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Rapid urbanization increases the number of vehicles on a road section significantly throughout the country. Traffic in India is generally heterogeneous consisting of variety of vehicles which comprise wide range of static and dynamic characteristics. To estimate volume of such heterogeneous traffic it is essential to convert the different types of vehicles into equivalent passenger cars and express the volume in terms of Passenger Car Unit (PCU) per hour. The equivalency unit is universally adopted for measurement of traffic volume and the value is obtained by taking the passenger car as the 'Standard Vehicle.' The present study has been concentrated on four and six lane divided urban arterials in Kolkata. The PCU of vehicles have been presented for both categories of urban roads and the values are found to be higher than the values given in IRC: 106-1990. It has also been observed that, PCU values of different types of vehicles have been found to be different for different ranges of volume, composition and v/c ratio. Mathematical relationships have been developed on the basis of the variation of PCU with traffic stream parameters. The relationships are developed to forecast the PCU for several vehicular categories that have been statistically validated for different ranges of traffic stream parameters. [ABSTRACT FROM AUTHOR]

Saturation flow estimation is a challenge in non-lane based mixed traffic streams due to the presence of mixed vehicle-types, each having different static and dynamic characteristics. Such a mix gives way to traffic behaviours like weak lane discipline, multiple-leader following, etc. Due to these behaviours, queue discharge flow during green time fluctuates, which makes it difficult to identify a prolonged steady period of queue discharge required to estimate saturation flow. The present study is based on the hypothesis that the Passenger Car Unit (PCU) can explain the fluctuations in discharge caused by mixed vehicle-types. Accordingly, this study proposes a new model to estimate saturation flow along with PCUs from field data. Mathematical properties of the model are studied before field applications. Field data collected from six different locations are used to estimate the saturation flow and PCUs. The results indicate that the model can capture complex interactions of various vehicle-types. [ABSTRACT FROM AUTHOR]

The main purpose of the paper is to propose a traffic flow assignment method with matched selection of a multi-level road traffic network structure. Firstly, road connection 'design' parameters of traffic pricing are introduced, equilibrium conditions of users by traffic flow assignment are improved, design/pricing problem models of traffic network are constructed and surrounding semi-differentiable conditions of the reference point are considered and sensibility analysis methods of traffic equilibrium are designed. Then, sensitivity analysis is implemented combined with traffic flow assignment (TAPAS) output based on paired selection, it is shown how to use TAPAS to find a very precise equilibrium solution effectively and use the directional derivative. [ABSTRACT FROM AUTHOR]

Use of sensor data has been increasingly common in recent years, yet there is still a knowledge gap in evaluating the precision of traffic sensor data being used in traffic analyses for developing a transportation management plan. This paper fills this gap by exploring a new approach to evaluating the level of precision of large-scale traffic sensor data. The proposed analytical framework incorporates a spatiotemporal domain for the purpose of projecting spatiotemporal characteristics of the data into a repeatability and reproducibility (R&R) study. The main finding of this study is that the proposed framework is effective in examining the precision level of large-scale data spatiotemporally. The proposed framework would be useful for researchers and practitioners to benchmark precision measurements of traffic sensor data in a way to gather quality data and avoid any potential biased result of deeper traffic analyses. [ABSTRACT FROM AUTHOR]

In Nigeria, goods haulage is currently dominated through heavy trucks, whose effect on the pavement deterioration can be enormous, because the truck wheel/pavement interaction plays a key role in deterioration of pavement life. This study aims to measure the truck wheel/pavement contact characteristics with a view to develop its quantitative damaging influence on a pavement structure. Axle load distribution, tyre inflation pressure and tyre/pavement contact area of selected tyre types for different axle configurations were determined for four classes of trucks being used by a major haulage outfit in Nigeria, Messrs Dangote Industries Limited. The results obtained showed that the tyre pavement contact length depends on tyre load as the length increases with increase in tyre load, while tyre pavement contact width is averagely constant with tyre load increase. It is concluded that design and use of tyres should allow for large contact areas with small tyre pressures to lessen the menace of pavement deterioration, and also there is need for a strict control for standards of truck loads that travel on Nigerian road. [ABSTRACT FROM AUTHOR]

Conventional Transit Signal Priority (TSP) controls often reach the limitation for arterials accommodating heavy bus flows since the priority function can significantly increase delay at minor streets. Under such conditions, a proper signal progression plan that accounts for the benefits of buses may offer the potential to improve the reliability of bus operations and increase the bus ridership. This study proposes a bus-based progression model to reduce the delay of buses on local arterials. Given the cycle length and green splits at each intersection, the bus-based progression model, grounded on the same notion as conventional signal progression methods, considers the operational characteristics of transit vehicles, such as the impact of bus dwell time and the capacity constraints at bus stops. Also, to deal with the stochastic nature of dwell time, this study introduces additional constraints to maximize the percentage of buses which can stay within the green band after leaving bus stops. Taking an arterial with five intersections and three two-way bus stops as an example, this study applies VISSIM as an unbiased tool for model evaluation. The simulation results demonstrate that the proposed model can significantly reduce bus passenger delays and the average person delays for the entire arterial, compared with the conventional progression models. [ABSTRACT FROM AUTHOR]

Bluetooth technology has been widely used in transportation studies to collect traffic data. Bluetooth media access control (MAC) readers can be installed along roadways to collect Bluetooth-based data. This data is commonly used to measure traffic performance. One of the advantages of using Bluetooth technology to measure traffic performance is that travel time can be measured directly with a certain level of error instead of by estimation. However, travel time outliers can commonly be observed due to different travel mode on arterials. Since travel mode information cannot be directly obtained from the raw Bluetooth-based data, a mathematical methodology is in need to identify travel mode. In this study, a genetic algorithm and neural network (GANN)-based model was developed to identify travel mode. GPS-enabled devices were used to collect ground truth travel time. In order to additionally compare the model performance, K nearest neighbor (KNN) and support vector machine (SVM) were also implemented. N-fold cross validation was applied to statistically assess the models’ results. Since the model performances depend on the model inputs, seven collections of model inputs were tested in order to achieve the best travel mode identification performance. An arterial segment with four consecutive links and three intersections was selected to be the study segment. The results suggested that correctly identifying the three travel modes successfully every time was not possible, although the GANN based model had low misidentification rates. In our study, 6.12% of autos were misidentified as bikes and 10.53% of bikes were misidentified as autos using three links. [ABSTRACT FROM AUTHOR]

This paper proposes simple and direct formulation and algorithms for the probit-based stochastic user equilibrium traffic assignment problem. It is only necessary to account for random variables independent of link flows by performing a simple transformation of the perceived link travel time with a normal distribution. At every iteration of a Monte-Carlo simulation procedure, the values of the random variables are sampled based on their probability distributions, and then a regular deterministic user equilibrium assignment is carried out to produce link flows. The link flows produced at each iteration of the Monte-Carlo simulation are averaged to yield the final flow pattern. Two test networks demonstrate that the proposed algorithms and the traditional algorithm (the Method of Successive Averages) produce similar results and that the proposed algorithms can be extended to the computation of the case in which the random error term depends on measured travel time. [ABSTRACT FROM PUBLISHER]

Short period traffic counts (SPTCs) are conducted routinely to estimate the annual average daily traffic (AADT) at a particular site. This paper uses Indian traffic volume data to methodically and extensively study the effect of four aspects related to the design of SPTCs. These four aspects are: (i) for how long, (ii) on which days should SPTCs be carried out, (iii) how many times, and (iv) on which months should SPTCs be carried out? The analyses indicate that the best durations for conducting SPTCs are 3 days (starting with a Thursday) and 7 days, for total traffic and truck traffic, respectively. Further, these counts should be repeated twice a year keeping a separation of two months between the counts to obtain good estimates of AADT at minimal cost. An additional outcome of this study has been the determination of seasonal factor values for roads in developing economies, like India. [ABSTRACT FROM PUBLISHER]

Background: This study aimed to investigate the relationship between road users' attitudes and their travel behaviors, to explore the acceptability of traffic measures for sustainable transport promotion, and to investigate predictors of intention to reduce car use.Method: Using a cross-sectional survey, 381 residents in Adelaide were interviewed via a computer-assisted telephone interviewing system. Descriptive analysis was used to describe demographic, travel behavior, and effectiveness of potential traffic measures. Attitude statements relating to transport use were factor-analyzed into four factors: “sustainable transport benefits awareness,” “traffic problems awareness,” “cycling safety concerns and car use comfort” and “public transport negative emotion.” Scores on these factors were analyzed with Spearman's correlation and logistic regression.Results: In general, “push” measures (e.g. more expensive petrol) were considered less effective than “pull” measures (e.g. cheaper public transport). “Cycling safety concerns and car use comfort” and “public transport negative emotion” factors were positively related to the annual driving distance of the participants. Both “sustainable transport benefits awareness” and “traffic problems awareness factors” were positively associated with the acceptance of measures for sustainable transport promotion. Furthermore, participants who used cars more frequently, had high sores on “cycling safety concerns and car use comfort,” and had a bachelor degree or higher would be less likely to reduce car use.Conclusion: These findings indicate the importance of increasing public awareness of traffic problems and perceived benefits of sustainable transport as a potential strategy to reduce car use. [ABSTRACT FROM AUTHOR]

This paper presents a methodology aimed to acquire traffic flow data through the employment of unmanned aerial vehicles (UAVs). The study is focused on the determination of driving behavior parameters of road users and on the reconstruction of traffic flow Origin/Destination matrix. The methodology integrates UAV flights with video image processing technique, and the capability of geographic information systems, to represent spatiotemporal phenomena. In particular, analyzing different intersections, the attention of the authors is focused on users’ gap acceptance in a naturalistic drivers’ behavior condition (drivers are not influenced by the presence of instruments and operators on the roadway) and on the reconstruction of vehicle paths. Drivers’ level of aggressiveness is determined by understanding how drivers decide that a gap is crossable and, consequently, how their behavior is critical in relation to a moving stream of traffic with serious road safety implications. The results of these experiments highlight the usefulness of the UAVs technology, that combined with video processing technique allows the capture of real traffic conditions with a good level of accuracy. [ABSTRACT FROM PUBLISHER]

The prevailing roadway and traffic conditions on expressways in India are vastly different when compared with the other roads in India and also, there is no perfect lane-discipline. The knowledge of roadway capacity is an important basic input required for planning, design, analysis, and operation of roadway systems. Hence, this work aims to model traffic flow on Indian urban expressways with specific reference to Delhi–Gurgaon expressway and estimate its capacity using the micro-simulation model using VISSIM 5·40. For this purpose, the field data collected on traffic-flow characteristics on expressways was used in calibration and validation of the simulation model. The validated simulation model was then used to develop fundamental traffic–flow relationships, namely, speed–flow, speed–area occupancy, and flow–area occupancy for the traffic-flow levels, starting from near-zero until the capacity of the facility. The capacity of an eight-lane divided urban expressway in level terrain with 14·0-m wide road space (one direction of traffic flow) was found to be in the range of 9700–10 000 vehicles/h. Moreover, through sensitivity analysis using simulation model, the following relationships, (i) percentage trucks in the traffic stream and capacity-level flow and (ii) percentage of trucks in the traffic stream and capacity-level traffic-stream speed, were developed. The results and the overall methodology followed in this study for modeling traffic flow on expressways in India to determine the capacity estimates under varying traffic compositions may be very useful for the practitioners and also for the continuing efforts to prepare an Indian Highway Capacity Manual. [ABSTRACT FROM PUBLISHER]

In this paper we discuss why traffic forecasting is such a difficult endeavour, and point at alternatives to the current widespread use of traffic models almost independently of the problem faced by the planners. It will be argued that it is inherently impossible to make exact predictions about the magnitude of ‘general’ traffic growth 20–30 years ahead, since many of the influencing factors depend on inherently unpredictable geopolitical trajectories as well as contested political decision-making. Due to the context-dependency of each particular planning situation, it is also hardly possible to make exact, quantitative predictions about the impact of implementing a specific infrastructure project, compared to ‘doing nothing’. We propose separating the so-called strategic, tactical and operational levels of traffic forecasting into three distinct methodological approaches reflecting the different degrees of openness and closure of the systems at hand: scenario analyses at the strategic level; theory-informed, mainly qualitative analyses supplemented with simple calculations at the tactical level; while more traditional micro-simulations should be applied only at a detailed operational level. [ABSTRACT FROM PUBLISHER]

Travel times on the urban roadways are intrinsically uncertain. For known traffic conditions, a wide travel time distribution can be observed. Among all the components of travel times, delays incurred when approaching intersections constitute a large part of travel times that vehicles experience in urban trips. In this article, a model is presented for the delay distribution function for an urban trip with two fixed-time controlled intersections. Most parameters of the model are related to traffic control and flows, which can be directly calibrated from observations. The overflow queue distribution provides important parameters in the delay distribution function that have to be calibrated indirectly from traffic measurements, for example, from the measured delays and flows. Based on the directly observed and estimated model parameters, the delay distribution can be reconstructed. This article discusses the calibration procedure for delays. Two parameter estimation methods, namely, maximum likelihood (ML) and least squares (LS), are applied to estimate the overflow queue distribution from sample data simulated by VISSIM. Results show that estimation accuracy is not so susceptible to the choice of the estimation methods, sampling techniques, and sample size. The proposed delay model is able to successfully capture the delay process. [ABSTRACT FROM AUTHOR]

Mainstream traffic flow control (MTFC) on freeways, enabled via variable speed limits (VSL), is a traffic management tool capable of avoiding or, at least, postponing congestion formation on freeway bottlenecks, and may complement other existing measures. Two simple feedback controllers for local MTFC via VSL are proposed. Both controllers are evaluated and compared to a previously developed local MTFC feedback cascade controller and to a sophisticated optimal control approach. All feedback controllers rely on readily available real-time measurements, are simple and robust, and take into account a number of practical and safety restrictions; therefore, they are suitable for implementation in the field as a new or as part of an existing intelligent transportation systems infrastructure. The evaluations are conducted for a hypothetical freeway network by use of a validated second-order macroscopic traffic flow model. The results show that the feedback controllers exhibit a satisfactory control behavior and, indeed, approach the optimal control results. Recommendations for the operation of the feedback controllers are given. [ABSTRACT FROM AUTHOR]

Travel time prediction could be applied to various fields and purposes. For traffic managers, travel time prediction is a fundamental part of traffic system operation. Its results may assist traffic management department in adjusting traffic flow through time-dependent rules. From the travellers' viewpoints, travel time prediction saves travel time and improves reliability through the selection of travel routes pre-trip and en route to optimize travel plans. A large number of research efforts on travel time prediction have been conducted, but trip travel time prediction is relatively limited, compared with link travel time. Travellers are more interested in specific trip travel time than average link travel time. The advances in positioning technologies, such as Global Positioning System (GPS), make it possible to collect a large number of vehicle trajectories which cover the whole road network as long as data are enough and is growing as an alternative data set for travel time prediction as well as other traffic studies. In view of these, we extend the conventional methodology of link travel time prediction to trip using historical trajectory data from taxis in urban road network. This article basically consists of the following several parts, extracting origins and destinations, searching for matched trips, testing for normal distribution, detecting and removing outliers, predicting travel time in a statistic way, and evaluating the reliability of prediction results. Experiments based on taxi data in Shenzhen are conducted and the results are evaluated. [ABSTRACT FROM AUTHOR]

Environmental sustainability is closely related to transportation, especially to the road network, because vehicle emissions and noise damage the environment and have adverse effects on human health. It is, therefore, important to take their effect into account when designing and managing road networks. Road network equilibrium approaches have been used to estimate this impact and to design and manage road networks accordingly. However, no comprehensive review has summarized the applications of these approaches to the design and management of road networks that explicitly address environmental concerns. More importantly, it is necessary to identify this gap in the literature so that future research can improve the existing methodologies. Hence, this paper summarizes these applications and identifies potential future research directions in terms of theories, modelling approaches, algorithms, analyses, and applications. [ABSTRACT FROM AUTHOR]

Fuzzy logic has been recognised in the literature as an effective methodology for real-time signal control. The majority of the fuzzy controllers in the literature depend on simple logic which in turn depends on the raw data of a single detector. Their input variables are usually simple estimates of traffic measures such as flow, speed or occupancy, estimated from such single-detector readings. A room for improvement is sought in this article by developing a fuzzy logic model (FLM) that could be integrated with smarter 'processing' tools to estimate several traffic measures from multiple detectors on each approach. The estimates obtained from this processing tool are integrated as input knowledge into the FLM. The mathematical formulation of these traffic measures is presented. The fuzzy logic structure is addressed in detail. A simulation model is devised to test the effectiveness of the FLM. The results are presented and discussed in depth. [ABSTRACT FROM AUTHOR]

Traffic count data are useful for many purposes, but often not available for significant portions of road networks. It would be prohibitive to cover all roads with traditional sensor-based traffic monitoring system, particularly for rural, low-class roads. In cases where traffic volumes are needed but unavailable, travel demand models (TDMs) can be used to estimate such information. A literature review indicates that research work for estimating traffic volumes for low-class roads using TDM is scarce. The majority of previous research used traffic count data-based regressions. The problem of such an approach is that it relies on available traffic counts to develop, calibrate, and validate regression models. Nevertheless, few or no traffic counts are collected on low-class roads, and therefore make it inapplicable. This study implements TDMs for two regions in the province of New Brunswick, Canada to estimate traffic volumes for low-class roads. Geographical Information System-based TDMs using census data and Institute of Transportation Engineers (ITE) Quick Response Method produce forecasted traffic for a significant portion of road network previously without any traffic information and limit the average estimation errors for low-class roads to less than 40%. Available traffic data were increased by 45% in York County and 144% in the Beresford area. The traffic estimation errors are comparable to or better than those reported in the literature, and the forecast traffic volumes provide a solid foundation for identifying high-volume road segments and prioritizing funding. Study results clearly show TDM is a practical, useful, cost-effective way for estimating traffic parameters on low-class roads. [ABSTRACT FROM AUTHOR]

In June 2007, the Danish Parliament passed an act to finance the construction of the Metro City Ring in Copenhagen. The assessment project is based on the passenger patronage forecasts for 2015 from the Copenhagen traffic model. In this paper we show how the model forecasts for this particular infrastructure project can be explained through detailed knowledge of model structure and model validation. [ABSTRACT FROM AUTHOR]