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Travel times are generally stochastic and spatially correlated in congested road networks. However, very few existing route guidance systems (RGS) can provide reliable guidance services to aid travellers planning their trips with taking account explicitly travel time reliability constraint. This study aims to develop such a RGS with particular consideration of travellers' concern on travel time reliability in congested road networks with uncertainty. In this study, the spatially dependent reliable shortest path problem (SD-RSPP) is formulated as a multi-criteria shortest path-finding problem in road networks with correlated link travel times. Three effective dominance conditions are established for links with different levels of travel time correlations. An efficient algorithm is proposed to solve SD-RSPP by adaptively using three established dominance conditions. The complexities of road networks in reality are also explicitly considered. To demonstrate the applicability of proposed algorithm, a comprehensive case study is carried out in Hong Kong. The results of case study show that the proposed solution algorithm is robust to take account of travellers' multiple routing criteria. Computational results demonstrate that the proposed solution algorithm can determine the reliable shortest path on real-time basis for large-scale road networks. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, two-tier mathematical models were developed to simulate the microscopic pedestrian decision-making process of route choice at signalized crosswalks. In the first tier, a discrete choice model was proposed to predict the choices of walking direction. In the second tier, an exponential model was calibrated to determine the step size in the chosen direction. First, a utility function was defined in the first-tier model to describe the change of utility in response to deviation from a pedestrian's target direction and the conflicting effects of neighboring pedestrians. A mixed logit model was adopted to estimate the effects of the explanatory variables on the pedestrians' decisions. Compared with the standard multinomial logit model, it was shown that the mixed logit model could accommodate the heterogeneity. The repeated observations for each pedestrian were grouped as panel data to ensure that the parameters remained constant for individual pedestrians but varied among the pedestrians. The mixed logit model with panel data was found to effectively address inter-pedestrian heterogeneity and resulted in a better fit than the standard multinomial logit model. Second, an exponential model in the second tier was proposed to further determine the step size of individual pedestrians in the chosen direction; it indicates the change in walking speed in response to the presence of other pedestrians. Finally, validation was conducted on an independent set of observation data in Hong Kong. The pedestrians' routes and destinations were predicted with the two-tier models. Compared with the tracked trajectories, the average error between the predicted destinations and the observed destinations was within an acceptable margin. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including the problem on traffic data fusion for travel times estimation, the prediction of work zone traffic capacity for traffic management, and the algorithm for traffic assignment problem.

This paper proposes an analytical model for investigating transit technology selection problem from a perspective of transit authority. Given a transit technology alternative (e.g., metro, light rail transit, or bus rapid transit), the proposed model aims to maximize the social welfare of the transit system by determining the optimal combination of transit line length, number of stations, station location (or spacing), headway, and fare. In the proposed model, the effects of passenger demand elasticity and capacity constraint are explicitly considered. The properties of the model are examined analytically, and a heuristic solution procedure for determining the model solution is presented. By comparing the optimized social welfare for different transit technology alternatives, the optimal transit technology solution can be obtained together with critical population density. On the basis of a simple population growth rate formula, optimal investment timing of a new transit technology can be estimated. The proposed methodology is illustrated in several Chinese cities. Insightful findings are reported on the interrelation among transit technology selection, population density, transit investment cost, and transit line parameter design as well as the comparison between social welfare maximization and profit maximization regimes. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, a new cellular automata model is proposed to simulate the car and bicycle heterogeneous traffic on urban road. To capture the complex interactions between these two types of vehicles, a novel occupancy rule is adopted in the proposed model to consider the variable lateral distances of mixed vehicular traffic. Based on massive simulations, microscopic fundamental diagrams under different bicycle densities are devised. With these, the bicycle's spilling behavior is then investigated and discussed. In order to reflect the interference of a bicycle on a car, the interference transformation from friction state to block state is modeled explicitly. Finally, different simulation results under different occupancy rules indicate that the constant and fixed occupancy rule adopted in the previous studies might lead to overestimation of car flux in the heterogeneous traffic flows with different bicycle densities. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY In densely populated and congested urban areas, the travel times in congested multi-modal transport networks are generally varied and stochastic in practice. These stochastic travel times may be raised from day-to-day demand fluctuations and would affect travelers' route and mode choice behaviors according to their different expectations of on-time arrival. In view of these, this paper presents a reliability-based user equilibrium traffic assignment model for congested multi-modal transport networks under demand uncertainty. The stochastic bus frequency due to the unstable travel time of bus route is explicitly considered. By the proposed model, travelers' route and mode choice behaviors are intensively explored. In addition, a stochastic state-augmented multi-modal transport network is adopted in this paper to effectively model probable transfers and non-linear fare structures. A numerical example is given to illustrate the merits of the proposed model. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper proposes a new model for investigating the allocation of new lines in a competitive transit network in which transit operations are subject to demand uncertainty and scale economies. Scale economies imply that the operating cost of each operator per unit of transit line decreases with the number of lines operated. The proposed model explicitly considers the interactions among three types of players: transit authority, transit operators, and transit passengers. The transit authority aims to maximize the total social welfare for a given confidence level (or probabilistic guarantee) by optimizing the allocation of new lines to bidding operators. For a given allocation scheme, each of the operators determines the associated frequencies and fares to maximize its own profit at a certain confidence level while accounting for the responses of transit passengers to their strategies. The proposed line allocation model is formulated as a robust 0-1 integer programming problem that can be solved by an implicit enumeration algorithm. A numerical example is presented to illustrate the effects on the transit system of the allocation of new lines, the scale economies, the level of variation in passenger demand, and the risk attitude of transit operators toward uncertainty. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper proposes a new risk-averse user equilibrium (RAUE) model to estimate the distribution of traffic flows over road networks with taking account the effects of accident risks due to the conflicting traffic flows (left- and right-turning and through traffic flows) at signalized intersections. It is assumed in the proposed model that drivers consider simultaneously both the travel time and accident risk in their route choices. The accident risk of a route is measured by the potential accident rate on that route. The RAUE conditions are formulated as an equivalent path-based variational inequality problem which can be solved by a path-based solution algorithm. It is shown that the traditional user equilibrium (UE) model is in fact a special case of the proposed model. A numerical example on a grid network is used to illustrate the application of the proposed model and to compare the results with the conventional UE traffic assignment. Numerical results show that the traditional UE model may underestimate the total system travel time and overestimate the system accident rate. Sensitivity tests are also carried out to assess the effects of drivers' preferences, signal control parameters (i.e., green time proportions), and various network demand levels on the route choice problem. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper addresses a general stochastic user equilibrium (SUE) traffic assignment problem with link capacity constraints. It first proposes a novel linearly constrained minimization model in terms of path flows and then shows that any of its local minimums satisfies the generalized SUE conditions. As the objective function of the proposed model involves path-specific delay functions without explicit mathematical expressions, its Lagrangian dual formulation is analyzed. On the basis of the Lagrangian dual model, a convergent Lagrangian dual method with a predetermined step size sequence is developed. This solution method merely invokes a subroutine at each iteration to perform a conventional SUE traffic assignment excluding link capacity constraints. Finally, two numerical examples are used to illustrate the proposed model and solution method. [ABSTRACT FROM AUTHOR]

This paper proposes a new travel time reliability-based traffic assignment model to investigate the rain effects on risk-taking behaviours of different road users in networks with day-to-day demand fluctuations and variations in travel time. A generalized link travel time function is used to capture the rain effects on vehicle travel times and road conditions. This function is further incorporated into daily demand variations to investigate those travel time variations arising from demand uncertainty and rain condition. In view of these rain effects, road users' perception errors on travel times and risk-taking behaviours on path choices are incorporated in the proposed model with the use of a logit-based stochastic user equilibrium framework. This new model is formulated as a variational inequality problem in terms of path flows. A numerical example is used to illustrate the application of the proposed model for assessment of the rain effects on road networks with uncertainty. [ABSTRACT FROM AUTHOR]

In this paper, a case study is carried out in Hong Kong for demonstration of the Transport Information System (TIS) prototype. A traffic flow simulator (TFS) is presented to forecast the short-term travel times that can be served as a predicted travel time database for the TIS in Hong Kong. In the TFS, a stochastic deviation coefficient is incorporated to simulate the minute-by-minute fluctuation of traffic flows within the peak hour period. The purposes of the case study are: 1) to show the applicability of the TFS for larger-scale road network; and 2) to illustrate the short-term forecasting of path travel times in practice. The results of the case study show that the TFS can be applied to real network effectively. The predicted travel times are compared with the observed travel times on the selected paths for an OD pair. The results show that the observed path travel times fall in the 90% confidence interval of the predicted path travel times. [ABSTRACT FROM AUTHOR]

This paper is an attempt to develop a generic simulation-based approach to assess transit service reliability, taking into account interaction between network performance and passengers' route choice behaviour. Three types of reliability, say, system wide travel time reliability, schedule reliability and direct boarding waiting-time reliability are defined from perspectives of the community or transit administration, the operator and passengers. A Monte Carlo simulation approach with a stochastic user equilibrium transit assignment model embedded is proposed to quantify these three reliability measures of transit service. A simple transit network with a bus rapid transit (BRT) corridor is analysed as a case study where the impacts of BRT components on transit service reliability are evaluated preliminarily. [ABSTRACT FROM AUTHOR]

The transport demand in most major cities around the world can only be met with a high-quality public transport system. The requirements on bus, rail, underground and tram systems are manifold with reliability and efficiency as the key factors. The service operating hours and the size of the network are often extended in order to serve the needs better. Further, most metropolitan areas are trying to provide more incentives for citizens to leave the car at home and use the local transit systems instead. The reasons are well known. Not only does a public transport system only make economical sense if it is well used, but most urban areas with a high car-dependency face at least three major problems; safety, congestion, and pollution (noise and air pollution, land separation, etc.). It is generally recognised that to decrease car usage and to increase public transport usage a stick & carrot approach is needed. The London congestion-charging scheme is an example since all revenues collected by the scheme are put into the improvement of bus and underground services. [ABSTRACT FROM AUTHOR]

This paper proposes an elastic demand network equilibrium model for networks with transit and walking modes. In Hong Kong, the multi-mode transit system services over 90% of the total journeys and the demand on it is continuously increasing. Transit and walking modes are related to each other as transit passengers have to walk to and from transit stops. In this paper, the multi-mode elastic-demand network equilibrium problem is formulated as a variational inequality problem where the combined mode and route choices are modeled in a hierarchical logit structures and the total travel demand for each origin-destination pair is explicitly given by an elastic demand function. In addition, the capacity constraint for transit vehicles and the effects of bi-directional flows on walkways are considered in the proposed model. All these congestion effects are taken into account for modeling the travel choices. A solution algorithm is developed to solve the multi-mode elastic-demand network equilibrium model. It is based on a Block Gauss-Seidel decomposition approach coupled with the method of successive averages. A numerical example is used to illustrate the application of the proposed model and solution algorithm. [ABSTRACT FROM AUTHOR]

The author reflects on the significance of the development of intelligent transportation systems (ITS). He notes that ITS makes it possible to improve the efficiency and reliability of transportation. The author also believes that the combined application of various ITS technologies may increase the capacity of existing road networks though more efficient road use.

This paper presents an off-line forecasting system for short-term travel time forecasting. These forecasts are based on the historical traffic count data provided by detectors installed on Annual Traffic Census (ATC) stations in Hong Kong. A traffic flow simulator (TFS) is developed for short-term travel time forecasting (in terms of offline forecasting), in which the variation of perceived travel time error and the fluctuations of origin-destination (O-D) demand are considered explicitly. On the basis of prior O-D demand and partial updated detector data, the TFS can estimate the link travel times and flows for the whole network together with their variances and covariances. The short-term travel time forecasting by O-D pair can also be assessed and the O-D matrix can be updated simultaneously. The application of the proposed off-line forecasting system is illustrated by a numerical example in Hong Kong. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including transit system fares, impact of routing strategies on transit network design problems, and the performance of a transit route for a fixed schedule.

The fare of a transit line is one of the important decision variables for transit network design. It has been advocated as an efficient means of coordinating the transit passenger flows and of alleviating congestion in the transit network. This paper shows how transit fare can be optimized so as to balance the passenger flow on the transit network and to reduce the overload delays of passengers at transit stops. A bi-level programming method is developed to optimize the transit fare under line capacity constraints. The upper-level problem seeks to minimize the total network travel time, while the lower-level problem is a stochastic user equilibrium transit assignment model with line capacity constraints. A heuristic solution algorithm based on sensitivity analysis is proposed. Numerical example is used to illustrate the application of the proposed model and solution algorithm. [ABSTRACT FROM AUTHOR]

The average annual daily traffic (AADT) volumes can be estimated by using a short period count of less than twenty-four hour duration. In this paper, the neural network method is adopted for the estimation of AADT from short period counts and for the determination of the most appropriate length of counts. A case study is carried out by analysing data at thirteen locations on trunk roads and primary roads in urban area of Hong Kong. The estimation accuracy is also compared with the one obtained by regression analysis approach. The results show that the neural network approach consistently performed better than the regression analysis approach. [ABSTRACT FROM AUTHOR]

This paper investigates the transportation network reliability based on the information provided by detectors installed on some links. A traffic flow simulator (TFS) model is formulated for assessing the network reliability (in terms of travel time reliability), in which the variation of perceived travel time error and the fluctuations of origin-destination (OD) demand are explicitly considered. On the basis of prior OD demand and partial updated detector data, the TFS can estimate the link flows for the whole network together with link/path travel times, and their variance and covariance. The travel time reliability by OD pair can also be assessed and the OD matrix can be updated simultaneously. A Monte Carlo based algorithm is developed to solve the TFS model. The application of the proposed TFS model is illustrated by a numerical example. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between the dwelling time of trains and the crowding situations at Mass Transit Railway (MTR) stations in Hong Kong. Regression models were established for the dwelling delays of trains due to congestion at stations, and a simulation model making use of the Monte-Carlo technique is developed to assess the reliability of the estimated train dwelling time. Therefore, the distribution and the confidence interval of the train dwelling time can be predicted on the basis of observed boarding and alighting distributions. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including new approaches for management of traffic in urban areas, advantages of implementation of traffic control systems on fuel consumption and optimization of traffic signals at intersections.

An introduction is presented in which the editor discusses various reports within the issue on topics including short-tem prediction models to predict average spot speeds, driver's dynamic route choice behaviour, and driver's route choice rules.

Recent comprehensive reviews on traveler behavior in transportation networks have been given by Asakura (1999), Alder (2001), Chatterjee et al. (2002), Bell (2002), Arentze and Timmermans (2005). However, the expansion of transportation networks and the emergence of new technologies have generated an urgent need for advanced models and solution algorithms so as to provide better understanding of the traveler behavior on networks in response to various changes. This special issue on 'Behavior in Networks' is a collection of selected papers presented at the International Workshop on Behavior in Networks held on 22nd −23rd July, 2004. The workshop placed greater emphasis on discussions of how new models and advanced methods can be used for giving better insights on travel behaviors in transportation networks particularly in view of the recent advancement of technologies. The workshop brought together experts in a behavior side as well as a transportation network side worldwide to discuss both recent research and future directions in this important field. The selected papers cover the important aspects of behavior in networks to enhance the realism of modeling in transport. [ABSTRACT FROM AUTHOR]

The author reflects on the significance of intelligent transport system (ITS). He notes that the introduction of ITS and the concept of reliability analysis has generated a need for better understanding of road network reliability under recurrent and nonrecurrent congestion cases. The author also believes that the ITS also triggers traffic engineers to research on transport network design and analysis.

An introduction is presented in which the editor discusses various reports within the issue on topics including the contribution of transport telematics to enhance bus operations, development of intelligent transportation system (ITS) technologies and fare deregulation.