Modeling capacity flexibility of transportation networks

Flexibility of the transportation system is one of the important performance measures needed to deal with demand changes. In this paper, we provide a quantitative assessment of capacity flexibility for the passenger transportation network using bi-level network capacity models. Two approaches for assessing the value of capacity flexibility are proposed. One approach is based on the concept of reserve capacity, which reflects the flexibility with respect to changes in terms of demand volume only. The second approach allows for variations in the demand pattern in addition to changes in demand volume in order to more fully capture demand changes. Two models are developed in the second approach to consider two types of capacity flexibility. The total capacity flexibility allows all users to have both route choice and destination choice when estimating capacity flexibility. The limited capacity flexibility estimates how much more demand volume could be added to a fixed demand pattern by allowing the additional demand to deviate from the fixed demand pattern. Numerical examples are provided to demonstrate the different concepts of capacity flexibility for a passenger transportation system under demand changes.     

Real-time congestion pricing strategies for toll facilities

This paper analyzes the dynamic traffic assignment problem on a two-alternative network with one alternative subject to a dynamic pricing that responds to real-time arrivals in a system optimal way. Analytical expressions for the assignment, revenue and total delay in each alternative are derived as a function of the pricing strategy. It is found that minimum total system delay can be achieved with many different pricing strategies. This gives flexibility to operators to allocate congestion to either alternative according to their specific objective while maintaining the same minimum total system delay. Given a specific objective, the optimal pricing strategy can be determined by finding a single parameter value in the case of HOT lanes. Maximum revenue is achieved by keeping the toll facility at capacity with no queues for as long as possible. Guidelines for implementation are discussed.     

Application of advanced sampling for efficient probabilistic traffic modelling

In probabilistic traffic models, consideration of stochasticity in the dynamics of traffic gives a closer representation of a traffic system in comparison to that of a deterministic approach. Monte Carlo simulation is a broadly accepted method to consider variations in traffic within modelling. In this contribution, the possibility of increasing the efficiency of probabilistic traffic flow models using Monte Carlo simulation is analysed using variance reduction techniques and sequencing, for varied capacity and traffic demand values. The techniques of Importance Sampling, Latin Hypercube Sampling and Quasi-Random Sequencing are compared in a dynamic macroscopic traffic model to demonstrate the effectiveness of these techniques for reduction of the computational load when considering multiple input variations. Demonstration of their efficiency in traffic modelling is expected to lead to a wider application of the methods in practice.     

Modelling of motorised two-wheelers: a review of the literature

Motorised two-wheeler (MTW) has emerged as the most widely used transportation mode for short distance trips in many Asian and European countries because of its affordable price and flexibility in manoeuvring through traffic. Its small size and aggressive riding patterns can considerably affect the overall traffic flow characteristics and safety. Modelling the characteristic behaviour and complex movement patterns of motorised two-wheelers is essential due to their pronounced role in microscopic traffic simulations, traffic management strategies, safety evaluation, transport planning and intelligent transportation systems. This paper begins with an overview of the determinant factors used for MTW modelling, followed by a critical review of various modelling approaches that have been adopted to depict the movement patterns of MTWs. The review concentrates on (i) identifying the factors mostly studied with respect to MTW-research, (ii) discussing the potential and limitations of each modelling approach and (iii) reporting some of the aspects that need further consideration for modelling MTWs in heterogeneous mixed traffic streams. The findings of the paper suggest that an integrated approach can be more viable to depict the unique riding patterns of motorised two-wheelers and some possible directions for future studies are also proposed.     

Network structure,capacity growth and route hierarchies: the case of China’s air traffic system revisited

This paper examines air traffic patterns among China’s scheduled airlines in January 2006 and January 2011, using Official Airline Guide data on carrier schedules. The author classifies Chinese carriers into one of four classes. Airports are also organized into a classification scheme based on several criteria related to the total volume of traffic, the carriers serving the airports and the nature of the airports to which they are connected. Counts, sums, percentage shares and changes in these calculations between 2006 and 2011 are presented in tabular form. Inferences about the fundamental structure and future patterns of capacity growth for the yet not fully emerged Chinese air traffic system can be drawn.     

Study on road section environmental traffic capacity model and algorithm under double constraints

The coordinated development of city traffic and environment is a key research content in traffic field in twenty-first Century. Among them, road section environmental traffic capacity analysis is one of the important research issues. It can provide solid theoretical basis and reliable data support for road network traffic optimization control, road traffic pollution control and city traffic structure optimization. This paper analyzed main factors which impacted environmental traffic capacity from two aspects, including road capacity constraint conditions and road traffic pollution control constraint conditions. Then, road section environmental traffic capacity optimization model was established, and method of improved augmented Lagrange function was used to solve the model. Case study showed that, (1) The environmental traffic capacity optimal model and methodology were effective; (2) In order to ensure road section environmental traffic capacity greater than (or equal to) road capacity, some measures could be taken including adjusting motor vehicle type proportion as well as improving emission characteristics of motor vehicles exhausting pollutants.     

Robust identification of air traffic flow patterns in Metroplex terminal areas under demand uncertainty

Multi-Airport Systems (MAS), or Metroplexes, serve air traffic demand in cities with two or more airports. Due to the spatial proximity and operational interdependency of the airports, Metroplex airspaces are characterized by high complexity, and current system structures fail to provide satisfactory utilization of the available airspace resources. In order to support system-level design and management towards increased operational efficiency in such systems, an accurate depiction of major demand patterns is a prerequisite. This paper proposes a framework for the robust identification of significant air traffic flow patterns in Metroplex systems, which is aligned with the dynamic route service policy for the effective management of Metroplex operations. We first characterize deterministic demand through a spatio-temporal clustering algorithm that takes into account changes in the traffic flows over the planning horizon. Then, in order to handle uncertainties in the demand, a Distributionally Robust Optimization (DRO) approach is proposed, which takes into account demand variations and prediction errors in a robust way to ensure the reliability of the demand identification. The DRO-based approach is applied on pre-tactical (i.e. one-day planning) as well as operational levels (i.e. 2-h rolling horizon). The framework is applied to Time Based Flow Management (TBFM) data from the New York Metroplex. The framework and results are validated by Subject Matter Experts (SMEs).     

Optimal allocation of turns to lanes at an isolated signal-controlled junction

Conventional design methods require the lane marking patterns, which are painted on ground showing road users the permissible turning directions on different approach lanes, as exogenous inputs to define the traffic stream grouping for analysis. This predefined grouping of traffic movements may restrict the design of signal timings in the optimisation procedures. More recently, a lane-based design method has been developed to relax the lane markings as binary-type control variables in a mathematical programming approach. The lane marking patterns and the signal timings can then be optimised simultaneously in a unified framework. This paper presents an extension work to further relax the numbers of approach lane in traffic arms as new integer variables which can then be optimised to give optimal lane arrangement in various arms of a junction to manage the given traffic demands more efficiently. All well-defined signal timings variables in the phase-based approach as well as the lane marking and lane flow variables in the lane-based approach together with their governing constraints are all preserved in the new formulation for the reserve capacity optimisation of isolated signal-controlled junctions.     

Quantifying uncertainties in a national forecasting model

Uncertainties related to demand model system outputs is an important issue in travel demand models. This paper focuses on uncertainties arisen from the fact that models are estimated on a sample of the population (and not the whole population). Forecasting systems can be quite complex, and may contain procedures that not easily permit analytically derived statistical measures of uncertainty. In this paper, the possibilities to use computer-intensive numerical methods to compute statistical measures for very complex systems, without being bound to an analytical approach, are explored. Here, the bootstrap method is used to obtain statistical measures of outputs produced by the forecasting system SAMPERS. The SAMPERS system is used by Swedish transport authorities. The bootstrap method is briefly described as well as the procedure of applying bootstrap on the SAMPERS system. Numerical results are presented for selected forecast results at different levels such as total traffic demand, origin–destination demand, train line demand and the demand on specific links. Also, the uncertainty related to the value of time estimate is analysed.     

Lane-harmonised passenger car equivalents for heterogeneous expressway traffic

In order to account for variations in traffic composition during traffic analysis, passenger car equivalent (PCE) factors are used to convert flow rates of various vehicle classes into flow rates in terms of passenger car units (PCUs). Earlier studies have developed various methods to estimate PCE values but only a few of them are based on uninterrupted traffic flow, particularly for flow regimes with heterogeneous traffic where differential (lower) speed limits are imposed on commercial vehicles. This paper proposes a lane-harmonisation approach, which leverages on the high variation in traffic composition across the lanes, to estimate PCE factors for urban expressways. Multiple linear regression is used and the PCE factors obtained for motorcycles, light goods vehicles, and heavy goods vehicles are 0.65, 1.53, and 2.75, respectively. The estimated capacity flow rate after the application of the obtained PCE factors is around 2200 PCUs per hour per lane.     

Benchmarking airports with specific safety performance measures

The purpose of this paper is to develop safety performance measures and test the measures on data for air traffic management failure events. Failure events are classified by the severity of the consequence of occurrence, resulting in the rate of occurrence in severity categories. The safety measures are standard statistics calculated from this “distribution” for comparison of airport operations by stochastic ordering. For comparisons a benchmark is developed from the aggregation of failure data on a set of comparable airports. Airport performance is then compared with the benchmark using the defined safety measures. The benchmark comparison was implemented with failure data for major airports in Canada from 2005 to 2012. The results show a number of patterns and anomalies and some airports perform poorly in comparison to a class of similar operations. We conclude by suggesting benchmarking safety measures as a natural addition to the information system on aviation safety compiled by a national regulatory body to unravel anomalies such as implementation problems of a safety management system.     

A multiclass cell transmission model for shared human and autonomous vehicle roads

Autonomous vehicles have the potential to improve link and intersection traffic behavior. Computer reaction times may admit reduced following headways and increase capacity and backwards wave speed. The degree of these improvements will depend on the proportion of autonomous vehicles in the network. To model arbitrary shared road scenarios, we develop a multiclass cell transmission model that admits variations in capacity and backwards wave speed in response to class proportions within each cell. The multiclass cell transmission model is shown to be consistent with the hydrodynamic theory. This paper then develops a car following model incorporating driver reaction time to predict capacity and backwards wave speed for multiclass scenarios. For intersection modeling, we adapt the legacy early method for intelligent traffic management (Bento et al., 2013) to general simulation-based dynamic traffic assignment models. Empirical results on a city network show that intersection controls are a major bottleneck in the model, and that the legacy early method improves over traffic signals when the autonomous vehicle proportion is sufficiently high.     

A flexible terminal/mobile lounge system for expanding the capacity of existing airports

One of the great dilemmas facing major airports is the problem of capacity and seasonal surges of activity. This paper suggests a system of small, inexpensive Airport Terminal Modules, which together with a new type of Mobile Lounge, could make available a considerable degree of flexibility. The ATM's are designed to allow maximum variations of aircraft type and passenger load as well as high ground utilization. This concept would allow major airports to be extended with a minimum of inconvenience as demand becomes apparent, thereby allowing financial expenditure to be carefully controlled and more evenly spread.     

Traffic performance of shared lanes at signalized intersections based on cellular automata modeling

Shared lanes at signalized intersections are designed for use by vehicles of different movement directions. Shared lane usage increases the flexibility of assigning lane grouping to accommodate variable traffic volume by direction. However, a shared lane is not always beneficial as it can at time result in blockage that leads to both capacity and safety constraints. This paper establishes a cellular automata model to simulate traffic movements at signalized intersections with shared lanes. Several simulation experiments are carried out both for a single shared lane and for an approach with a shared lane. Simulation of a single shared lane used by straight‐through and right‐turn (as similar to left‐turn in the USA) vehicles suggests that the largest travel delay occurs when traffic volumes (vehicles/lane) of the two movement streams along the shared lane are at about the same level. For a trial lane‐group with a shared lane, when traffic volumes of the two movement streams are quite different, the shared lane usage is not efficient in terms of reduction in traffic delay. The simulation results are able to produce the threshold traffic volume to arrange a shared lane along an approach. Copyright © 2013 John Wiley & Sons, Ltd.     

Genetics of traffic assignment models for strategic transport planning

This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic assignment models can be described by three genes. The first gene determines the spatial capability (unrestricted, capacity restrained, capacity constrained, and capacity and storage constrained) described by four spatial assumptions (shape of the fundamental diagram, capacity constraints, storage constraints, and turn flow restrictions). The second gene determines the temporal capability (static, semi-dynamic, and dynamic) described by three temporal assumptions (wave speeds, vehicle propagation speeds, and residual traffic transfer). The third gene determines the behavioural capability (all-or-nothing, one shot, and equilibrium) described by two behavioural assumptions (decision-making and travel time consideration). This classification provides a deeper understanding of the often implicit assumptions made in traffic assignment models described in the literature. It further allows for comparing different models in terms of functionality, and paves the way for developing novel traffic assignment models.     

Network models in traffic management and control

Abstract

The context for network modelling in traffic management and control is described in terms of the current area‐wide nature of traffic management and the range of objectives to which it can contribute. Representation of a road system and traffic management measures in terms of nodes and links and parameters associated with them is described. It is shown that the pattern of traffic has to be represented not only in terms of flows on links of the network but also in terms of numbers of movements per unit time between points of entry to and points of exit from the area being modelled. In modelling so far, these numbers of movements are regarded as given, but the routes taken are estimated by traffic assignment. Models can so far be used for comparison of a range of given schemes and for optimization of traffic control within a scheme. Variation over time is a central feature of the modelling, and this requires the use of time‐dependent queueing theory, and the specification of numbers of movements for a succession of periods of between 10 and 30 minutes. Theoretical approaches to the resulting problems of modelling and optimization are discussed, and the ways in which these are supplemented by heuristic methods in currently available models is described. Some requirements‐for further research are outlined.     

Random covariance heterogeneity in discrete choice models

In this paper, we extend the standard discrete choice modelling framework by allowing for random variations in the substitution patterns between alternatives across respondents, leading to increased model flexibility. The paper shows how such a Mixed Covariance model can be specified either with purely random variation or with a mixture of random and deterministic variation. Additionally, the model can be based on an underlying GEV or ECL structure. Finally, the model can be specified as a continuous mixture or as a discrete mixture. An application on Stated Preference data for the choice of departure time and travel mode shows that important gains in model performance can be obtained by allowing for random covariance heterogeneity. Furthermore, the approach leads to significant differences in the implied willingness to pay measures, and the substitution patterns between alternatives.     

Developing evasive action‐based indicators for identifying pedestrian conflicts in less organized traffic environments

There has been a growing interest in using surrogate safety measures such as traffic conflicts to analyse road safety from a broader perspective than collision data alone. This growing interest has been aided by recent advances in automated video‐based traffic conflict analysis. The automation enables accurate calculation of various conflict indicators such as time‐to‐collision and post‐encroachment time. These indicators rely on road users getting within specific temporal and spatial proximity from each other and therefore assume that proximity is a surrogate for conflict severity. However, this assumption may not be valid in many driving environments where close interactions between road users are common. The objective of this paper is to investigate the applicability of time proximity conflict indicators for evaluating pedestrian safety in less‐organized traffic environments with a high mix of road users. Several alternative behavioural conflict indicators based on detecting pedestrian evasive actions are recommended to better measure traffic conflicts in such traffic environments. These indicators represent variations in the spatio‐temporal gait parameters (step length, step frequency and walk ratio) immediately before the conflict point. A highly congested shared intersection in Shanghai, China, with frequent pedestrian conflicts is used as a case study. Traffic conflicts are analysed with the use of automated video‐based analysis techniques. The results showed that evasive action‐based indicators have higher potential to identify pedestrian conflicts and measure their severity in high mix less organized traffic environments than time proximity measures such as time‐to‐collision and post‐encroachment time. Copyright © 2016 John Wiley & Sons, Ltd.