Travel Route Choice Research Articles

Empirical Analysis of Decision-Making and Tour Formation Process

The decision-making processes behind activity–travel planning and tour formation are still insufficiently understood. This lack of understanding is especially true in regard to seniors, the fastest growing age group in the United States. To understand these processes, activity–travel planning data collected in the Urban Travel Route and Activity Choice Survey for Chicago, Illinois, were analyzed. In this analysis, the activity planning behavior exhibited by respondents 65 years of age and older was compared with that of respondents younger than 65. The planning horizons and flexibilities of activity–travel attributes as well as the motivations for planning decisions were analyzed. Results revealed that elderly people tended to make fewer routine and more preplanned decisions, whereas younger people made more routine or impulsive decisions. People were highly inflexible in regard to activity location choice, but they were much more flexible when making timing decisions. An analysis of tour formation revealed that advanced age played a role in trip chaining behavior and that differences between younger and older people were observed in temporal distribution of tours, the activity planning horizon, and multistop-tour mode choice. These results re important because of the general unavailability of such decision-making process data.

Estimating Route Choice and Travel Time Reliability with Field Observations of Bluetooth Probe Vehicles

Route choice is often assessed with either a modeling technique or field observations. Field observations have historically used a variation of license plate matching. The proposed technique assesses route choice and travel time that uses an anonymous Bluetooth media access control (MAC) address sampling technique as a surrogate for license plate matching to assess route choice. The Bluetooth sampling technique was used to evaluate the impact of an unexpected bridge closure in northwest Indiana, including an assessment of the proportion of vehicles using each of four alternate routes. The Bluetooth technology also provided a means to collect travel time data for each alternate route; these observed travel times were also compared with travel time estimates obtained by route classification and link distance. In general, the route choice behavior was consistent with observed travel time estimates. The Bluetooth sampling technique is cost-effective to deploy, and although results are approximate, direct measurement of travel times and route choice is useful for public agencies to assess mobility and travel time reliability along alternate routes.

An accessibility measure for the combined travel demand model

The accessibility-oriented transport planning method is critical for many high population density cities in China. Most definitions of accessibility only consider spatial separation and ignore the influence of traveler choice on accessibility. In this paper, the combined travel demand model is employed in transport planning. The travelers’ choice behavior of the model is based on the random utility theory. The model overcomes inconsistence problem of the sequential four-step model on travel behavior and congestion effects. Based on the same random utility theory, an accessibility measure is proposed, which can be integrated into the combined travel demand model. The accessibility measure can reflect the traveler’s choices at different stages (travel choice, destination choice, mode choice and route choice). The properties of the accessibility measure are discussed through a numerical example.

Urban Travel Route and Activity Choice Survey

This paper presents the results of an Internet-based prompted-recall activity travel survey using Global Positioning System (GPS) data collection combined with a short activity preplanning and scheduling survey. In addition to collecting traditional activity travel diary data, this survey collects basic information about activity planning and scheduling processes. Because aging is a growing concern among transportation planners, this survey has a special focus on the elderly population with about half of the survey sample consisting of elderly households. Respondents carried a portable GPS device for 14 consecutive days and at the end of each day uploaded the collected data to a website where the activity travel survey questionnaires were answered. Results indicate that the quality of the data collected is superior to other survey approaches and that the response rates are satisfactory considering the time commitment involved in participation. The results reinforce previous findings that GPS surveys have an improved ability to capture trips that are frequently underreported and provide valuable data about the activity planning and scheduling process itself. Respondents' feedback on their participation experience and fatigue and conditioning analysis reveal that this type of survey has great potential for data collections that last longer than 2 weeks.

Residential Self‐Selection and Appropriate Control Variables in Land Use: Travel Studies

Several researchers within the field of land use and travel have claimed that self‐selection of residents into geographical locations matching their travelling preferences precludes researchers from drawing firm conclusions about influences of residential location on travel. This paper counters this position. For one thing, if households self‐select into areas that meet their travel preferences, it seems self‐evident that urban structure matters. Evidence from qualitative interviews in the metropolitan areas of Copenhagen and Hangzhou indicates that most of the interviewees’ rationales for activity participation, location of activities, choice of travel mode and route choice contribute to a higher amount of motorized travel among outer‐area residents than among inner‐city dwellers, regardless of any self‐selection of residents to particular types of neighbourhoods. Drawing on data from Copenhagen Metropolitan Area, the paper shows that significant relationships between residential location and travel exist regardless of travel‐related residential preferences. Moreover, car ownership, and to some extent also transport attitudes, is influenced by residential location. Studies treating car ownership and attitudes to car travel as exogenous control variables not influenced by urban structure tend to underestimate the impacts of residential location on travel.

AN INTEGRATED MODELING FRAMEWORK FOR ENVIRONMENTALLY EFFICIENT CAR OWNERSHIP AND TRIP BALANCE

Urban transport emissions generated by automobile trips are greatly responsible for atmospheric pollution in both developed and developing countries. To match the long-term target of sustainable development, it seems to be important to specify the feasible level of car ownership and travel demand from environmental considerations. This research intends to propose an integrated modeling framework for optimal construction of a comprehensive transportation system by taking into consideration environmental constraints. The modeling system is actually a combination of multiple essential models and illustrated by using a bi-level programming approach. In the upper level, the maximization of both total car ownership and total number of trips by private and public travel modes is set as the objective function and as the constraints, the total emission levels at all the zones are set to not exceed the relating environmental capacities. Maximizing the total trips by private and public travel modes allows policy makers to take into account trip balance to meet both the mobility levels required by travelers and the environmentally friendly transportation system goals. The lower level problem is a combined trip distribution and assignment model incorporating traveler's route choice behavior. A logit-type aggregate modal split model is established to connect the two level problems. In terms of the solution method for the integrated model, a genetic algorithm is applied. A case study is conducted using road network data and person-trip (PT) data collected in Dalian city, China. The analysis results showed that the amount of environmentally efficient car ownership and number of trips by different travel modes could be obtained simultaneously when considering the zonal control of environmental capacity within the framework of the proposed integrated model. The observed car ownership in zones could be increased or decreased towards the macroscopic optimization objective with zonal limit of emissions.

Reliability of Travel Time

The reliability of the travel time on a route is widely regarded as one of the dominant factors affecting the route and departure time choices of travelers. There is still a lack of consensus on the quantitative measures that best reflect travel time reliability. This paper addresses this question from a traveler's point of view. It was concluded from a large stated preference-revealed preference route choice experiment that a measure of the asymmetry of a travel time distribution (λskew) was an important reliability measure. Put simply, people prefer a route that is usually fast but sometimes quite costly over a route that can have any travel time over a long range. In terms of reliability there is a discrepancy between user-optimal choices and system-optimal choices, because the recent literature reveals that skewed travel time distributions may yield much higher (collective) costs than symmetric distributions. Although the results indicate that the degree of skew in the travel time distribution of a route largely affects travel choices, it is strongly argued that there is no one best measure, because what can be regarded as “best” is contingent on the goal that must be reached. In line with this view, it was found in more detailed analyses that travel information and travel purpose influenced travelers’ route choices. Further research should focus on elaborating the contingency view and on working with more individual-based reliability measures for route choice situations.

Drivers’ Preferences for Traffic Information for Nonrecurrent Traffic Situations

The field of advanced traveler information systems (ATIS) has seen many improvements in the past years. These systems are developed to allow drivers or travelers to make better travel choices about travel time reduction or route choice. If such a system is to be generally accepted by drivers, it is necessary to know drivers’ preferences for traffic information content, as well as the characteristics of the information the system provides. These preferences should be known for all types of drivers and for all kinds of situations. This paper presents results of a study of these preferences. Although several studies have addressed the subject, little is known about preferences in nonrecurrent traffic situations. By means of an Internet survey, Dutch drivers were asked for their preferences concerning the content of traffic information for different nonrecurrent traffic situations. Statistical testing shows that drivers’ preferences differ according to the situation. Important driver characteristics influencing these preferences are current use of the information, driver type, and driver age. Drivers were also asked to choose between different information types, with different characteristics for a generic situation. Results were analyzed with a multinomial logit model. The most important characteristic of the information was cost; however, reliability and timeliness also contributed significantly to the utility of traffic information. Findings indicate that ATIS should be strongly adaptive to the driver and to the traffic situations at hand.

11.3.2 Development of an Object‐Oriented Multi‐Leg Route Choice Model on Transportation Network Simulation

Due to its complexity, modeling of the transportation network involves a very large number of node choices for completion of a travel route. Conventional route choice models approach this problem from the mathematical point of view. In this paper, a System‐of‐Systems approach is used to model a Personal Air Vehicle (PAV) network, and a traveler's route choice model in a multi‐leg travel scenario is proposed. Both the network and route choice model are designed using Object‐Oriented (OO) programming techniques eliminating the usage of complicated matrix calculations as in many other mathematical models. The practical limitations of the shortest path problem are not usually in the solution itself, but in the application of it in the simulation environment. This paper also covers some of the most important concepts of the Traveling Salesman Problem (TSP) and an idea to tackle TSP is suggested with a modified model.

Congestion pricing on a road network: A study using the dynamic equilibrium simulator METROPOLIS

The gradually accelerating pace at which tolls are being implemented or actively considered around the world suggests that road pricing is an idea whose time may finally have come. Nevertheless, various design considerations must be addressed and public acceptability hurdles overcome if road pricing is to become widespread. And to measure the efficiency gains and welfare-distributional effects of road pricing accurately, models need to account for potential behavioural responses to tolls—and in particular adjustments in trip timing. This paper analyzes some road pricing schemes using the dynamic network simulator METROPOLIS: a tool that treats endogenously departure-time decisions as well as mode and route choices of individual travelers. Simulations are conducted for a stylized urban road network that consists of radial arterials and circumferential ring roads, and with trip origins and destinations that are distributed throughout the network. Six types of link-tolling schemes are analyzed: (1) the system optimum which can be supported approximately by imposing time-varying step tolls that eliminate queuing, (2) a set of comprehensive flat (time-independent) tolls, (3,4) second-best flat and step tolls for a toll cordon, and (5,6) second-best flat and step tolls within a charge area. Two results show the superiority of step tolls over flat tolls. First, step tolls easily outperform flat tolls in terms of welfare gains while inducing a smaller shift of trips from auto to transit. Second, step tolls generate smaller revenues than do flat tolls, and consequently have more favourable distributional impacts on travelers.

Road Pricing with Autonomous Links

This research seeks to examine road pricing on a network of autonomous highway links. “Autonomous” refers to the links’ being competitive and independent and having the objective of maximizing their own profits without regard for either social welfare or the profits of other links. The principal goal of this research is to understand the implications of the adoption of road pricing and privatization on social welfare and the distribution of gains and losses. The specific pricing strategies of autonomous links are evaluated first under the condition of competition for simple networks. An agent-based modeling system is then developed; it integrates an equilibrated travel demand, route choice, and travel time model with a repeated game of autonomous links setting prices to maximize profit. The levels of profit, welfare consequences, and potential cooperative arrangements undertaken by autonomous links are evaluated. By studying how such an economic system may behave under various circumstances, the effectiveness of road pricing and road privatization as public policy can be assessed.

Evaluating the Ability of Global Positioning System Receivers to Measure a Real-World Operating Mode for Emissions Research

This paper evaluates the ability of Global Positioning System (GPS) receivers to determine accurately the second-by-second operating mode of a vehicle in the real-world transportation network. GPS offers the ability to obtain second-by-second velocity directly and to obtain acceleration data indirectly from a vehicle traveling in the real-world traffic network. Although GPS has been used successfully in travel behavior and route choice surveys, the uncertainty in accuracy of velocity and acceleration data obtained from the GPS warrants further investigation to gain a better understanding of the range and spatial distribution of vehicle emissions. In this study, data from two GPS receivers and a ScanTool were collected over five repetitions of a 65-mi route. The results indicate that GPS receivers perform as well as the ScanTool when measuring velocity. Furthermore, the GPS receivers determined the 1-s operating mode of the vehicle successfully when measured against the ScanTool. These results will aid in the future development of vehicle emissions models and allow for an analysis of real-world emissions based on real-world operating mode data.

Evaluating the Ability of Global Positioning System Receivers to Measure a Real-World Operating Mode for Emissions Research

This paper evaluates the ability of Global Positioning System (GPS) receivers to determine accurately the second-by-second operating mode of a vehicle in the real-world transportation network. GPS offers the ability to obtain second-by-second velocity directly and to obtain acceleration data indirectly from a vehicle traveling in the real-world traffic network. Although GPS has been used successfully in travel behavior and route choice surveys, the uncertainty in accuracy of velocity and acceleration data obtained from the GPS warrants further investigation to gain a better understanding of the range and spatial distribution of vehicle emissions. In this study, data from two GPS receivers and a ScanTool were collected over five repetitions of a 65-mi route. The results indicate that GPS receivers perform as well as the ScanTool when measuring velocity. Furthermore, the GPS receivers determined the 1-s operating mode of the vehicle successfully when measured against the ScanTool. These results will aid in the future development of vehicle emissions models and allow for an analysis of real-world emissions based on real-world operating mode data.

Road Pricing with Autonomous Links

This research seeks to examine road pricing on a network of autonomous highway links. Autonomous refers to the links' being competitive and independent and having the objective of maximizing their own profits without regard for either social welfare or the profits of other links. The principal goal of this research is to understand the implications of the adoption of road pricing and privatization on social welfare and the distribution of gains and losses. The specific pricing strategies of autonomous links are evaluated first under the condition of competition for simple networks. An agent-based modeling system is then developed; it integrates an equilibrated travel demand, route choice, and travel time model with a repeated game of autonomous links setting prices to maximize profit. The levels of profit, welfare consequences, and potential cooperative arrangements undertaken by autonomous links are evaluated. By studying how such an economic system may behave under various circumstances, the effective...

Uncovering the contribution of travel time reliability to dynamic route choice using real-time loop data

Travel time reliability has generally been surmised to be an important attribute of transportation systems. In this paper, we study the contribution of travel time reliability in travelers' route choice decisions. Traveler's route choice is formulated as a mixed-logit model, with the coefficients in the model representing individual traveler's preferences or tastes towards travel time, reliability and cost. Unlike the traditional approach involving the use of traveler surveys to estimate model coefficients and thereby uncover the contribution of travel time reliability, we instead apply the methodology to real-time loop detector data, and use genetic algorithm to identify the parameter set that results in the best match between the aggregated results from traveler's route choice model and the observed time-dependent traffic volume data from loop detectors. Based on freeway loop data from California State Route 91, we find that the estimated median value of travel-time reliability is significantly higher than that of travel-time, and that the estimated median value of degree of risk aversion indicates that travelers value a reduction in travel time variability more highly than a corresponding reduction in the travel time for that journey. Moreover, travelers' attitudes towards congestion are not homogeneous; substantial heterogeneity exists in travelers' preference of travel time and reliability. Our results validate results from previous studies involving the California State Route 91 value-pricing project that were based on traditional traveler surveys and demonstrate the applicability of the approach in travelers' behavioral studies.

Formulation and Solution Algorithm for Fuzzy Dynamic Traffic Assignment Model

An issue that is always important in the development of traffic assignment models is how travelers' perceptions of travel time should be modeled. Because travelers rarely have perfect knowledge of the road network or of the travel conditions, they choose routes on the basis of their perceived travel times. Traditionally, travelers' perceived travel times are treated as random variables, leading to the stochastic traffic assignment problem. However, uncertain factors are also observed in the subjective recognition of travel times by travelers, and these can be illustrated as fuzzy variables. Therefore, a fuzzy dynamic traffic assignment model that takes into account the imprecision and the uncertainties in the route choice process is proposed. By modeling the expressions of perceived travel times as fuzzy variables, this model makes possible the description of a traveler's process of choosing a route that is more accurate and realistic than those from its deterministic or stochastic counter parts. The fuzzy perceived link travel time and fuzzy perceived path travel time are defined, and a fuzzy shortest path algorithm is used to find the group of fuzzy shortest paths and to assign traffic to each of them by using the so-called C-logit method. The results of the proposed model are also compared with those from the stochastic dynamic traffic assignment model, and it is demonstrated that the impact of advanced traveler information systems on the traveler's route choice process can be readily incorporated into the proposed model.

Combined activity/travel choice models : time-dependent and dynamic versions

To fully understand and predict travel demand and traffic flow, it is necessary to investigate what drives people to travel. The analysis should examine why, where and when various activities are engaged in, and how activity engagement is related to the spatial and institutional organization of an urban area. In view of this, two combined activity/travel choice models are presented in this paper. The first one is a time-dependent (quasi-dynamic) model for long-term transport planning such as travel demand forecasting, while the other one is a dynamic model for short-term traffic management such as instantaneous flow analysis. The time-dependent model is formulated as a mathematical programming problem for modeling the multinomial logit activity/destination choice and the user equilibrium route choice behavior. It can further be converted to a variational inequality problem. On the other hand, the dynamic model is aimed to find a solution for equilibrium activity location, travel route and departure time choices in queuing networks with multiple commuter classes. It is formulated as a discrete-time, finite-dimensional variational inequality and then converted to an equivalent “zero-extreme value” minimization problem. Solution algorithms are proposed for these two models and numerical example is presented for the latter. It is shown that the proposed modeling approaches, either based on time-dependent or dynamic traffic assignment principles, provide powerful tools to a wide variety of activity/travel choice problems in dynamic domain.

Estimation and Prediction of Time-Dependent Origin-Destination Flows with a Stochastic Mapping to Path Flows and Link Flows

This paper presents a new suite of models for the estimation and prediction of time-dependent Origin-Destination (O-D) matrices. The key contribution of the proposed approach is the explicit modeling and estimation of the dynamic mapping (the assignment matrix) between time-dependent O-D flows and link volumes. The assignment matrix depends upon underlying travel times and route choice fractions in the network. Since the travel times and route choice fractions are not known with certainty, the assignment matrix is prone to error. The proposed approach provides a systematic way of modeling this uncertainty to address both the offline and real-time versions of the O-D estimation/prediction problem. Preliminary empirical results indicate that generalized models with a stochastic assignment matrix could provide better results compared to conventional models with a fixed matrix.

A Basic Analysis of Drivers' Route Choice and Information Acquisition Behavior Based on Stated Preference Data Collected through Intranet Survey

A computer network-based survey was proposed as a method of collecting travel behavior data ondriver's information service utilization and route choice when traffic information is provided, and itseffectiveness was verified. We found that the survey method using the intranet is superior to the conventional questionnaire ones, because its survey time was shorter and the reality of the experimental situation was greatly improved. Furthermore, we analyzed the relation between information utilization behavior and variables consisting of driver's awareness level of congestion and characteristics of information services. As results, we found that the reduction in vehicle speed is likely to increase driver's access to the information services.

Formulation, Stability, and Computation of Traffic Network Equilibria as Projected Dynamical Systems

In this paper, we present a unified treatment and analysis of a dynamic traffic network model with elastic demands formulated and studied as a projected dynamical system. We propose a travel route choice adjustment process that satisfies the projected dynamical system. Under certain conditions, stability and asymptotical stability of the equilibrium patterns are then derived. Finally, two discrete-time algorithms, the Euler method and the Heun method, are proposed for the computation of the solutions, and convergence results established. The convergence results depend crucially on stability analysis. The performance of the algorithms is then illustrated on several transportation networks.