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.     

A Pareto‐improving hybrid policy for transportation networks

This paper investigates an innovative Pareto‐improving hybrid policy that combines two policy instruments, that is, congestion pricing and road space rationing, and takes advantage of the synergistic effects between these instruments. Mathematical formulations for developing Pareto‐improving pure road space rationing schemes and hybrid policies are presented. Numerical examples demonstrate that the proposed hybrid policy offers greater flexibility and is more prominent in leading to Pareto improvement than both pure congestion pricing and road space rationing schemes. Copyright © 2013 John Wiley & Sons, Ltd.     

Computing dynamic user equilibria for large-scale transportation networks

In this paper, we present an approach for determining dynamic user equilibria. The method is suitable for disaggregated microscopic and mesoscopic simulation-based models. It is a modification of the convex-simplex method, which disposes with the line search step, and controls the subset of travelers to be re-routed at each step while updating the link travel times after each assignment. To guarantee finite termination, a suitable stopping criterion is adopted. The proposed method is implemented within TRANSIMS, the Transportation Analysis and Simulation System, as a two-stage process that employs a combined use of link performance functions and a microsimulator in order to design a framework suitable for application to real transportation systems. To demonstrate this capability, we apply the developed methodology to a large-scale network, Bignet, which is part of the transportation city network of Portland, Oregon; and a medium-scale network, Blacksburg, Virginia; and provide some comparative analyses. Our results exhibit that an improved distribution of travelers is obtained while consuming less than 17–33% of the effort required by the current version of TRANSIMS.     

Continuum modelling of transportation networks

The standard discrete transportation models, which attempt to determine traffic flow on every link of a transportation network, are inapplicable to complex dense urban networks, in view of the amount of computation involved. In this paper we adopt a radically new point of view and construct a family of models based on the assumption of continuous traffic distribution over the network. We derive the flow conservation equations and the equilibrium conditions for user-optimized and system-optimized networks.     

Substituting operational control for physical capacity in urban transportation

This paper develops recommendations for improving in an evolutionary manner the performance of our urban ground transportation systems. The strengths and limitations of present static control technology and current computer traffic signal and freeway surveillance and control systems in urban areas are described. A taxonomy of possible information and control configurations in urban traffic operations is developed. The alternatives in the taxonomy are analysed and used as the basis for recommending specific real time information and control functions for improving, in an evolutionary manner, the performance of urban ground transportation systems. The recommended improvements would allow for the first time a meaningful substitution of operational control for physical (static) capacity increases in urban transportation.     

Defining and measuring service availability for complex transportation networks

Service Availability of a transportation system is a measure of a performance that has been generally defined according to the reliability and maintainability terms of mean-time-before-failure and mean-time-to-restore, as borrowed from the aerospace/defense industry. While such definitions correctly describe the availability of a system and its equipment to function they do not directly measure the percent of designed and scheduled service available for passenger use. For the more complex transportation systems having multiple tracks and routes, fleets of vehicles, more than two stations and more than one mode of service there are needs for definitions that account for isolated failures that partially interrupt or delay service. Successful definitions of service availability have been based on data that is easily and directly entered in the operating log or automatically collected by Automatic Train Supervision (ATS) system and reports generated by software. The following paper first defines measures of service availability in current use and analyzes exact and approximation methods for data collection and computation. Second, the paper postulates and explores classical and new definitions of service availability applicable for complex networks such as Personal Rapid Transit (PRT). Insight is provided for choosing a suitable definition based on the type of transportation network.     

Risk-based maintenance and rehabilitation decisions for transportation infrastructure networks

A method for determining optimal risk-based maintenance and rehabilitation (M&R) policies for transportation infrastructure is presented. The proposed policies guarantee a certain performance level across the network under a predefined level of risk. The long-term model is formulated in the Markov Decision Process framework with risk-averse actions and transitional probabilities describing the uncertainty in the deterioration process. The well known Conditional Value at Risk (CVaR) is used as the measure of risk. The steady-state risk-averse M&R policies are modeled assuming no budget restriction. To address the short-term resource allocation problem, two linear programming models are presented to generate network-level polices with different objectives. While the proposed methodology is general and can be used with any performance indicator, pavement roughness is used for numerical studies and an analytical expression for computing CVaR is derived.     

Models for optimizing transportation networks and modal split in China

This paper summarizes the research in a project entitled “The Models for Optimizing Transportation Network and Modal Split in China”. The research background, procedure, various mathematical models used in traffic demands forecasting, modal split and network design are presented with the key results. The systematic optimization approach adopted in this paper for integrated planning of transport network and the rational modal split formulation is firstly proposed in China. Finally, further discussion on the difficulties of using transport modeling techniques in Chinese conditions is given.     

Performance indicators for public transit connectivity in multi-modal transportation networks

Connectivity plays a crucial role as agencies at the federal and state level focus on expanding the public transit system to meet the demands of a multimodal transportation system. Transit agencies have a need to explore mechanisms to improve connectivity by improving transit service. This requires a systemic approach to develop measures that can prioritize the allocation of funding to locations that provide greater connectivity, or in some cases direct funding towards underperforming areas. The concept of connectivity is well documented in social network literature and to some extent, transportation engineering literature. However, connectivity measures have limited capability to analyze multi-modal public transportation systems which are much more complex in nature than highway networks.In this paper, we propose measures to determine connectivity from a graph theoretical approach for all levels of transit service coverage integrating routes, schedules, socio-economic, demographic and spatial activity patterns. The objective of using connectivity as an indicator is to quantify and evaluate transit service in terms of prioritizing transit locations for funding; providing service delivery strategies, especially for areas with large multi-jurisdictional, multi-modal transit networks; providing an indicator of multi-level transit capacity for planning purposes; assessing the effectiveness and efficiency for node/stop prioritization; and making a user friendly tool to determine locations with highest connectivity while choosing transit as a mode of travel. An example problem shows how the graph theoretical approach can be used as a tool to incorporate transit specific variables in the indicator formulations and compares the advantage of the proposed approach compared to its previous counterparts. Then the proposed framework is applied to the comprehensive transit network in the Washington–Baltimore region. The proposed analysis offers reliable indicators that can be used as tools for determining the transit connectivity of a multimodal transportation network.     

Toward a data structure for computer-aided design of transportation networks

Although there are a great variety of transportation network design applications, there are important similarities across all transportation networks. These similarities permit the construction of a single, relatively simple, data structure that satisfies the needs of both graphics and algorithms. This paper describes how this data structure was implemented as the basis of the General Network Editor— a program for graphical preparation of network data.     

Improved reliability of public transportation using real-time transfer synchronization

Service reliability of public transportation (PT) systems is a dominant ingredient in what is perceived as the PT image. Unreliable service increases the uncertainties of simultaneous arrivals of vehicles at a transfer point. Implementing proper control actions leads to preventing missed transfers, one of the undesirable features of PT service and a major contributor to a negative image. The present work focuses on performance measurements of a PT system offering direct transfers on multi-legged trips. The method developed evaluates and improves system performance by applying selected operational tactics in real-time scenarios. In order to investigate the efficiency level of the PT system, five types of vehicle positional situations with reference to a transfer point are considered: considerably ahead of schedule, ahead of schedule, on schedule, behind schedule, and considerably behind schedule. Each situation contributes differently to the degree of system performance. The optimization framework developed results in selected operational tactics to attain the maximum number of direct (without waiting) transfers and minimize total passenger travel time. The implementation of the concept is performed in two steps: optimization and simulation. The optimization process searches for the best operational tactics, using the states of the five vehicle-position types, and the simulation serves to validate the optimal results under a stochastic framework using the concept of a multi-agent system. A case study of Auckland, New Zealand, is described for assessing the methodology developed. Results showed a 58% improvement in the system performance index compared to no-tactic operations.     

Optimal deployment of charging lanes for electric vehicles in transportation networks

Given the rapid development of charging-while-driving technology, we envision that charging lanes for electric vehicles can be deployed in regional or even urban road networks in the future and thus attempt to optimize their deployment in this paper. We first develop a new user equilibrium model to describe the equilibrium flow distribution across a road network where charging lanes are deployed. Drivers of electric vehicles, when traveling between their origins and destinations, are assumed to select routes and decide battery recharging plans to minimize their trip times while ensuring to complete their trips without running out of charge. The battery recharging plan will dictate which charging lane to use, how long to charge and at what speed to operate an electric vehicle. The speed will affect the amount of energy recharged as well as travel time. With the established user equilibrium conditions, we further formulate the deployment of charging lanes as a mathematical program with complementarity constraints. Both the network equilibrium and design models are solved by effective solution algorithms and demonstrated with numerical examples.     

Improving the accessibility of urban transportation networks for people with disabilities

What is the most effective way to enhance the accessibility of our oldest and largest public transportation systems for people with reduced mobility? The intersection of limits to government support with the growing mobility needs of the elderly and of people with disabilities calls for the development of tools that enable us to better prioritise investment in those areas that would deliver the greatest benefits to travellers. In principle and, to a lesser extent, in practice, many trains and buses are already accessible to nearly all users, leaving the stations and interchanges as the single largest and most expensive challenge facing operators trying to improve overall access to the network.Focussing on travel time and interchange differences, we present a method that uses network science and spatio-temporal analysis to rank stations in a way that minimises the divergence between accessible and non-accessible routes. Taking London as case study, we show that 50% of the most frequently followed journeys become 50% longer when wheelchair accessibility becomes a constraint. Prioritising accessibility upgrades using our network approach yields a total travel time that is more than 8 times better than a solution based on random choice, and 30% more effective than a solution that seeks solely to minimise the number of interchanges facing those with mobility constraints. These results highlight the potential for the analysis of ‘smart card’ data to enable network operators to obtain maximum value from their infrastructure investments in support of expanded access to all users.     

Counting the different efficient paths for transportation networks and its applications

This paper deals with an interesting problem about how to efficiently compute the number of different efficient paths between an origin‐destination pair for a transportation network because these efficient paths are the possible paths used by drivers to some extent. Based on a novel triangle operation derived, it first presents a polynomial‐time combinatorial algorithm that can obtain the number of different simple paths between any two nodes for an acyclic network as well as the total travel cost of these paths. This paper proceeds to develop a combinatorial algorithm with polynomial‐time complexity for both counting the different efficient paths between an origin‐destination pair and calculating the total travel cost of these paths. As for applications, this paper shows that the preceding two algorithms can yield the lower and upper bounds for the number of different simple paths between an origin‐destination pair, while it has already be recognized that a polynomial‐time algorithm getting such a number does not exist for a general network. Furthermore, the latter algorithm can be applied for developing a heuristic method for the traffic counting location problem arising from the origin‐destination matrix estimation problems.     

Optimal selection of build-operate-transfer projects on transportation networks

This paper considers the problem of how to select highway projects for the build-operate-transfer (BOT) development with the objective of improving the social benefit while ensuring the marketability of those selected. The problem can be viewed as a tri-level leader-follower game and is formulated as a mixed integer program with equilibrium constraints. Without solving the associated problem, we show that optimal tolls and travel times on selected BOT highways can be determined from their attributes under mild assumptions. This leads to an efficient heuristic algorithm for solving the project selection problem.     

Generation of logistics networks in freight transportation models

This article analyzes the concept of logistics networks in the context of behavioral freight transport modeling. Starting from the basic definition of networks, the different perceptions of networks in transportation science and logistics are worked out. The micro?Cmacro gap, as a main challenge in freight transport modeling, is explained by the existence of logistics networks on a meso level. A taxonomy of modeling methods dealing with logistics networks is defined, based on two characteristics: the changeability of networks within models (fixed, partially variable and variable networks) and the form of cost functions mapped (economies of scale, constant average cost, and diseconomies of scale). For each category, different possible modeling methods and their application in existing freight transport models are discussed. A special focus is placed on methodologies and models that map variable networks.     

Stability of transportation networks under adaptive routing policies

Growing concerns regarding urban congestion, and the recent explosion of mobile devices able to provide real-time information to traffic users have motivated increasing reliance on real-time route guidance for the online management of traffic networks. However, while the theory of traffic equilibria is very well-known, fewer results exist on the stability of such equilibria, especially in the context of adaptive routing policy. In this work, we consider the problem of characterizing the stability properties of traffic equilibria in the context of online adaptive route choice induced by GPS-based decision making. We first extend the recent framework of “Markovian Traffic Equilibria” (MTE), in which users update their route choice at each intersection of the road network based on traffic conditions, to the case of non-equilibrium conditions, while preserving consistency with known existence and uniqueness results on MTE. We then exhibit sufficient conditions on the network topology and the latency functions for those MTEs to be stable in the sense of Lyapunov for a single destination problem. For various more restricted classes of network topologies motivated by the observed properties of travel patterns in the Singapore network, under certain assumptions we prove local exponential stability of the MTE, and derive analytical results on the sensitivity of the characteristic time of convergence to network and traffic parameters. The results proposed in this work are illustrated and validated on synthetic toy problems as well as on the Singapore road network with real demand and traffic data.     

Partition‐based algorithm for estimating transportation network reliability with dependent link failures

Evaluating the reliability of a transportation network often involves an intensive simulation exercise to randomly generate and evaluate different possible network states. This paper proposes an algorithm to approximate the network reliability which minimizes the use of such simulation procedure. The algorithm will dissect and classify the network states into reliable, unreliable, and un‐determined partitions. By postulating the monotone property of the reliability function, each reliable and/or unreliable state can be used to determine a number of other reliable and/or unreliable states without evaluating all of them with an equilibrium assignment procedure. The paper also proposes the cause‐based failure framework for representing dependent link degradation probabilities. The algorithm and framework proposed are tested with a medium size test network to illustrate the performance of the algorithm.