recent years, Structural Health Monitoring (SHM) systems have been developed to monitor bridge deterioration, assess real load levels and hence extend bridge life and safety. A road bridge is only safe if the stresses caused by the passing vehicles are less than the capacity of the bridge to resist them. Conventional SHM systems can be used to improve knowledge of the bridges capacity to resist stresses but generally give no information on the causes of any increase in stresses (based on measuring strain). The concept of in Bridge Weigh-in-Motion (B-WIM) is to establish axle loads, without interruption to traffic flow, by using strain sensors at a bridge soffit and subsequently converting the data to real time axle loads or stresses. Recent studies have shown it would be most beneficial to develop a portable system which can be easily attached to existing and new bridge structures for a specified monitoring period. The sensors could then be left in place while the data acquisition can be moved for various other sites. Therefore it is necessary to find accurate sensors capable of capturing peak strains under dynamic load and suitable methods for attaching these strain sensors to existing and new bridge structures. Additionally, it is important to ensure accurate strain transfer between concrete and steel, the adhesives layer and the strain sensor. This paper describes research investigating the suitably of using various sensors for the monitoring of concrete structures under dynamic vehicle load. Electrical resistance strain (ERS) gauges, vibrating wire (VW) gauges and fibre optic sensors (FOS) are commonly used for SHM. A comparative study will be carried out to select a suitable sensor for a bridge Weigh in Motion System. This study will look at fixing methods, durability, scanning rate and accuracy range. Finite element modeling is used to predict the strains which are then validated in laboratory trials.

Road traffic information platform for energy and emissions savings

Apesar das recentes inovações tecnológicas, o setor dos transportes continua a exercer impactes significativos sobre a economia e o ambiente. Com efeito, o sucesso na redução das emissões neste setor tem sido inferior ao desejável. Isto deve-se a diferentes fatores como a dispersão urbana e a existência de diversos obstáculos à penetração no mercado de tecnologias mais limpas. Consequentemente, a estratégia “Europa 2020” evidencia a necessidade de melhorar a eficiência no uso das atuais infraestruturas rodoviárias. Neste contexto, surge como principal objetivo deste trabalho, a melhoria da compreensão de como uma escolha de rota adequada pode contribuir para a redução de emissões sob diferentes circunstâncias espaciais e temporais. Simultaneamente, pretende-se avaliar diferentes estratégias de gestão de tráfego, nomeadamente o seu potencial ao nível do desempenho e da eficiência energética e ambiental. A integração de métodos empíricos e analíticos para avaliação do impacto de diferentes estratégias de otimização de tráfego nas emissões de CO2 e de poluentes locais constitui uma das principais contribuições deste trabalho. Esta tese divide-se em duas componentes principais. A primeira, predominantemente empírica, baseou-se na utilização de veículos equipados com um dispositivo GPS data logger para recolha de dados de dinâmica de circulação necessários ao cálculo de emissões. Foram percorridos aproximadamente 13200 km em várias rotas com escalas e características distintas: área urbana (Aveiro), área metropolitana (Hampton Roads, VA) e um corredor interurbano (Porto-Aveiro). A segunda parte, predominantemente analítica, baseou-se na aplicação de uma plataforma integrada de simulação de tráfego e emissões. Com base nesta plataforma, foram desenvolvidas funções de desempenho associadas a vários segmentos das redes estudadas, que por sua vez foram aplicadas em modelos de alocação de tráfego. Os resultados de ambas as perspetivas demonstraram que o consumo de combustível e emissões podem ser significativamente minimizados através de escolhas apropriadas de rota e sistemas avançados de gestão de tráfego. Empiricamente demonstrou-se que a seleção de uma rota adequada pode contribuir para uma redução significativa de emissões. Foram identificadas reduções potenciais de emissões de CO2 até 25% e de poluentes locais até 60%. Através da aplicação de modelos de tráfego demonstrou-se que é possível reduzir significativamente os custos ambientais relacionados com o tráfego (até 30%), através da alteração da distribuição dos fluxos ao longo de um corredor com quatro rotas alternativas. Contudo, apesar dos resultados positivos relativamente ao potencial para a redução de emissões com base em seleções de rotas adequadas, foram identificadas algumas situações de compromisso e/ou condicionantes que devem ser consideradas em futuros sistemas de eco navegação. Entre essas condicionantes importa salientar que: i) a minimização de diferentes poluentes pode implicar diferentes estratégias de navegação, ii) a minimização da emissão de poluentes, frequentemente envolve a escolha de rotas urbanas (em áreas densamente povoadas), iii) para níveis mais elevados de penetração de dispositivos de eco-navegação, os impactos ambientais em todo o sistema podem ser maiores do que se os condutores fossem orientados por dispositivos tradicionais focados na minimização do tempo de viagem. Com este trabalho demonstrou-se que as estratégias de gestão de tráfego com o intuito da minimização das emissões de CO2 são compatíveis com a minimização do tempo de viagem. Por outro lado, a minimização de poluentes locais pode levar a um aumento considerável do tempo de viagem. No entanto, dada a tendência de redução nos fatores de emissão dos poluentes locais, é expectável que estes objetivos contraditórios tendam a ser minimizados a médio prazo. Afigura-se um elevado potencial de aplicação da metodologia desenvolvida, seja através da utilização de dispositivos móveis, sistemas de comunicação entre infraestruturas e veículos e outros sistemas avançados de gestão de tráfego.

Simulation and dynamics of freeway traffic

This paper presents the new package entitled Simulator of Intelligent Transportation Systems (SITS) and a computational oriented analysis of traffic dynamics. The SITS adopts a microscopic simulation approach to reproduce real traffic conditions considering different types of vehicles, drivers and roads. A set of experiments with the SITS reveal the dynamic phenomena exhibited by this kind of system. For this purpose a modelling formalism is developed that embeds the statistics and the Laplace transform. The results make possible the adoption of classical system theory tools and point out that it is possible to study traffic systems taking advantage of the knowledge gathered with automatic control algorithms. A complementary perspective for the analysis of the traffic flow is also quantified through the entropy measure.

A field study of factors influencing the concentrations of a traffic-related pollutant in the vicinity of a complex urban junction

The paper describes a field study focused on the dispersion of a traffic-related pollutant within an area close to a busy intersection between two street canyons in Central London. Simultaneous measurements of airflow, traffic flow and carbon monoxide concentrations ([CO]) are used to explore the causes of spatial variability in [CO] over a full range of background wind directions. Depending on the roof-top wind direction, evidence of both flow channelling and recirculation regimes were identified from data collected within the main canyon and the intersection. However, at the intersection, the merging of channelled flows from the canyons increased the flow complexity and turbulence intensity. These features, coupled with the close proximity of nearby queuing traffic in several directions, led to the highest overall time-average measured [CO] occurring at the intersection. Within the main street canyon, the data supported the presence of a helical flow regime for oblique roof-top flows, leading to increased [CO] on the canyon leeward side. Predominant wind directions led to some locations having significantly higher diurnal average [CO] due to being mostly on the canyon leeward side during the study period. For all locations, small changes in the background wind direction could cause large changes in the in-street mean wind angle and local turbulence intensity, implying that dispersion mechanisms would be highly sensitive to small changes in above roof flows. During peak traffic flow periods, concentrations within parallel side streets were approximately four times lower than within the main canyon and intersection which has implications for controlling personal exposure. Overall, the results illustrate that pollutant concentrations can be highly spatially variable over even short distances within complex urban geometries, and that synoptic wind patterns, traffic queue location and building topologies all play a role in determining where pollutant hot spots occur.

Activity patterns of urban red foxes (Vulpes vulpes) reduce the risk of traffic-induced mortality

Traffic collisions can be a major source of mortality in wild populations, and animals may be expected to exhibit behavioral mechanisms that reduce the risk associated with crossing roads. Animals living in urban areas in particular have to negotiate very dense road networks, often with high levels of traffic flow. We examined traffic-related mortality of red foxes (Vulpes vulpes) in the city of Bristol, UK, and the extent to which roads affected fox activity by comparing real and randomly generated patterns of movement. There were significant seasonal differences in the number of traffic-related fox deaths for different age and sex classes; peaks were associated with periods when individuals were likely to be moving through unfamiliar terrain and would have had to cross major roads. Mortality rates per unit road length increased with road magnitude. The number of roads crossed by foxes and the rate at which roads were crossed per hour of activity increased after midnight when traffic flow was lower. Adults and juveniles crossed 17% and 30% fewer roads, respectively, than expected from randomly generated movement. This highly mobile species appeared to reduce the mortality risk of minor category roads by changing its activity patterns, but it remained vulnerable to the effects of larger roads with higher traffic flows during periods associated with extraterritorial movements.

QoS evaluation of bandwidth schedulersin IPTV networks offered SRD fluidvideo traffic: a simulation study

IPTV is now offered by several operators in Europe, US and Asia using broadcast video over private IP networks that are isolated from Internet. IPTV services rely ontransmission of live (real-time) video and/or stored video. Video on Demand (VoD)and Time-shifted TV are implemented by IP unicast and Broadcast TV (BTV) and Near video on demand are implemented by IP multicast. IPTV services require QoS guarantees and can tolerate no more than 10-6 packet loss probability, 200 ms delay, and 50 ms jitter. Low delay is essential for satisfactory trick mode performance(pause, resume,fast forward) for VoD, and fast channel change time for BTV. Internet Traffic Engineering (TE) is defined in RFC 3272 and involves both capacity management and traffic management. Capacity management includes capacityplanning, routing control, and resource management. Traffic management includes (1)nodal traffic control functions such as traffic conditioning, queue management, scheduling, and (2) other functions that regulate traffic flow through the network orthat arbitrate access to network resources. An IPTV network architecture includes multiple networks (core network, metronetwork, access network and home network) that connects devices (super head-end, video hub office, video serving office, home gateway, set-top box). Each IP router in the core and metro networks implements some queueing and packet scheduling mechanism at the output link controller. Popular schedulers in IP networks include Priority Queueing (PQ), Class-Based Weighted Fair Queueing (CBWFQ), and Low Latency Queueing (LLQ) which combines PQ and CBWFQ.The thesis analyzes several Packet Scheduling algorithms that can optimize the tradeoff between system capacity and end user performance for the traffic classes. Before in the simulator FIFO,PQ,GPS queueing methods were implemented inside. This thesis aims to implement the LLQ scheduler inside the simulator and to evaluate the performance of these packet schedulers. The simulator is provided by ErnstNordström and Simulator was built in Visual C++ 2008 environmentand tested and analyzed in MatLab 7.0 under windows VISTA.