Travel Time Budget Research Articles

The k-th order mean-deviation model for route choice under uncertainty

This study introduces the k-th order mean-deviation model for optimizing route choice within large, stochastic, and time-variant networks. This model addresses the limitations of the traditional mean-standard deviation approach by better handling extreme outcomes in travel times. It features an objective function called the “travel time budget”, which combines the average path travel time with a safety margin. This margin is defined by a trade-off coefficient and a selected deviation measure (total or semi) of the travel time. The model is divided into three variations: 1) The mean-total deviation (MTD) model for symmetric travel time distributions, 2) The mean-upper-semi-deviation (MUSD) model for asymmetric distributions prioritizing upper semi-deviations, suitable for risk-averse travelers, and 3) The mean-lower-semi-deviation (MLSD) model for asymmetric distributions focusing on lower semi-deviations, preferred by risk-prone individuals. We explore these models’ alignment with the stochastic dominance (SD) rule and develop a solution methodology based on SD principles. Numerical experiments in two real-world transportation networks demonstrate the models’ effectiveness and show how the choice of deviation affects route selection decisions.

Impact of autonomous vehicles on discretionary activities: an agent-based model with space–time accessibility constraints

AbstractThe extensive development of autonomous vehicles (AVs) is set to revolutionise the way of travelling. Research suggests that the introduction of AVs may affect travel behaviour and choices, resulting in long-term changes in land use. Accessibility is an important concept that connects transportation and land use, providing a holistic performance measure for the transport-land use system. However, this concept has not been adequately capitalised in studies that attempt to understand the impact of AVs on location choice decisions. To explore this knowledge gap, we proposed an agent-based simulation framework that integrates with accessibility constraints to study how AVs influence behavioural and location choices. The framework consists of an activity-based travel demand model with accessibility constraints and a dynamic transport assignment model. The accessibility constraints are derived from individuals’ travel time budgets based on activity-travel survey data. We applied the agent-based simulation framework to Clayton, Australia, and focused on discretionary activity location choices. Various values of travel time and vehicle running costs underpinned by the use of AVs were examined. While most studies have concluded that AVs can significantly increase trip lengths for daily activities, our results demonstrate that even when AVs are used, the movement of individuals is still limited by spatio-temporal constraints of accessibility. As a result, we predict that the increase in discretionary trip lengths and their impact on traffic congestion is modest.

The importance of recurring public transport delays for accessibility and mode choice

This paper looks at the relationship between recurring public transport delays, accessibility to jobs, and travel behaviour in the region of Scania, Sweden. The difference between potential (scheduled) accessibility, observed (actual) accessibility, and behaviour is an important part of this research. This paper contributes to the growing body of literature that uses GTFS data (for both scheduled and actual services) to provide a deeper understanding of temporal variations in accessibility with public transport. Historic public transport data were used to develop a measure for typical delays in the region. The accessibility analysis shows that, on average, recurring public transport delays result in a 4–9% reduction in accessibility to jobs in the region. The loss in accessibility varied depending on the travel time budget that was considered and the location within the region. The accessibility analysis also shows that areas with higher concentrations of households with a lower economic standard experience a smaller loss in job accessibility caused by public transport delays. However, the concentration of these effects depends on the measure that is used. The measurement of typical delays was also analysed in relation to actual trips from the regional travel survey. The statistical analysis found that recurring public transport delays were associated with a lower likelihood of using public transport compared to other motorised modes.

Is car traffic close to saturation in France?

After decades of uninterrupted growth, car traffic temporarily levelled off during the 2000′s in France, before coming back to growth after 2008. However, there are reasons to believe that car traffic growth is potentially limited, among which completion of the diffusion process for car ownership, limited travel time budgets, decreasing returns of additional car travel. In this study, we implement a disaggregate model at the household level to project future car ownership and car mileage per household in France, along with total car traffic, accounting for demographic growth. Our model relies on a sequential approach using panel data, with an ordered response probit model for the number of vehicles, including saturation thresholds by vehicle rank, and a log-linear model for car mileage, conditional on the number of vehicles, both with correlated random effects. A time trend is also incorporated to account for the decreasing household car mileage that was noticed over the last twenty years, which is not entirely explained by decreasing household size and the gradual decline of income growth. Assuming this trend to go on, total car traffic in France would grow only a little by 2050, despite demographic growth, and start decreasing from 2040. We discuss these results by questioning the structural nature of this trend.

Decomposition of travel time expenditure through individual mobility trajectories based on mobile phone signaling data

The concept of travel time expenditure (TTE) or travel time budget (TTB) was developed approximately 60 years ago, and its stability issues have long been debated based on traditional household travel survey (HHTS) methods or less developed information and communication technologies (ICTs). Recent advances in mobile phone technologies have enabled the use of individuals’ mobility information at the disaggregation level. The objective of this study is to explore the TTE based on mobile phone signaling data (MPSD) collected from the residents in two different types of districts in South Korea. The results may produce better spatiotemporal precision than traditional household survey data because MPSD is generated when a mobile phone changes the cell coverage area and base transceiver stations (BTSs) or whenever the recording time interval set by the cellular service provider arrives. On the other hand, tremendous effort is needed to collect and clean up the raw data compared to data obtained using the conventional HHTS method. This paper presents data-cleaning processes and the results of a TTE calculation as a function of the day of weekday, age group, and region type. The processes and results of this study could be useful for modeling human mobility behavior using MPSD.

Passenger Transport Modal Mix by Incorporating Travel Behaviour: A Case Study of Kathmandu Valley, Nepal

Most of the travel demand in developing countries is fulfilled by private vehicles dominated by 2-wheelers due to their affordability, accessibility, and availability, which has direct effects on energy, economy, and environment. To achieve sustainable transport, policies such as electric mobility and mass transport options have been implemented which are mainly focused on technology shift based on technology cost and environmental externalities. Transport modelling in this study was carried out using an additional attribute: travel time which shows the impact of travel behaviour on the optimal modal mix and the consequent impact on energy and emissions. The scenario-based approach using the travel time budget (TTB) concept was used using a bottom-up TIMES modelling framework. The scenario analysis shows the trade-off between the speed of the vehicle, available travel time, and sustainability in transport. The result suggests that the investment in rapid transit would be the potential future mode in Kathmandu valley.

Bi-objective reliable eco-routing considering uncertainties of travel time and fuel consumption

Eco-routing aims to provide fuel-efficient paths to help travellers make route choice decisions in the road network. Most eco-routing algorithms build on a deterministic assumption about link fuel consumption. However, link fuel consumption in real road networks is highly stochastic caused by travel speed variations. This study investigates the eco-routing problem by explicitly considering uncertainties of travel time and fuel consumption. A stochastic fuel consumption formula to estimate fuel consumption distributions caused by travel speed variations is proposed. A bi-objective reliable eco-routing model is developed by minimizing the travel time budget and fuel consumption budget simultaneously while satisfying given constraints on travel time reliability and fuel consumption reliability. An efficient reliable path ranking algorithm is developed to solve the formulated model exactly. A comprehensive case study using real data from Hong Kong is presented to demonstrate the applicability of the proposed model and algorithm.

Transport vulnerability: Measuring travel time and expenditure budget in Addis Ababa

Public transport is critical for urban dwellers as it is a key link to access economic opportunities and social services. However, transit services in most developing nations are characterized by longer journey time, high fare, unsafe and uncomfortable travel. Hence, this study seeks to analyze the travel experience of public transit users through the lens of vulnerability. The main objective of the research is to investigate transit users’ expenditure on travel, both in terms of time and money, which are regarded as “budgets” allocated to travel. The analysis is based on a survey distributed to 457 public transit users in Addis Ababa. The study applied proportions, percentages and cross-tabulation of key variables and statistical methods, such as one-way ANOVA to analyze the level of vulnerability of transit users. The result shows that low- and middle-income groups bear a higher level of travel burden, in terms of total travel time and percentage of income spent on transport than high income groups. Transport expenditure accounted above 20% of household income for 88% of low-income groups. However, it is below 15% of household income for high income groups, which reveals less financial burden on them. In terms of travel time, 63.8% of middle income groups experience a total travel time of more than 2 h and 52.3% of low-income groups but only 36.3% of high-income groups devote a total travel time above 2 h. Therefore, transport policy formulation should consider the needs and challenges of various groups of transit users.

Research on the Optimization Model of Railway Emergency Rescue Network Considering Space-Time Accessibility

The capability of railway emergency rescue can be enhanced by maintaining the railway emergency rescue network and upgrading its technology. Nowadays, influenced by the factors, such as resource type, personnel distribution, line level, etc., space-time differences may be unavoidable. In the meantime, the general description method of the transportation network may lack the consideration of the rescue transportation particularity, so the strategies of resource allocation, maintenance, and upgrading could be illogical. Hence, in this paper, the gravity model is utilized to improve the classical travel time budget model and to construct the space-time accessibility model, firstly. Then, further exploring the space-time accessibility of nodes and edges of railway emergency rescue network and considering the randomness of travel time, a space-time accessibility measurement method for an emergency network is proposed. Moreover, a global optimization model with accessibility characteristics is then constructed for the maintenance allocation of the emergency rescue transportation network. The results show that the proposed method can solve the maintenance allocation problem of the large-scale rescue network effectively, reduce the risk of maintenance allocation strategy failure caused by unreasonable node index parameters, and provide an effective basis and theoretical support for the rational formulation of railway rescue transportation network maintenance allocation strategy.

Les arbitrages individuels en matière de temps de transport

In the context of a global health crisis, digital tools play a growing role in daily lives of students and working people. Many people now work from home and study online. Do these virtual exchanges replace spatial mobility? To answer this question in this article, we focus on individual trade-offs in terms of travel choices and, more specifically, in terms of travel time. Based on the work of Y. Zahavi and the hypothesis he made of the stability of time budgets on a daily scale, we question the relevance of an extension of the thinking to the weekly stability of these time budgets (with and without the weekend) and also to the stability of the perceived time budgets. Our challenge in this article is to better understand individual choice logics to ensure more efficient political measures. English title: Individual trade-offs in travel time budgets. Knowledges and practices in Switzerland

Co-evolution of the built environment and travel behaviour in Shenzhen, China

The impact of the built environment on travel behaviour may change over time especially over the course of urban expansion. There is a long-time debate on the existence of a constant time budget that people are willing to spend on daily travel. This study collects data from Shenzhen’s periodical travel surveys spanning two decades and examines the trends in travel distance and travel time as well as the changing impacts of the built environment on travel behaviour. We find that travel distance increases significantly over the study period, but travel time grows at a much lower pace and reaches stable level at the late stage. The travel behaviour impacts of the built environment also change over time in terms of directions and magnitudes. Findings of this study enrich the literature on the built environment-travel behaviour connection with a dynamic perspective and provide evidence supporting the constant travel time budget hypothesis.

Measuring joint space-time accessibility in transit network under travel time uncertainty

In densely populated areas, joint activity participation such as shopping and eating outside represents a substantial portion of individuals' daily activity-travel patterns. Individuals have several considerations in making joint activity choice behaviour such as space-time coordination, activity start time, activity location and joint activity duration. In a congested transit network, the travel time uncertainty significantly affects individuals' activity and travel choice behaviour. To conduct some important joint activities, individuals normally have high expectations of on-time arrival. Thus, the measurement of space-time accessibility in transportation networks should be extended to consider joint activity choices and travel time uncertainty. In this paper, a new method for measuring space-time accessibility is proposed for individuals' joint activities in transit network with consideration of travel time uncertainty. A reliable alighting location model is proposed to identify all feasible alighting locations in transit network to perform joint activities by explicitly considering constraints of on-time arrival probabilities. Individuals’ joint space-time accessibility (JSTA) is measured based on reliable alighting locations, travel time budget, and points of interests. Massive smart card data from metro network in Nanjing, China are used to show the merits of the proposed JSTA measure. The results show that there is a significant difference between the space-time accessibility to independent activity and that to joint activity under various on-time arrival probabilities. The effects of spatial (de)concentration of anchor locations and minimum joint activity duration on JSTA, and the role of additional participants are also presented in various scenarios. The proposed JSTA measure can be used to help policy makers to evaluate transit network development and land use planning in urban areas.

Mapping multimodal random accessibility using smart card data: a case study of bus and subway stations in Beijing

ABSTRACT Research on multimodal accessibility under uncertain travel time has become a significant issue. Existing studies on accessibility lack a direct integration of multi-source data accessibility evaluation methods. This paper develops a multimodal random accessibility model (MR model). Multi-source data is integrated with a built-in joint calculation method of walking time, waiting time, and transit time while considering the effects of both the travel time budget in the time dimension and distance friction parameter in the spatial dimension. Taking Beijing as an example, accessibility generally shows a downward trend from the center of the city to the suburbs, especially along the subway lines, and there is a positive correlation between traffic flow and accessibility. The low-accessible high-flow area is mainly distributed in areas away from the city center and at the end of subway lines. These results could help transport planners formulate more reasonable public transport planning policies.

Passenger Transport Modal Mix by Incorporating Travel Behaviour: A Case Study of Kathmandu Valley, Nepal

Most of the travel demand in developing countries is fulfilled by private vehicles dominated by 2-wheelers due to their affordability, accessibility, and availability, which has direct effects on energy, economy, and environment. To achieve sustainable transport, policies such as electric mobility and mass transport options have been implemented which are mainly focused on technology shift based on technology cost and environmental externalities. Transport modelling in this study was carried out using an additional attribute: travel time which shows the impact of travel behaviour on the optimal modal mix and the consequent impact on energy and emissions. The scenario-based approach using the travel time budget (TTB) concept was used using a bottom-up TIMES modelling framework. The scenario analysis shows the trade-off between the speed of the vehicle, available travel time, and sustainability in transport. The result suggests that the investment in rapid transit would be the potential future mode in Kathmandu valley.

Reliability in public transit networks considering backup itineraries

Itinerary planning serves an important purpose for travelers navigating through a public transit network. The uncertainty of travel times within the network must be considered since this uncertainty can lead to delays or missed transfers. If an initial transit service or a transfer between services is missed, then the traveler must have a contingency plan for reaching their destination. However, finding reliable itineraries with contingency plans is computationally challenging. This paper outlines an a priori policy that maximizes the reliability, i.e. the probability of reaching the destination within a travel time budget, while considering the most reliable primary itinerary and backup itineraries in case a transfer is missed.We develop a network search algorithm that finds the most reliable itinerary with backups, which accurately accounts for the uncertainty of travel times and frequency of alternative options in the recommendation. We compare our approach to state-of-the-art contingency research, Dynamic Journeying Under Uncertainty by Häme and Hakula (2013), and show that it more accurately calculates the reliability, is more intuitive to the traveler, and has a faster runtime. Additionally, we highlight the differences in reliability across times of day, travel time budgets, and city regions for a real-world transit network in Göttingen, Germany. This approach offers travelers an easy-to-understand tool for planning reliable public transit travel itineraries.

Adaptive drift and barrier-avoidance by a fly-forage migrant along a climate-driven flyway

BackgroundRoute choice and travel performance of fly-forage migrants are partly driven by large-scale habitat availability, but it remains unclear to what extent wind support through large-scale wind regimes moulds their migratory behaviour. We aimed to determine to what extent a trans-equatorial fly-forage migrant engages in adaptive drift through distinct wind regimes and biomes across Africa. The Inter-tropical Front (ITF) marks a strong and seasonally shifting climatic boundary at the thermal equator, and we assessed whether migratory detours were associated with this climatic feature. Furthermore, we sought to disentangle the influence of wind and biome on daily, regional and seasonal travel performance.MethodsWe GPS-tracked 19 adult Eleonora’s falcons Falco eleonorae from the westernmost population on the Canary Islands across 39 autumn and 36 spring migrations to and from Madagascar. Tracks were annotated with wind data to assess the falcons’ orientation behaviour and the wind support they achieved in each season and distinct biomes. We further tested whether falcon routes across the Sahel were correlated with the ITF position, and how realized wind support and biome affect daily travel times, distances and speeds.ResultsChanges in orientation behaviour across Africa’s biomes were associated with changes in prevailing wind fields. Falcons realized higher wind support along their detours than was available along the shortest possible route by drifting through adverse autumn wind fields, but compromised wind support while detouring through supportive spring wind fields. Movements across the Sahel-Sudan zone were strongly associated to the ITF position in autumn, but were more individually variable in spring. Realized wind support was an important driver of daily travel speeds and distances, in conjunction with regional wind-independent variation in daily travel time budgets.ConclusionsAlthough daily travel time budgets of falcons vary independently from wind, their daily travel performance is strongly affected by orientation-dependent wind support. Falcons thereby tend to drift to minimize or avoid headwinds through opposing wind fields and over ecological barriers, while compensating through weak or supportive wind fields and over hospitable biomes. The ITF may offer a climatic leading line to fly-forage migrants in terms of both flight and foraging conditions.

A bi-objective reliable path-finding algorithm for battery electric vehicle routing

This paper proposes a bi-objective reliable path-finding algorithm for routing battery electric vehicles on a road network, with vehicles’ energy consumption uncertainty and travel time uncertainty. A bi-objective stochastic optimization problem is proposed and formulated to simultaneously maximize energy consumption reliability (ECR) and travel time reliability (TTR). ECR is defined as the probability of finishing a trip without exhausting a given battery energy budget, while TTR is the on-time arrival probability with the travel time budget. In this study, the proposed optimization problem is decomposed into two sub-problems: (1) finding K most reliable paths for maximizing the TTR objective and (2) finding the most reliable path for optimizing the ECR objective. Then, a novel ranking algorithm is proposed to exactly solve the formulated optimization problem. A case study is carried out on Hong Kong’s road network to demonstrate the efficacy and efficiency of the proposed algorithm for real-world applications.

Understanding non-commuting travel demand of car commuters – Insights from ANPR trip chain data in Cambridge

Abstract The paper investigates the non-commuting travel demand of car commuters using Automatic Number Plate Recognition (ANPR) trip chain data in Cambridge, UK. A novel rule-based algorithm is developed for identifying commuting vehicles and the associated non-commuting trips. Identification results are validated with external data. Non-commuting travel demand is investigated in terms of trip probability, average trip frequency, duration and demand elasticity. The study finds that, first, non-commuting trips represent a significant source of travel demand for car commuters – car commuters who engage in non-commuting activities in their daily trip chains would on average spend approximately 2.7hr on those activities including travel time on a typical workday in Cambridge. Second, longer working hours are associated with a lower probability of engaging in non-commuting trips, implying a substitution effect within the daily travel time budget. Last, in terms of travel demand elasticity, non-commuting trips starting in the early morning (6–9am) are less elastic than those starting in the morning (9–12am) and during the lunch break (12-3pm). The varying demand elasticities are likely to be attributed to the different travel constraints associated with certain trip purposes. Implications for post-pandemic traffic demand and management are drawn.

Transit Accessibility Measurement Considering Behavioral Adaptations to Reliability

Accessibility measures are necessary for evaluating the benefits of proposed transportation improvements. However, they often do not account for travel time unreliability, but instead incorporate deterministic and time-invariant travel times. This approach risks mischaracterizing the accessibility experienced by travelers. In this paper, we review recent literature on accessibility and travel time reliability with a focus on transit and introduce an approach to joint accessibility-reliability measurement that relies on a behavioral perspective. Using this behavioral perspective, we propose that existing accessibility measures be implemented using travelers’ total travel time budget as a measure of travel time, and that varying departure time strategies depending on service characteristics be considered. The total travel time budget can reasonably be quantified with a high percentile of the total travel time distribution. However, we note that different percentiles may be more appropriate for different traveler types, as these percentiles correspond to varying tolerances for late arrivals. This behavioral perspective can be operationalized with commonly used accessibility measures, such as the cumulative opportunity measure, and with real-time vehicle location data. We include a demonstration of the potential changes in accessibility estimates when accounting for travel time unreliability, with a simplified case study of a transit route in San Francisco. The results show a considerable reduction of the number of opportunities available to travelers when the calculation is based on the latter—between 5.9% and 37.9% less, depending on various factors. Such differences have the potential to significantly affect the accessibility benefits of transit capital investments.

A conceptual framework and implementation tool for land use planning for corridor transit oriented development

Transit-oriented development (TOD) has gained worldwide popularity because of its potential to help communities achieve sustainability goals. The current practice of TODs has largely focused on individual transit station sites or TOD nodes, not fully capturing the corridor advantages associated with transit systems. This study develops a conceptual framework and an implementation tool for planning corridor TOD (C-TOD). C-TOD expands the conventional nodal TOD concept and practice to 1) capture corridor level interactions between individual TOD nodes, and 2) incorporate economic, social, and environmental indicators with the physical planner/design attributes for modeling and evaluating C-TOD plans. Conceptually, the study defines C-TOD spatially as individuals' travel shed within a travel time budget of 55–65 min along the transit service segment of 15–20 miles (stations). Operationally, the C-TOD tool measures TOD site attributes with 5D variables (Density, Diversity, Design, Distance to Transit, and Destination Accessibility) and quantifies three sustainability indicators in the C-TOD context with transit premiums, total accessibility to services and housing opportunities, and building and household travel emissions. To implement the multi-objective C-TOD tool, the study applies genetic algorithms to search, assess, and identify optimal C-TOD alternatives under user-specified planning and policy targets and constraints. A case study of Metro Line #2 in Wuhan, China, is presented to illustrate the C-TOD framework and optimization tool. As mass rapid transit systems continue to expand around the world, the C-TOD concept and tool introduced in this study can help practitioners and policy makers to augment TOD applications with improved land use planning and decision-making.