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This study investigates the trends and determinants that dictate the state of multimodal transport by incorporating the effect of travel time reliability at different levels of service of traffic conditions. To account for the taste variation of commuters, a random parameter mixed logit model is used for the multimodal choice analysis. Multimodal transport is defined as use of multiple (more than one) transport modes for commuting in a specified time period. The data were collected through an interview-based household survey for a single day trip and land use data were collected from secondary sources. The parameters used in this study are interconnectivity ratio, penalty, multimodal level of service, travel cost, age, gender, income of traveller, purpose of trip and land use intensity, as well as diversity parameters such as population density, employment density, entropy and transport network density. The results indicate that interconnectivity ratio and multimodal level of service play the most influential roles in selecting a multimodal transport system. Commuters are most sensitive towards access and egress time. Also, the utility of the multimodal transport system for a commuter is highest under the road service condition of level of service (LOS) D as compared to LOS A. [ABSTRACT FROM AUTHOR]

Bike-sharing schemes (BSSs) have gained popularity as an alternative mode of transportation to solve the first/last mile problem. However, the bike-share market is subject to an oversupply problem with a low fleet utilisation rate in many countries. The aim of this paper is to tackle the BSS optimisation problem under stochastic demand scenarios by determining the shared bicycle fleet size and a fleet deployment strategy, where the interests of multiple stakeholders are taken into consideration at the same time. A stochastic multi-period bi-objective optimisation model is formulated to maximise the profit of bike-share operators and minimise the unmet demand, controlling the bike fleet utilisation rate. The problem is solved by an augmented ε-constraint method (Augmecon), which generates a set of non-dominated solutions. The numerical test is conducted with real data from Citi Bike to evaluate the validity of the model formulation and the effectiveness of the solution algorithm. The effect of fleet utilisation rate on BSS is analysed, where the trade-offs among earned profit, service level and fleet utilisation rate are addressed. [ABSTRACT FROM AUTHOR]

The aim of this study was to explore the viability of microsimulation in estimating critical gaps at unsignalised intersections. Critical gaps are generally estimated by extracting gap acceptance data from traffic videos. Extracting such data is a strenuous task, especially under mixed traffic conditions. In this study, gap acceptance data were generated from simulation models developed in the Vissim software package. Critical gaps of three unsignalised intersections were estimated using field data and simulated data of the intersections. Critical gaps were estimated by the logit method and the clearing time method. The critical gaps estimated using simulated data were reasonably close to those obtained using field data for both methods. The results also showed that the logit method was more robust than the clearing time method in estimating critical gaps under mixed traffic conditions. Moreover, the time needed for generating simulated data was only 3.6% of that required for obtaining field data. The method proposed in this study will help traffic engineers and practitioners in critical gap estimation by saving a considerable amount of time and effort. [ABSTRACT FROM AUTHOR]

Most performance prediction models for asphalt pavements are either based on laboratory data or numerical distress data collected from field surveys. However, these models do not fully reflect the true performance of pavements in different traffic and environmental conditions. In the study reported in this paper, a multi-input unified prediction model based on an artificial neural network was developed by using a mixture of numerical and categorical features for in-service pavement test sections in the USA. Pavement age, cracking length and area, cumulative traffic loading, two functional classes of roads, four climatic zones and maintenance effects were considered as input variables while changes in the pavement condition index (PCI) were determined as the output. The developed model was found to be efficient in terms of processing time and accuracy in dealing with the complexity and non-linearity of multiple input parameters. The results showed that the model provided a high correlation between observed and predicted deterioration at the training stage. The testing and validation results also yielded high accuracy in predicting the PCI and could be combined with a pavement management system to plan timely and accurate maintenance strategies. [ABSTRACT FROM AUTHOR]

A novel station-level vulnerability algorithm that takes both passenger flow and network topology into account to reveal critical stations in a metro network is proposed. A vulnerability-based emergency resource distribution model (V-ERDM) is proposed in which a given metro station's vulnerability is measured by a combined index of network topology and passenger demand. The paper compares the proposed V-ERDM with a coverage-oriented model (i.e. a similar model without the vulnerability measure) to evaluate its performance. The models were implemented on two Chinese metro networks (Shaoxing and Shanghai), and these applications validated the feasibility of the proposed models. The unique contributions of this work are two-fold: network vulnerability in a metro system based on the characteristics of the metro network is proposed and the paper introduces a vulnerability index into the emergency resource distribution problem. [ABSTRACT FROM AUTHOR]

Saturation flow is a fundamental performance measure parameter used for the design of intersections. However, in mixed traffic conditions, the evaluation of saturation flow is more sensitive due to heterogeneous traffic where vehicles are travelling in the same right of way without any lane separation. In such cases, the passenger car unit (PCU) plays a major role in analysing heterogeneity using an equivalent value for each vehicle. This paper presents a novel approach using the optimisation technique to determine PCU values and saturation flow for mixed traffic streams. Field data were collected at six signalised intersections in three Indian cities. The optimisation technique produced reasonable PCU values and an accurate estimation of saturation flow of 1906 PCUs/h. The saturation flow prediction model was developed using the multi-linear regression technique as per Pearson's correlation between saturation flow and vehicle compositional share. The developed saturation flow model was validated using field data from another site and the predicted value was in good agreement with the observed value. Finally, the predictive model was used to analyse the impact of traffic composition on saturation flow in mixed traffic streams. [ABSTRACT FROM AUTHOR]

Regarding the necessity of developing transportation infrastructures and its increasing importance in urban issues, nowadays in different cities, bicycles are considered the main and sustainable vehicle along with walking and drawing more attention day by day. The case considers highly paramount since preservation of the environment, natural resources, and energy is one of the significant pillars of sustainable development, and urban transportation intensively influences it. Thus, Bicycle Sharing System (BSS) is recognized as an innovative urban transportation option that meets the citizens’ demand for commuting during the day. The BSS can highly affect the level of citizens’ health, and it can be counted as one of the leading health programs whether it’s added to the public transportation system, it can help the culture to be created to use bicycles instead of cars in most of the internal trips, and also it can be so influential in decreasing the air pollution and in the following its harmful effects on health issues. The mathematical model of rebalancing multi-zone BSS with mobile stations and applying maintenance constraints in a static status is considered in this research. The objective function of this research is a single-objective one, which is modeled with the aims of reducing the costs of traveled distances by the tracks within and outside the zones, reducing the costs of intact and defective bicycles transportation within and outside the zones, and eventually, reducing the costs of surplus bicycles depot at the stations. This issue is a multi-product one that includes different types of bicycles and balancing tracks. Computational results confirm the model’s efficiency. Also, sensitivity analysis has been done to prove that the model is affected by both parameters of storage costs of surplus bicycles and transportation costs within and outside the zones.

Crowd gatherings at religious occasions, fairs, transport terminals and so on can create severe threats for the crowd due to the high density of people in a certain space, with adverse outcomes such as crowd stampedes. Analyses of stream flow parameters describe the relationships among the characteristics of crowd traffic streams. A regime model chosen based on crowd density has an impact on the predicted crowd characteristics at both the micro-level (individual behaviours in a crowd) and macro-level (overall crowd behaviour). Two-regime and three-regime models were used in this study to characterise crowd traffic in different regimes such as uncongested flow, transitional flow and congested flow. A model was developed based on the better fitness of predicted data to actual observed data. Data from the Krishna Pushkaralu festival were used for the model development and the developed model was validated using data from the Medaram festival. The three-regime model was found to provide a better fit than the single- and two-regime models and it was therefore concluded that the three-regime model can be used to analyse crowd behaviour and effectively manage crowds at any large congregation. [ABSTRACT FROM AUTHOR]

This paper presents and evaluates an application of a robust data envelopment analysis (RDEA) multi-criteria model for prioritising safety improvement projects with limited budget and data uncertainty. RDEA can be seen as an extension of classic data envelopment analysis (CDEA) that supports a more flexible and robust project selection by enabling decision-makers to adjust the level of conservation (or robustness) of decision-making against data uncertainty. Data from an existing case study were used to evaluate the performance of the model. The results indicated that the proposed methodology provides a useful tool for adjusting the level of robustness and that the efficiency of the candidate project decreases with the decision-maker's conservativeness and their ranking does not change as the decision-maker becomes more risk-averse. As a comparative study, the proposed approach was compared with incremental benefit–cost analysis and CDEA methods. The results indicated some changes in the list of selected projects considering the uncertainty impacts of data observed according to allocated budgets. [ABSTRACT FROM AUTHOR]

Effective planning and optimization of rail transport operations depends on effective and reliable forecasting of demand. The results of transport performance forecasts usually differ from measured values because the mathematical models used are inadequate. In response to this applicative need, we report the results of a study whose goal was to develop, on the basis of historical data, an effective mathematical model of rail passenger transport performance that would allow to make reliable forecasts of future demand for this service. Several models dedicated to this type of empirical data were proposed and selection criteria were established. The models used in the study are: the seasonal naive model, the Exponential Smoothing (ETS) model, the exponential smoothing state space model with Box–Cox transformation, ARMA errors, trigonometric trend and seasonal components (TBATS) model, and the AutoRegressive Integrated Moving Average (ARIMA) model. The proposed time series identification and forecasting methods are dedicated to the processing of time series data with trend and seasonality. Then, the best model was identified and its accuracy and effectiveness were assessed. It was noticed that investigated time series is characterized by strong seasonality and an upward trend. This information is important for planning a development strategy for rail passenger transport, because it shows that additional investments and engagement in the development of both transport infrastructure and superstructure are required to meet the existing demand. Finally, a forecast of transport performance in sequential periods of time was presented. Such forecast may significantly improve the system of scheduling train journeys and determining the level of demand for rolling stock depending on the season and the annual rise in passenger numbers, increasing the effectiveness of management of rail transport.

Node-selection behaviour in subway stations directly impacts the utilisation and capacity of equipment and facilities. Although this topic has been extensively studied in various fields, existing studies are limited to environment characteristics while little research has been undertaken from the perspectives of pedestrian and interaction characteristics. In this study, pedestrian node-selection behaviour at automatic fare gates (AFGs) in subway stations was investigated and a multi-nomial logit model was developed that incorporates environment, pedestrian and interaction characteristics. For model estimation and validation, a detailed site survey was carried out to collect data on pedestrians' actual AFG selection at three Beijing subway stations. The prediction accuracy of the model reached 90·90%. Application of the model is demonstrated by detailed analyses of influence factors from four aspects along with the utilisation optimisation of AFGs in Beijing West subway station. [ABSTRACT FROM AUTHOR]

The increasing population in large cities and the unbalanced urban growth associated with massive use of private cars in metropolitan areas often lead to traffic jams and road congestion that warrant the construction of such capital-intensive buildings as off-street public parking facilities. However, the initial problem in such projects is locating a suitable spot where all citizens can be conveniently served and the traffic load in busy city centers can be reduced by removing the need for on-street parking facilities. In this paper, an urban transportation network including, a number of parking demand points, a set of possible sitting locations, and several entry points of traffic flow are considered. Four objectives are generally considered for the public off-street parking location problem that include reducing traffic congestion, maximizing coverage demand, minimizing walking distance between demand points and new parking facilities, and decreasing related costs. The flow-capturing model has been exploited to develop two approaches for minimizing traffic congestion. Based on these approaches and other objectives, two models have been proposed. The covering distance of parking facilities will be uncertain in these models. Traffic flow entry points, driver’s path, and different types of parking lots have also been considered. Finally, relevant information and data required for implementing the proposed models were collected on two traffic zones in Central Business Districts (CBD) of Isfahan (Iran). Then, the ε-constraint method was used to solve the proposed multi-objectives models and the best candidate points for establishing new off-street parking facilities were determined.

In the transport management of aviation networks, uncertain factors and delay propagation are two main sources of flight delays. However, the impacts of uncertainty and the degree of delays are difficult to calculate empirically in daily operations. In this paper, a novel delay propagation model is introduced utilising the mathematical modelling tool coloured–timed Petri nets. This model enables descriptions of the delay propagation progress and flight delay calculation under the influence of uncertain factors. In order to understand the influence of airline network operations with uncertainties, the mechanisms of the main uncertainties (weather factors, air traffic control (ATC) factors and other low-probability random factors) are studied and probability functions are obtained. To simulate conditions under different uncertainties, experiments were carried out on an aviation network comprising 13 airports under different settings of bad weather and ATC. The simulation results revealed the influence of different uncertain factors, delay propagation time through flight chains and delay prediction in the aviation network. Based on the predicted flight delays, flight sequence update rules were established, which showed that the updated flight sequence significantly reduced flight delays compared with the original flight sequence. [ABSTRACT FROM AUTHOR]

A new optimization model of Automated Storage and Retrieval Systems (AS/RS) containing three objective and four constraint functions is presented in this paper. Majority of the researchers and publications in material handling field had performed optimization of different decision variables, but with single objective function only. Most common functions are: minimum travel time, maximum throughput capacity, minimum cost, maximum energy efficiency, etc. To perform the simultaneous optimization of objective functions (minimum: “investment expenses”, “cycle times”, “CO2 footprint”) the Non-dominated Sorting Genetic Algorithm II (NSGA II) was used. The NSGA II is a tool for finding the Pareto optimal solutions on the Pareto line. Determining the performance of the system is the main goal of our model. Since AS/RS are not flexible in terms of layout and organizational changes once the system is up and running, the proposed model could be a very helpful tool for the warehouse planners in the early stages of warehouse design.

This paper contributes to debates around improving the modelling of cycles, through an exploratory case study of bus–cycle interactions in London. This case study examines undocumented delays to buses caused by high volumes of cyclists in bus lanes. It has generally been assumed that cyclists do not noticeably delay buses in shared lanes. However, in many contexts where cyclists routinely share bus lanes, cyclist numbers have historically been low. In some such places, bus lanes are now seeing very high volumes of cyclists, far above those previously studied. This may have implications for bus – and cycle – journey times, but traditionally traffic modelling has not represented the effects of such interactions well. With some manipulation of parameters taken from models of other cities, the model described here demonstrates that cycles can cause significant delays to buses in shared lanes, at high cycling volumes. These delays are likely to become substantially larger if London's cycling demographic becomes more diverse, because cyclist speeds will decline. Hence bus journey time benefits may derive from separating cycles from buses, where cycle flows are high. The project also suggests that microsimulation modelling software, as typically used, remains problematic for representing cyclists. [ABSTRACT FROM AUTHOR]

This paper presents an innovative network-level, multi-input deterioration-prediction model for flexible asphalt pavements specific to four climatic conditions (wet freeze, wet non-freeze, dry freeze and dry non-freeze) and for two classes of roads (high-capacity arterials and low- to medium-capacity collectors). The model considers the impact of climate, maintenance, construction, material properties, age, traffic and surface distress such as cracking. Condition data from the US long-term pavement performance database were used to determine changes of pavement condition index (PCI) over time and then utilised in a regression analysis. The prediction model showed good accuracy with a high determination coefficient. A sensitivity study showed that while the age of construction and traffic are largely responsible for pavement deterioration, the area and length of cracks appearing on the road surface can be effectively used in the prediction model. Maintenance has a positive impact on the model performance, showed in improvement of PCI. The model is simple and versatile and has the potential to be adopted in countries with similar climate and traffic conditions. [ABSTRACT FROM AUTHOR]

The uncertainty-based work zone capacity model is formulated as a mixed linear regression function of explanatory variables where capacity is a random variable following a lognormal distribution. Model parameters are calibrated using a Bayesian approach. Results show that the proposed work zone capacity distribution model can accurately predict the mean and prediction interval of work zone capacity at any given confidence level. It is found that work zones located in urban roads, with a larger number of open lanes or with long-term work duration have a larger mean work zone capacity. A short prediction interval (i.e. low uncertainty) for work zone capacity is found to be associated with the following situations: (a) a bigger number of open lanes; (b) rural work zone; (c) short-term work duration; (d) left lane closure; (e) daytime work and (f) a smaller percentage of heavy vehicles. The predicted interval length for the medium level of work intensity is increased, although the corresponding mean work zone capacity is reduced, as compared with the light level of work intensity. There will be a bigger measured work zone capacity on average if the measurement method is adopted in which work zone capacity is taken as the mean queue-discharge rate. [ABSTRACT FROM AUTHOR]

Traffic-state estimation is a key component of an advanced traffic management system. The Eulerian traffic-state estimation based on an X-T traffic-flow model has proved successful in processing traditional X-T data sources such as inductive loop data. However, over the past decade, the emergence of probe vehicle data from paired sensors has created challenges for X-T traffic-state estimation. The vehicle–space (N-X) model has shown potential benefits in modelling paired-probe data. In this paper, an original N-X traffic-state estimation framework is proposed and validated by numerical experiments. In addition, an original first-order conservation formulation is derived to address the entry and exit slip road issue for motorway corridors. An evaluation is conducted by comparing the proposed N-X estimation with the X-T estimation. The results show that the proposed model is superior to the X-T estimation in terms of accuracy and efficiency. It performs well, particularly during congestion, and can track traffic breakdowns and recoveries effectively. [ABSTRACT FROM AUTHOR]

The primary goal of this study was to determine appropriate policies to increase the proportion of freight transported by water on the Hangyong canal in China and thus improve the economic efficiency of the canal. Factors were used to construct a transportation chain utility function and the most suitable model was selected according to the level of significance of the estimated parameter values. It was determined that the total logistics costs are the most significant factors in the decisions of Hangyong canal freight shippers. To show the heterogeneity in the choices of shippers, a mixed logit model with random parameters and a restricted triangular distribution was constructed. The time value of all shipping in the Hangyong channel was found as 52·50 yuan (1 GBP = 9·9970 CNY (15/09/2014))/(twenty-foot equivalent units (TEU) h). The modal share of the waterway transport chain, particularly the chain using 500 deadweight ton ships (1 deadweight ton (DWT) = 1000 deadweight kilograms), gradually increases as the channel capacity is increased. Furthermore, the effect of the transportation time on the 500 DWT ship waterway transportation chain is much higher than that of the transportation cost. The increase in waterway modal share resulting from reductions in transportation time is approximately seven times that resulting from reductions in transportation cost of the same percentage. [ABSTRACT FROM AUTHOR]

Vehicular traffic in developing countries like India is highly heterogeneous in nature. For effective planning, design, operation and management of highways, determination of traffic volume in a standard unit is a prerequisite. Interactions among vehicles under heterogeneous traffic conditions are highly complex. The passenger car unit (PCU) was therefore developed to represent the amount of impedance caused to the flow of traffic by a vehicle type in comparison with that of a standard vehicle (usually a passenger car). Since urban roads are marked by frequent changes in acceleration–deceleration characteristics, the interaction among various categories of vehicles can be realistically determined using a parameter that represents the change in acceleration/deceleration. A methodology for determining the PCU values of vehicles based on the concept of acceleration noise was developed in this study. The PCU for a study section was determined as the ratio of the variance of acceleration noise of the vehicle under consideration to that of a passenger car. PCU values were determined for four basic categories of vehicles on four-lane divided urban road stretches. [ABSTRACT FROM AUTHOR]

A support vector machine (SVM) model is proposed for accident prediction on non-urban sections of highways as an alternative to conventionally used fixed-effect or random-effect negative binomial (FENB/RENB) regression models. Road accident data over a period of 8 years on different sections of eight highways in India were collected from police records. In addition, data relating to road geometry, traffic and road environment related variables were collected through field studies. A total of 222 data points was gathered by dividing highways into sections with certain uniform geometric characteristics. Two modelling approaches were used (RENB and SVM models) to predict accident frequencies. The results showed encouraging performance of the SVM model in comparison with the RENB model in terms of both the correlation coefficient and root mean square error values. The SVM, originating from statistical learning theory, can better solve over-fitting and local minima problems and the results indicate that this approach can effectively be used as an alternative to the RENB approach if the sole aim is to predict crashes. The results clearly indicate that, to improve safety on Indian highways, minor access roads to highways and service roads need to be properly designed and controlled and the dispersion of speeds needs to be reduced. [ABSTRACT FROM AUTHOR]

Railway track behaviour with unsupported prestressed sleepers has been investigated in the literature. However, some of the important factors – such as prestressing forces, variations of the sleeper cross-section along its length, losing or recovering contact between the sleeper and the ballast layer – have been omitted. These limitations have been addressed in this research. The effects of unsupported sleepers on the dynamic behaviour of railway track have been investigated, using an improved three-dimensional numerical model of track developed here. The validity of the model is evaluated by comparing the results obtained from the model with experimental results (obtained in this research and available in the literature). The influences of the size of the gap between the sleeper and the underlying ballast, the vehicle speed and the number of unsupported sleepers on the track dynamic behaviour were investigated. The effects of the various unsupported conditions of sleepers on the rail seat load, sleeper bending moment and sleeper–ballast contact force at various train speeds were illustrated. It was shown that consideration of sleeper prestress forces, detailed geometry of the sleepers and a more realistic assumption for the sleeper–ballast contact has considerably improved the accuracy of the results obtained from theoretical models. [ABSTRACT FROM AUTHOR]

In this paper, an Integer Linear Programming (ILP) has been developed for rebalancing the stations of a Periodic Bike Relocation Problem (PBRP) in multiple periods. The objective function of the mathematical model is reducing costs of implementing trucks, transportation between stations and holding bikes on trucks during rebalancing. The variables we are following them in this model are conducting the optimal route in several periods, using the most appropriate trucks for these routes, and determining the best program for loading/unloading bikes for stations. The distinguishing features of the proposed model are considering several bike types, several exclusive trucks and several time periods. Finally, a numerical example confirms the applicability of the proposed model.

The aim of this study was to simulate pedestrian movements in the queuing process in subway stations using microscopic simulation models. The queuing process was divided into two stages - walking and selecting a queue, and entering a queue and waiting in that queue. To represent the boundary of these two stages, a novel queuing line concept was developed. This queuing line dynamically changes with factors such as pedestrian preference, queue shape and queue length. Furthermore, two corresponding microscopic simulation models were developed to handle those two stages on the basis of the social force model and the queuing rule, respectively. Typically, the queuing rule is determined by the desired force, the impact of the nearest pedestrian ahead in the same direction and a self-stopping mechanism. Two examples - a ticket office and a security check in a subway station - were used to verify the validity of the proposed models. [ABSTRACT FROM AUTHOR]

The publication presents the results arising from the experimental and mathematical modelling studies, which mainly aimed to investigate the selection and optimization of the rational operation modes particular to diesel engines of freight locomotives in the possession of the JSC ‘Lithuanian Railways’ (AB ‘Lietuvos geležinkeliai’). The goal of the optimization is to increase the energy efficiency, reduce fuel consumption and emissions of harmful air pollutants to the environment from diesel engines of locomotives during freight transportation via the main lines of the Lithuanian railway network. A complex energy efficiency and environmental pollution assessment criterion KE–E adjusted for diesel engines of freight locomotives has been suggested. The use of KE–E on the basis of the conducted complex experimental mathematical computer modelling studies has determined that the reserves reducing fuel consumption, harmful emissions and greenhouse gas (CO2) emissions constitute 6÷15% on an average, and in the case of individual railway network lines they go up to 30%. The comparative emission of harmful components per fuel mass (NOx, CO, CH, PM) e´NOx, e´CO, e´CH, e´PM when carrying freight via the main lines of the railway network by trains weighing 3000÷7500 t has been singled out. The results constitute sufficient grounds to organise control of harmful emissions and provide an opportunity to solve practical tasks with a slight tolerance (3÷7%) taking account of diesel engines of locomotives used for transportation. It has been proposed to measure the freight transportation efficiency according to the complex criterion KE–E, indicates the energy efficiency and the assessment of environmental pollution originating from diesel engine of locomotives. The reserves for increasing the efficiency of energy usage have been studied according to the variational mathematical computer modelling data. A methodology for measuring the freight transportation rationality and estimating the optimal indicators has been proposed, using the values of the KE–E criterion for the railways freight transportation, as well as the technology for controlling the traction characteristics as well as energy and ecology indicators of diesel engines of locomotives in operational conditions. First published online: 20 Oct 2016

Speed-flow relationships used to describe speed characteristics are very useful, especially as they can be utilised to analyse capacity and level of service. Speed-flow relationships for motorised vehicles have been widely studied, but those for heterogeneous bicycle flow have yet to be examined. This research thus aimed to develop speed-flow relationships for heterogeneous bicycle traffic flow, incorporating the factors of bicycle type and characteristics of cyclists such as percentages of electric bicycles (EBs), male cyclists, elderly cyclists and cyclists carrying loads. On the basis of field bicycle traffic data from 11 cycleway sections, three speed-flow relationships for different numbers of cycleway lanes were developed. The three models were further validated and used to examine the effects of bicycle type and characteristics of cyclists on the speed-flow relationships for bicycle traffic. The results showed that bicycle speed increases with the percentage of EBs on the cycleway, while the proportion of elderly cyclists has no significant effect on bicycle speed. Cyclists carrying loads and male cyclists have negative impacts on bicycle speed for a narrow width of cycleway. The findings of this study provide some countermeasures for bicycle planning and management. [ABSTRACT FROM AUTHOR]

Engineers have applied mathematical models to find the optimal railway path in order to minimise the total cost subject to the railway limitations. There are two main issues for this problem. First, this approach results in a complex formulation for real-life applications, mainly because there are a huge number of variables and constraints. Second, to compute the total cost, different types of data are required, such as topography, right-of-way unit cost, forbidden zones and geology. Because various administrations are often responsible for preparing these data with their own standards, there is much inconsistency in the data. This paper deals with the first issue by proposing a high-performance optimisation technique that simulates the behaviour of ants to obtain a good optimum. To show the effectiveness of this algorithm in finding a solution, a comparison with common algorithms is presented. In addition, a geographical information system database is used to obtain all the necessary data to estimate the total cost for each rail path. Finally, the proposed algorithm is tested to find the optimal path in a hypothetical area and the result of the proposed algorithm for finding the path is validated. [ABSTRACT FROM AUTHOR]

This study investigated the level of injury severity in crashes in right-turn lanes at signalised intersections. It used a dataset of 1900 injuries occurring at 275 signalised intersections in the Las Vegas, NV, USA area in the period 2003 to 2005. An advanced random-parameter binary logit model was used to determine the factors that significantly influence injury severity - categorised as either property damage only or severe injury - in right-turn lanes. A comparison of this model with the traditional fixed-parameter model was made to account for the unobserved heterogeneity. It was comparable to the two-level binary logistic model, which accounts for cross-group heterogeneity. The analysis showed that the following factors lead to a significantly higher likelihood of severe injury: rear-end crashes, the involvement of a vehicle going through the intersection, stopped and parked vehicles on main and minor streets, length of corner clearance, number of through lanes on minor streets and intersection angle. [ABSTRACT FROM AUTHOR]

Effective prediction of real-time traffic flow is important for traffic management and intelligent traffic systems. This paper proposes a hybrid model, consisting of the k-nearest neighbours ( k-NN) method and the Kalman filter (KF) technique, to dynamically predict real-time traffic flow. In the model, the k-NN method predicts a baseline speed of traffic flow on the basis of historical travel data of the target road link. To reflect the dynamic evolution of traffic flow in the prediction, a KF-based algorithm that uses the latest travel data, is developed to adjust the baseline travel speed. The hybrid model is tested with global positioning system data of Foshan City, China. In the numerical test, the proposed hybrid model is compared with a single k-NN model based on the same database. The results show that the hybrid model can provide more accurate prediction and thus holds potential for use in practice. [ABSTRACT FROM AUTHOR]

This paper proposes a methodology for the evaluation of the track condition by means of the measurement of the track stiffness. This magnitude is calculated from vertical acceleration data measured at the axle box of trains during their normal operation. From the corresponding vertical acceleration spectra, the dominant vibration frequencies for each track stretch are identified and the combined stiffness is then determined. The stiffness without the contribution of the rail is then calculated. The results obtained for a high-speed ballasted track in several track stretches are within the range 120-130 kN/mm, a result consistent with direct stiffness measurements taken during previous studies. Therefore, the proposed methodology may be used to obtain a first insight to the track condition by means of a continuous measurement of the track combined stiffness. This offers an alternative to traditional stationary stiffness measuring devices and might be a useful complement to dedicated continuous monitoring vehicles. [ABSTRACT FROM AUTHOR]

The origin-destination (OD) matrix, as a fundamental element of transportation planning, can be estimated in various ways. Owing to lower costs and the ability to keep matrices up to date, estimating OD matrices from observed traffic counts is gaining interest. These methods find an OD matrix that, when assigned to the network, reproduces the traffic counts. The main weakness of these methods, assuming traffic counts as deterministic values, has been overcome by the TFlowFuzzy (TFF) algorithm, which considers the counts as imprecise values. In this paper, a limitation of TFF is identified and accounted for with a methodological enhancement for modification. A key element in the estimation of trip matrices from traffic counts is the route choice proportions (assignment matrix). In the conventional TFF, the assignment matrix is computed only once and held constant during the whole estimation process. Hence, a modified algorithm is proposed in which the assignment matrix is updated successively. This modification is implemented on the real-size network of Mashad city. Results indicate a considerable improvement in the modified TFF goodness of fit compared to the traditional algorithm, as it is increased by 55%. This shows the effectiveness of the proposed algorithm, considering the assignment matrix endogenously. [ABSTRACT FROM AUTHOR]

In previous studies, little attention has been paid to developing methods for estimating passenger car equivalent (PCE) factors under oversaturated conditions. This paper presents a new method to estimate PCE factors for heavy vehicles based on the assumption that backward wave velocities keep consistent under oversaturated conditions. As the variations of backward wave velocities in mixed flows will be minimal if the traffic stream is uniform, a minimum relative standard deviation optimising model is given based on backward wave velocity. The traffic data drawn from I-80 datasets provided by the next generation simulation are utilised to analyse this method and prove the assumption. In view of the limitation of empirical data, Vissim microscopic traffic software is used to simulate oversaturated traffic flow under different percentages of heavy vehicles. The results show that the effects of heavy vehicles under oversaturated conditions are greater than those under free-flow conditions and the proportion of heavy vehicles has a major impact on the PCE factors. [ABSTRACT FROM AUTHOR]

This paper presents an investigation, using a numerical approach, of the dynamic response of the vehicle-track system as a function of the mechanical properties of high-speed rail track components. In particular, in this study the stiffness of the rail pad, ballast and sub-grade layer were considered as variable parameters. In order to assess their influence on the dynamic response during vehicle-track interaction, a sensitivity analysis was carried out. The analysis was undertaken using a simplified two-dimensional vehicle-track model, including the non-linear contact between wheel and rail, the track irregularities and several vehicle speeds. In total, more than 120 numerical simulations were performed, modifying, one at a time, the stiffness of the parameters. After processing the results, it was concluded that all the parameters considered have some influence, although the rail pad stiffness is the variable showing the highest influence. It is concluded that the procedure described is of use in optimising track design and reducing the dynamic response. [ABSTRACT FROM AUTHOR]

This study aimed to estimate the annual average daily traffic in inter-urban networks determining the best correlation (affinity) between the short period traffic counts and permanent traffic counters. A bi-level optimisation problem is proposed in which an agent in an upper level prefixes the affinities between short period traffic counts and permanent traffic counters stations and looks to minimise the annual average daily traffic calculation error while, in a lower level, an origin-destination (O-D) trip matrix estimation problem from traffic counts is solved. The proposed model is tested over the well-known Sioux-Falls network and applied to a real case of Cantabria (Spain) regional road network. The importance of determining appropriate affinity and the effect of localisation of permanent traffic counters stations are discussed. [ABSTRACT FROM AUTHOR]

The macroscopic fundamental diagram (MFD) traffic modelling method has been proved for large urban roads and freeway networks, but hysteresis and scatter have been found in both such networks. This paper investigates how incident variables affect the shape and scatter of the MFD using both simulated data and real data collected from the M3 Pacific motorway in Brisbane, Australia. Three key components of incidents are investigated based on the simulated data (i.e. incident location, incident duration and traffic demand). The results based on simulated data indicate that the diagram shape is a property not only of the network itself but also of the incident variables. Diagrams for three types of real incidents (crash, hazard and vehicle breakdown) are explored separately. The results based on the empirical data are consistent with the simulated results. The hysteresis phenomenon occurs both upstream and downstream of the incident location, but for opposite hysteresis loops. The gradient of the upstream diagram is greater than that downstream on the incident site, when traffic demand is for an off-peak period. [ABSTRACT FROM AUTHOR]

The problem of the improvement of parameters of maintenance of medium speed diesel engines is described in the publication. The most rational way of solving this problem is the performing of calculational research by using modern programs of mathematical modelling. At the initial stage of the research the approbation of interapplication of computer programs with a different level of elaboration for the optimisation of the main indexes of medium speed diesel engines (fuel economy, reliability, emission of harmful components in exhaust gases) is performed. The investigated efficiency of separate motor methods was applied for diesel engines 6VDS 48/42 AL-2 which are widely spread in the fleet of Lithuania. For the performance of further investigations the indirect criterion which estimates the phase of kinetic combustion and emission of nitric oxides is offered.

The identification and solution of transportation problems related to customs posts at railway border stations enable successful functioning of international freight transport, thus guaranteeing its reliability, punctuality and high quality. Perfection of the complex work is necessary in order to meet the requirements as well as to preserve goods during their transportation process. For the solution of the problems at the stations it is important to analyse fundamental principles, to assess an environmental impact, to formulate and evaluate the issues of wagon management by means of complicated technical systems, and to optimise the process of problems on the basis of research methods.

Recently, it has been recognised that flapping wing propulsion can be more efficient than conventional propel­lers if applied to very small-scale vehicles, so-called MAVs (micro air vehicles). Extraordinary possibilities of such objects, particularly in the context of special missions, are discussed. Flapping flight is more complicated than flight with fixed or rotating wings. Therefore, there is a need to understand the mechanisms of force generation by flapping wings in a more comprehensive way. The paper describes the current work on flapping wing conducted by the Flying & Swimming Puzzle Group. The key to understand the mechanisms of flapping flight is the adequate physical and mathematical modelling; modelling problems of flow and motion are emphasised. Sample calculations illustrating current capabilities of the method have been performed. The effect of feathering amplitude, flapping amplitude, and phase shifting on the MAVs control effectiveness has been examined. It has been discovered that the parameters mentioned above can be considered as control parameters of “flapping wing” MAVs, especially in lateral direction. Research programmes for the construction of MAVs concentrate on understanding the mechanisms of animal flight and on creating smart structures which would enable flight in micro-scale.

The objective of this study was to identify the influencing factors of road traffic crash rates from the perspective of access management techniques in urban areas. The target areas are located in the Las Vegas metropolitan area in the USA and 19 arterial routes were selected. To address the interdependency between crash rates and travel speeds and left-censored issue, simultaneous equation Tobit models are presented. The structure of the model addresses the left-censored issue for the segments while the simultaneous equation models treat the endogeneity issue between crash rates and travel speeds. The results indicate that there is a strong interdependency between crash rates and travel speeds. Segment length, driveway density, median (central reservation) opening density, posted speed limit and annual average daily traffic per lane were found to be statistically significant factors that influence both crash rates and travel speeds on segments. Moreover, crash rates are significantly influenced by two-directional median opening density. [ABSTRACT FROM AUTHOR]

The study shows how the evolution of two-way traffic flows on a local highway network can be predicted over time using a network-level traffic flow model (NTFM) to model both urban and motorway road networks. After a brief review of the main principles of the NTFM and its associated sub-models, the paper describes how a maintenance worksite can be modelled using a roadwork-node sub-model and a network solution routine in the NTFM. In order to model the two-way traffic flow in the road network, an iterative simulation method is used to generate the evolution of dependent traffic flows and queues. The NTFM has been applied to model the traffic characteristics and the effects of maintenance activities on the local Loughborough-Nottingham highway network. The study has demonstrated that the methodology is useful in selecting various worksite arrangements in order to reduce the effects of maintenance on road users. [ABSTRACT FROM AUTHOR]

The increase in the efficiency of main hub ports is a result of home base theory. Put another way, a network comprising linked nodes that are in collaboration is the issue of concern. In a sense, the bases and facilities of the main hub port serve as the trans-shipment and assembling centres for the departure destination flows. Based on this theory, this study puts forth the main hub port potentials for the Marmara region ports in Turkey by analysing the connection-rich nodes in the region through a transition from a random graph network structure to a non-scaled network structure using the port connectivity index and the port collaboration index. [ABSTRACT FROM AUTHOR]

Large off-street car parks are traditionally modelled as self-standing traffic zones representing origins/destinations in standard network assignment models. However, such a treatment precludes the drivers from choosing alternative car parks as it assumes the car parks are their final destinations. This paper discusses the feasibility of bringing car park choice and the effects of capacity within a traditional network assignment model. The search time within car parks depends on the car park occupancy and can be represented by a flow-delay type function on the car park occupancy/capacity. This research calibrates the search-time function based on practically observed occupancy and search time at two city-centre car parks in Leeds, England. The analysis follows a simple fixed search-time method as well as a sophisticated variable search-time method. The results are validated against the observed occupancies at the car parks. A car park specific constant was introduced to account for the unobserved preference for a given type of parking facility. In a multiperiod assignment, when car park occupancies are passed on dynamically, both fixed and variable search-time approaches are seen as an improvement over the standard approach, with the variable search time outperforming the fixed time approach. [ABSTRACT FROM AUTHOR]

Two Portuguese universities (University of Beira Interior and University of Coimbra) researched and developed a simplified road-user costs model for inclusion in a pavement management system, as well as input data for Portuguese trunk road networks, between 2004 and 2007. The model can be used to calculate the average road-user costs in relation to vehicle operating, accident, time and toll costs. This paper describes the main activities that led to the model formulation and the input data, and presents a new development to simplify user costs estimation considering changes in pavement condition and the influence of road work zones. These scenarios can then be easily and reliably utilised within the process of road maintenance and rehabilitation, evaluating the needs and consequences of road intervention actions for consideration in the cost-benefit and life-cycle cost analysis. This paper also confirms the importance of these additional costs through a model application to a Portuguese road network under private concession, comparing average costs with those for specific work zones and pavement condition scenarios. [ABSTRACT FROM AUTHOR]

Currently, there is no road deterioration (RD) model that can address pavement performance with flooding. Therefore, the aim of this work was to develop an RD model that considers flooding and pre- and post-flood strategies. The case study is road group(s) in Queensland, Australia, based on the 34 000 km road database of its main roads authority, as Queensland was severely affected by floods in 2011. This paper provides a brief literature review and proposes an approach to develop an RD model based on a non-homogeneous Markov transition probability matrix. The new RD models are developed for a number of road groups based on roughness and rutting data collected since 2000. Detailed results on the derived roughness-based and rutting-based RD models with flooding for two selected road groups are highlighted. The new RD models show significant pavement deterioration at different probabilities of flooding events, especially at higher probabilities. It is believed that these results will help road authorities in managing flood-damaged roads with appropriate treatments and optimum budget. [ABSTRACT FROM AUTHOR]

Transport accounts for 26% of global carbon dioxide emissions. The need to reduce greenhouse gas emissions, especially carbon dioxide, is thus becoming increasingly urgent and several approaches have been adopted to achieve this goal. Alternative sustainable technologies form one possible solution, and changes in driving styles could also contribute to a reduction in emissions. An alternative interesting approach is to reduce vehicle miles travelled. In this paper, the concept of vehicle miles travelled reduction based on a heuristic optimisation approach and geographical information system technology is introduced. The suitability of the concept was tested with the school bus routing problem. Working mechanisms of the adopted optimisation algorithms are explained. The results show that optimisation of bus stops, bus routes and driving schedules could significantly reduce the amount of vehicle miles travelled and, consequently, carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

Anticipated climate changes in Europe over the next 100 years were estimated using two different scenarios of carbon dioxide emissions and two computational approaches. The principal manifestations of climate change within the European region are predicted to be a rise in temperature, an increase in rainfall intensity in most areas and a decrease in freeze-thaw cycling. The impacts of such possible climate changes were then estimated for pavements and the pavement-related infrastructure. It should be noted that the life cycle of pavements is much shorter than the time span over which climate change might have a statistically significant influence on pavement performance. Several analytical and numerical analyses were performed in order to simulate the effect of future climate change, taking into account the fact that the effect of these changes on pavements structures will depend on local conditions. In particular, temperature and rainfall increase will be a challenge for asphalts, as both rutting and stripping of asphalt layers can be expected. In countries where roads are presently frequently frozen in winter, the length of this period of freezing will be reduced. For this reason, many thin and unsealed pavements will need to be upgraded if high bearing capacity is to be maintained. In coastal and low-lying areas raised water tables may occur due to areas where flood waters may collect, or due to raised sea levels. For most applications, appropriate responses to these changes in pavement performance will be achievable through the use of new design criteria with regard to temperature and the return period of storm flows. More attention needs to be paid to drainage systems, which should be self-cleaning and easy to inspect. [ABSTRACT FROM AUTHOR]

A comprehensive understanding of speed-flow-density relations is an essential requirement in planning, design and operation of transportation systems. Many researchers have investigated the nature of speed-flow-density relationships, commonly known as stream models, under homogeneous traffic conditions. However, those models may not be the best under Indian traffic conditions. Indian traffic differs significantly from homogeneous traffic and may need a different treatment for analysis. Not much research has been reported on this important aspect so far from India. The present study is an attempt to develop an optimal traffic stream model suitable for the heterogeneous traffic flow condition existing in India, taking Chennai as a case study. A two-regime speed-density relationship was developed using a conventional optimisation algorithm. Using this, the speed-flow and flow-density relationships were theoretically derived. The results indicate that the proposed model is able to represent the steady-state macroscopic behaviour of the heterogeneous and less lane-disciplined traffic stream under study with reasonable accuracy. [ABSTRACT FROM AUTHOR]

Short-term traffic-flow forecasting, the process of predicting future traffic conditions based on historical and real-time observations, is an essential aspect of intelligent transportation systems. The existing well-known algorithms used for short-term traffic flow include time-series analysis-based techniques, of which the seasonal auto-regressive moving average model is one of the most precise methods used in this field. The effectiveness of short-term traffic flow in an urban transport network can be fully realised only in its multivariate form where traffic flow is predicted at multiple sites simultaneously. In this paper, this concept in explored utilising an additive seasonal vector auto-regressive moving average model to predict traffic flow in the short-term future considering the spatial dependency among multiple sites. The dynamic linear model representation of the auto-regressive moving average model is used to reduce the number of latent variables. The parameters of the model are estimated in a Bayesian inference framework employing a Markov chain Monte Carlo sampling method. The efficiency of the proposed prediction algorithm is evaluated by modelling real-time traffic-flow observations available from a certain junction in the city centre of Dublin, Ireland. [ABSTRACT FROM AUTHOR]

The travel time reliability of buses has become increasingly important for public transit companies. In this study, a novel approach is proposed to evaluate and analyse the travel time reliability of bus services provided by TransLink in Queensland, Australia. In view of their stochastic features, the two components of travel time - dwell time and driving time - are represented by discrete distributed and normally distributed random variables respectively. Accordingly, the travel time could be described by Gaussian mixture models. Based on the proposed model, impact analysis shows that bus line reliability would increase by around 15% if onboard top-up for 'go cards' (electronic tickets) was not offered by TransLink. It was found that not providing this top-up method would not significantly harm the benefit of go card users, but it would substantially increase the total social benefit thanks to improved bus line reliability. [ABSTRACT FROM AUTHOR]

In many high-speed railway lines, the zones between embankments and structures may present some discontinuities, in terms of track geometry and track stiffness, which may create discomfort for passengers, induce deterioration of track and vehicle materials and even raise the risk of derailment to dangerous levels. In the attempt to attenuate the consequences of such problems, some solutions pointing at progressively changing the vertical stiffness in the railway track have been tested, such as transition zones or pads placed either between the rails and the sleepers or under the sleepers. The contribution of under-sleeper pads in transition regions and their effect on the railway infrastructure is specifically analysed in the present paper. The results obtained are of interest since they provide useful information for railway managers on infrastructure design and justify the need to implement such transition zones. [ABSTRACT FROM AUTHOR]