Can rural older drivers meet their needs without a car? Stated adaptation responses from a GPS travel diary survey

Rural seniors are highly dependent on their automobile to meet their trip making needs, yet the effects of aging can make access to the vehicle difficult or impossible over time. The anticipated growth in the older person population, in concert with limited travel data available to support rural transportation planning in Canada suggests a disconnect between what rural older people may require for transportation and the availability of formal alternatives. Many will seek informal alternatives to driving, such as depending on friends and family, to meet their travel needs, but the degree is not well understood in the context of their actual vehicle usage and stated ability to adapt. This paper draws from a Global Positioning System (GPS)-based multi-day travel diary survey of a convenience sample of 60 rural older drivers (29 men, 31 women, average age of 69.6 years) from New Brunswick, Canada. Participants would rely on “friends and family” for 52% of all trips they undertook as driver in the survey, “walk or bike” for 14% of trips, and “not take the trip” in 34% of trips if they did not have access to a vehicle. The formal option of “Transit” was not selected as a viable alternative by any participant for any trip. “Medical trips”, “Shopping” and “Personal Errands” were the least discretionary of all trip types, yet the most difficult for participants to find alternate arrangements. This suggests the need to explore different models of service delivery, such as a community-supported, member-based rural shuttle service with volunteer and paid drivers that build on informal social networks and can provide service when friends and family are unavailable.     

The multi-objective network design problem using minimizing externalities as objectives: comparison of a genetic algorithm and simulated annealing framework

Incorporation of externalities in the Multi-Objective Network Design Problem (MO NDP) as objectives is an important step in designing sustainable networks. In this research the problem is defined as a bi-level optimization problem in which minimizing externalities are the objectives and link types which are associated with certain link characteristics are the discrete decision variables. Two distinct solution approaches for this multi-objective optimization problem are compared. The first heuristic is the non-dominated sorting genetic algorithm II (NSGA-II) and the second heuristic is the dominance based multi objective simulated annealing (DBMO-SA). Both heuristics have been applied on a small hypothetical test network as well as a realistic case of the city of Almelo in the Netherlands. The results show that both heuristics are capable of solving the MO NDP. However, the NSGA-II outperforms DBMO-SA, because it is more efficient in finding more non-dominated optimal solutions within the same computation time and maximum number of assessed solutions.     

Some managerial and technical issues in transport sector development projects

In development projects there is only one problem, but it is huge: everything is connected to everything else. The authors separated from the whole the following important issues: (1) Project management and coordination: The Recipient Country’s Aid Coordination Unit (ACU) and Project Implementation Unit (PIU) staffed with competent local experts are necessary to hold the reform process memory. This issue is considered in the context of “Ownership” and “Government Leadership” as it is recognized in donor aid forums in the last decade. (2) Human resource development: Most technical assistance is oriented toward providing solutions, and the development of local capacities is ignored. The authors point out the importance of specially selected local experts—the “Technical Communication Officers”. (3) Institutional functioning: A ‘process consultation’ approach to institutional restructuring is promoted in which the Recipient has the key role. It is also recommended that the Recipient is the initiator of technical assistance in the projects. (4) Design standards are a recurrent and difficult problem. Recommendations are necessary how to transit to the new standards and how to mediate their approval process. (5) Procurement and management of consulting services: The authors argue that the recipient country qualified professionals have to be in the lead role. The vignettes in the paper are from the “real world” although they are modified slightly to protect privacy.     

Designing personal rapid transit (PRT) networks

This paper presents a heuristic method for designing a PRT network. Because the PRT system operating characteristics and performance measures differ widely from those of conventional transit technologies, an algorithm for the PRT network design problem (NDP) is derived by using concepts from some current NDP algorithms. We minimize the sum of passenger travel time cost, construction cost, vehicle cost and operational costs, subject to an available budget of guideway, a maximum number of vehicles and given link capacities. Starting with a well-connected initial network, the algorithm eliminates and adds links iteratively as it searches for a near-optimal solution. If this solution satisfies the budget constraint, it is considered to be acceptable. Otherwise, additional links are deleted until a feasible near-optimal solution is obtained. The link elimination phase of the algorithm only considers half of the links at a time which greatly decreases computing time. None of the links in an acceptable solution will be overloaded.     

Co-design of traffic network topology and control measures

The two main directions to improve traffic flows in networks involve changing the network topology and introducing new traffic control measures. In this paper, we consider a co-design approach to apply these two methods jointly to improve the interaction between different methods and to get a better overall performance. We aim at finding the optimal network topology and the optimal parameters of traffic control laws at the same time by solving a co-optimization problem. However, such an optimization problem is usually highly non-linear and non-convex, and it possibly involves a mixed-integer form. Therefore, we discuss four different solution frameworks that can be used for solving the co-optimization problem, according to different requirements on the computational complexity and speed. A simulation-based study is implemented on the Singapore freeway network to illustrate the co-design approach and to compare the four different solution frameworks.     

Exploring the propensity to perform social activities: a social network approach

Conceptual and empirical models of the propensity to perform social activity–travel behavior are described, which incorporate the influence of individuals’ social context, namely their social networks. More explicitly, the conceptual model develops the concepts of egocentric social networks, social activities, and social episodes, and defines the three sets of aspects that influence the propensity to perform social activities: individuals’ personal attributes, social network composition, and information and communication technology interaction with social network members. Using the structural equation modeling (SEM) technique and data recently collected in Toronto, the empirical model tests the effect of these three aspects on the propensity to perform social activities. Results suggest that the social networks framework provides useful insights into the role of physical space, social activity types, communication and information technology use, and the importance of “with whom” the activity was performed with. Overall, explicitly incorporating social networks into the activity–travel behavior modeling framework provides a promising framework to understand social activities and key aspects of the underlying behavioral process. Juan Antonio Carrasco a PhD candidate in Civil Engineering at the University of Toronto, holds a MSc degree in Transportation Engineering from the Pontificia Universidad Católica de Chile. His doctoral research explores the relationships between social networks, activity–travel behavior, and ICTs. His research interests also include microsimulation, land use-transportation, and econometric modeling. Eric J. Miller is Bahen-Tanenbaum Professor of Civil Engineering at the University of Toronto where he is also Director of the Joint Program in Transportation. His research interests include integrated land-use/transportation modeling, activity-based travel modeling, microsimulation and sustainable transportation planning.     

Should we abandon activity type analysis? Redefining activities by their salient attributes

This paper poses a challenge and begins a search. The challenge is to reconsider the usefulness of traditional activity types (“work”, “shopping”, etc.) in the understanding and modelling of travel behaviour. The search is for the more salient attributes of activities that may serve to better explain complex travel behaviours—such as activity scheduling and tour formation. In particular, this paper focuses on explicit measures of the spatial, temporal and interpersonal flexibility of activities, along with several traditional attributes (frequency, duration, involved persons, travel time, and location). Data from a recent in-depth week-long activity scheduling survey was used to define and compare these attributes. Results show that considerable variability in the attributes between and within traditional activity groups is evident. This casts considerable uncertainty on assumptions that statically assign levels of spatial, temporal, and interpersonal flexibility to any given activity type. A Principal Components Analysis further revealed eight new distinct clusters of activities that share like attributes. The relative role of each attribute in each component is examined, and subjective interpretations emerged (e.g., “Long and frequent”, “Space and time flexible” “Social networking”). The implications of these results for future model development and research are discussed. Future research should continue to expand the search for salient attributes and link them more directly to decision processes.     

Tests of assignment accuracy: An interurban case study

This paper is concerned with methods of testing the accuracy of traffic assignments. It focuses on the fact that whereas assignment models are usually based on a behavioural hypothesis about drivers' route choice (e.g. cost or time minimisation) the test of the accuracy of the assignment is the extent to which observed link loadings are reproduced. This inconsistency opens up the doubt that an apparently “accurate” assignment on this basis may be a result of compensating errors. It is difficult to apply the same test to accuracy of route choices as is applied to accuracy of link loadings (e.g. chi square, correlation coefficient) and hence a new measure is devised here which can be applied both to comparisons between observed and predicted route choices and comparisons between observed and predicted loadings. It is, moreover, possible to devise a test of significance for this measure so that one can test whether a predicted assignment is significantly different from what one, might have observed on the basis of chance observation. A case study is carried out to test the proposed method. Traffic flows between 72 origins and destinations on either side of the Pennine Mountains in Britain are assigned to a network using different assignment techniques with varied parameters. In all, one hundred and ninety assignments are carried out and the degree of correspondence between observed and predicted route choices and link loadings is measured. The results tend to confirm that the link loadings criterion is not a very stable criterion and that the route choice correspondence criteria seems to behave in a sensible way. A simulation exercise is carried out which produces the probability distribution of the “route-fit” index for different assumed sample levels. The paper concludes by suggesting avenues for further research.     

A stochastic multimodal reliable network design problem under adverse weather conditions

This paper formulates a network design problem (NDP) for finding the optimal public transport service frequencies and link capacity expansions in a multimodal network with consideration of impacts from adverse weather conditions. The proposed NDP aims to minimize the sum of expected total travel time, operational cost of transit services, and construction cost of link capacity expansions under an acceptable level of variance of total travel time. Auto, transit, bus, and walking modes are considered in the multimodal network model for finding the equilibrium flows and travel times. In the proposed network model, demands are assumed to follow Poisson distribution, and weather‐dependent link travel time functions are adopted. A probit‐based stochastic user equilibrium, which is based on the perceived expected travel disutility, is used to determine the multimodal route of the travelers. This model also considers the strategic behavior of the public transport travelers in choosing their routes, that is, common‐line network. Based on the stochastic multimodal model, the mean and variance of total travel time are analytical estimated for setting up the NDP. A sensitivity‐based solution algorithm is proposed for solving the NDP, and two numerical examples are adopted to demonstrate the characteristics of the proposed model. Copyright © 2014 John Wiley & Sons, Ltd.     

Transport Network Design Problem under Uncertainty: A Review and New Developments

This paper aims to provide a state-of-the-art review of the transport network design problem (NDP) under uncertainty and to present some new developments on a bi-objective-reliable NDP (BORNDP) model that explicitly optimizes the capacity reliability and travel time reliability under demand uncertainty. Both are useful performance measures that can describe the supply-side reliability and demand-side reliability of a road network. A simulation-based multi-objective genetic algorithm solution procedure, which consists of a traffic assignment algorithm, a genetic algorithm, a Pareto filter, and a Monte-Carlo simulation, is developed to solve the proposed BORNDP model. A numerical example based on the capacity enhancement problem is presented to demonstrate the tradeoff between capacity reliability and travel time reliability in the NDP.     

Optimizing one‐way traffic network reconfiguration and lane‐based non‐diversion routing for evacuation

Unfortunately, situations such as flood, hurricanes, chemical accidents, and other events occur frequently more and more. To improve the efficiency and practicality of evacuation management plan, an integrated optimization model of one‐way traffic network reconfiguration and lane‐based non‐diversion routing with crossing elimination at intersection for evacuation is constructed in this paper. It is an integrated model aiming at minimizing the network clearance time based on Cell Transmission Model. A hybrid algorithm with modified genetic algorithm and tabu search method is devised for approximating optimal problem solutions. To verify the effectiveness of the proposed model and solving method, two cases are illustrated in this paper. Through the first example, it can be seen that the proposed model and algorithm can effectively solve the integrated problems, and compared with the objective value of the original network, the network clearance time of the final solution reduces by 47.4%. The calculation results for the realistic topology and size network of Ningbo in China, which locates on the east coast of the Pacific Ocean, justify the practical value of the model and solution method, and solutions under different settings of reduction amount of merging cell capacity embody obvious differences. Copyright © 2015 John Wiley & Sons, Ltd.     

Dynamic traffic metering in urban street networks: Formulation and solution algorithm

Traffic metering offers great potential to reduce congestion and enhance network performance in oversaturated urban street networks. This paper presents an optimization program for dynamic traffic metering in urban street networks based on the Cell Transmission Model (CTM). We have formulated the problem as a Mixed-Integer Linear Program (MILP) capable of metering traffic at network gates with given signal timing parameters at signalized intersections. Due to the complexities of the MILP model, we have developed a novel and efficient solution approach that solves the problem by converting the MILP to a linear program and several CTM simulation runs. The solution algorithm is applied to two case studies under different conditions. The proposed solution technique finds solutions that have a maximum gap of 1% of the true optimal solution and guarantee the maximum throughput by keeping some vehicles at network gates and only allowing enough vehicles to enter the network to prevent gridlocks. This is confirmed by comparing the case studies with and without traffic metering. The results in an adapted real-world case study network show that traffic metering can increase network throughput by 4.9–38.9% and enhance network performance.     

A three-dimensional macroscopic fundamental diagram for mixed bi-modal urban networks

Recent research has studied the existence and the properties of a macroscopic fundamental diagram (MFD) for large urban networks. The MFD should not be universally expected as high scatter or hysteresis might appear for some type of networks, like heterogeneous networks or freeways. In this paper, we investigate if aggregated relationships can describe the performance of urban bi-modal networks with buses and cars sharing the same road infrastructure and identify how this performance is influenced by the interactions between modes and the effect of bus stops. Based on simulation data, we develop a three-dimensional vehicle MFD (3D-vMFD) relating the accumulation of cars and buses, and the total circulating vehicle flow in the network. This relation experiences low scatter and can be approximated by an exponential-family function. We also propose a parsimonious model to estimate a three-dimensional passenger MFD (3D-pMFD), which provides a different perspective of the flow characteristics in bi-modal networks, by considering that buses carry more passengers. We also show that a constant Bus–Car Unit (BCU) equivalent value cannot describe the influence of buses in the system as congestion develops. We then integrate a partitioning algorithm to cluster the network into a small number of regions with similar mode composition and level of congestion. Our results show that partitioning unveils important traffic properties of flow heterogeneity in the studied network. Interactions between buses and cars are different in the partitioned regions due to higher density of buses. Building on these results, various traffic management strategies in bi-modal multi-region urban networks can then be integrated, such as redistribution of urban space among different modes, perimeter signal control with preferential treatment of buses and bus priority.     

Incorporating Driver Behaviors in Network Design Problems: Challenges and Opportunities

The goal of a network design problem (NDP) is to make optimal decisions to achieve a certain objective such as minimizing total travel time or maximizing tolls collected in the network. A critical component to NDP is how travelers make their route choices. Researchers in transportation have adopted human decision theories to describe more accurate route choice behaviors. In this paper, we review the NDP with various route choice models: the random utility model (RUM), random regret-minimization (RRM) model, bounded rationality (BR), cumulative prospect theory (CPT), the fuzzy logic model (FLM) and dynamic learning models. Moreover, we identify challenges in applying behavioral route choice models to NDP and opportunities for future research.     

Distributed optimization and coordination algorithms for dynamic speed optimization of connected and autonomous vehicles in urban street networks

Dynamic speed harmonization has shown great potential to smoothen the flow of traffic and reduce travel time in urban street networks. The existing methods, while providing great insights, are neither scalable nor real-time. This paper develops Distributed Optimization and Coordination Algorithms (DOCA) for dynamic speed optimization of connected and autonomous vehicles in urban street networks to address this gap. DOCA decomposes the nonlinear network-level speed optimization problem into several sub-network-level nonlinear problems thus, it significantly reduces the problem complexity and ensures scalability and real-time runtime constraints. DOCA creates effective coordination in decision making between each two sub-network-level nonlinear problems to push solutions towards optimality and guarantee attaining near-optimal solutions. DOCA is incorporated into a model predictive control approach to allow for additional consensus between sub-network-level problems and reduce the computational complexity further. We applied the proposed solution technique to a real-world network in downtown Springfield, Illinois and observed that it was scalable and real-time while finding solutions that were at most 2.7% different from the optimal solution of the problem. We found significant improvements in network operations and considerable reductions in speed variance as a result of dynamic speed harmonization.     

A route-based solution algorithm for dynamic user equilibrium assignments

The aim of this study is to establish a method to calculate good quality user equilibrium assignments under time varying conditions. For this purpose, it introduces a dynamic network loading method that can maintain correct flow propagation as well as flow conservation, and it shows a novel route-based solution algorithm. This novel algorithm turns out to be convenient and logically plausible compared to the conventional [Frank, M., Wolfe, P., 1956. An algorithm for quadratic programming. Naval Research Logistics Quarterly 3, 95–110] algorithm, because the former does not require evaluation of an objective function and it finds solutions maintaining correct flow propagation in the time-varying network conditions. The application of novel dynamic network loading method and solution algorithm to test networks shows that we can find high quality dynamic user equilibrium assignment. This is illustrated in an example network using the deterministic queuing model for a link performance function and associating costs and flows in a predictive way in discrete time.     

Travel time ratio: the key factor of spatial reach

An important aspect of reach and accessibility is the time people are willing to spend on reaching activity places. In this paper we see the issue of travel time in an alternative way. Instead of looking at travel time separated from time spent on activities, we examine the relation between travel time and stay time. We operationalize this relation with the concept “travel time ratio”. A hypothetical framework underlying these travel time ratios is displayed. We show that for similar types of activity places the value of travel time ratio are in accordance with each other. We find large differences between trips for mandatory activities and trips for discretionary activities. The results indicate the stability of the travel time ratios. Finally, some implications for future research and policy will be mentioned. This revised version was published online in June 2006 with corrections to the Cover Date.     

Managing passenger behavioral intention: an integrated framework for service quality,satisfaction, perceived value,and switching barriers

This paper seeks to improve our understanding of passengers’ behavioral intention by proposing an integrated framework from the attitudinal perspective. According to the literature in marketing research, we establish a causal relationship model that considers “service quality-satisfaction-behavioral intentions” paradigm, perceived value theory, and switching barrier theory. Exploring passengers’ behavioral intention from satisfaction and perceived value help to understand how passengers are attracted by the company, while switching barriers assist in realizing how passengers are “locked” into a relationship with the current company. Furthermore, in order to capture the nature of service quality, we adopt a hierarchical factor structure which serves service quality as the higher-order factor. In this study, coach industry is selected as our research subject. The empirical results, as hypothesized, show that all causal relationships are statistically significant, and perceived value us the most important predictor of satisfaction and passengers’ behavioral intention. In conclusion, the managerial implications and suggestions for future research are discussed.     

Network Signal Setting Design: Meta-heuristic optimisation methods

This paper aims to investigate the application of meta-heuristic optimisation methods to Network Signal Setting Design. The adopted approaches are (i) three step optimisation, in which first the stage matrix (stage composition and sequence), the green timings at each single junction are optimised, then the node offsets are computed in three successive steps; (ii) two step optimisation, in which the stage matrix is defined at a first step, then the green timings and the node offsets are computed at a second step. In both approaches the stage matrix optimisation is carried out through explicit complete enumeration.In the first approach multi-criteria optimisation is followed for single junction signal setting design (green timings), whilst the coordination (node offsets) is approached through mono-criterion optimisation, as well as for the synchronisation (green timings and offsets) in the second approach.A new traffic flow model mixing CTM and PDM has been applied. This model allows to explicitly represent horizontal queuing phenomena as well as dispersion along a link. Some meta-heuristic algorithms (i.e. Genetic Algorithms, Hill Climbing and Simulated Annealing) are investigated in order to solve the two problems.The proposed strategies are applied to two different layouts (a two junction arterial vs. a four junction network) and their effectiveness is evaluated by comparing the obtained results with those from benchmark approaches implementing mono-criterion optimisation only.     

Application of Ant System to network design problem

Network design problem (NDP) is the problem of choosing from among a set of alternative projects which optimizes an objective (e.g., minimizes total travel time), while keeping consumption of resources (e.g., budget) within their limits. This problem is difficult to solve, because of its combinatorial nature and nonconvexity of the objective function. Many algorithms are presented to solve the problem more efficiently, while trading-off accuracy with computational speed. This increase in speed stems from certain approximations in the formulation of the problem, decomposition, or heuristics. This study adapts a meta – heuristic approach to solve NDP, namely Ant System (AS). The algorithm is first designed, and then calibrated to solve NDP for the Sioux Falls test network. The behavior of the algorithm is then investigated. The result seems encouraging.