Value Of Travel Time Research Articles

Exploring gaps in residential and parking location choice models for autonomous vehicles: a proposed evaluation framework

ABSTRACT The advent of autonomous vehicles (AVs) is poised to transform urban landscapes, notably by altering perceptions of travel time value, reshaping parking structures, and introducing additional travel demand through empty-cruising and self-parking capabilities. These changes are anticipated to influence both residential and parking location choices. This study delves into the complexities of these decisions by integrating insights from 28 modelling studies on residential and/or parking location choices in the context of AVs and by proposing an evaluation framework for future modelling efforts. A critical gap identified is the oversight of empty-cruising and parking costs in the context of residential relocation choice for owners of privately-owned AVs. Furthermore, no study has adopted a joint-choice modelling approach for residential and parking location choices. By offering guidelines for the incorporation of these elements, this study contributes to the development of a holistic residential and parking location choice model with AVs, thus providing a valuable roadmap for future research in urban planning and transportation economics.

Predicting temporal evacuation travel time in staircases between adjacent floors of super high-rise buildings by artificial neural networks

Predicting temporal evacuation travel time in staircases between adjacent floors is crucial for dynamic evacuation guidance to improve vertical evacuation efficiency during emergencies in super high-rise buildings. However, the prediction methods used in previous studies mainly focus on the total evacuation time in buildings and cannot predict the temporal evacuation travel time in every single part of the total evacuation route. This study proposes a novel method to predict temporal evacuation travel time in staircases between adjacent floors of super high-rise buildings by using artificial neural networks. Firstly, evacuation simulation data of a 71-storey office building are analyzed for feature engineering and dataset building. Secondly, three types of artificial neural networks, including convolutional neural networks, RNN-based model (the traditional recurrent neural networks, long-short term memory networks, and bidirectional long-short term memory networks), and Attention-based model (Attention model and Transformer model) are extended to predict the temporal evacuation travel time in staircases between adjacent floors based on the simulation data. Finally, the prediction results by different artificial neural networks are compared. The results show that the artificial neural networks can provide accurate prediction values for the temporal evacuation travel time in staircases between adjacent floors of super high-rise buildings.

Estimating the value of self‐drive recreation in the remote Kimberley: Sensitivity to multi‐destination trips

AbstractThe remote and iconic Kimberley region, in northern Western Australia, is a contested landscape with growing pressure for different types of land use and development. The region has high biodiversity values and impressive scenery that provide attractive recreation experiences for visitors. We estimate the value of domestic recreation to the region using a travel cost model. Analysis includes two approaches for accounting for multi‐destination trips (MDTs) given travel to remote sites are more likely to include these than shorter trips, and four specifications for the value of travel time. We estimate a total consumer surplus of A$110.34 million annually and find that adjusting travel costs for MDTs using stated survey information produces a better fitting model than using revealed travel information. These findings highlight both the importance of estimating recreation values for use in land use planning in the Kimberley and for improving the travel cost method for remote sites where per‐trip travel costs are high.

Too Far? Autonomous vehicles, travel demand, and carbon dioxide emissions in Sweden

This article envisions that by the middle of this century fully self-driving Autonomous Vehicles (AVs) are available for private use. By considering how AVs can affect the utility of being in the vehicle, and accounting for the utility of being able to transport oneself to and from various locations, we derive the consumer surplus of having an AV and evaluate that against the cost of adopting the technology. This break-even calculation is used to evaluate AV purchase and consequent impacts on increase in travel demand and lifecycle CO2 emissions for different income groups for different assumptions concerning the Value of Travel Time, transport demand elasticity, AV technology costs, interest rates, and the possibility to work in the car or not. The modelled results show that all income groups purchase AV given low technology cost, and the highest income groups purchase AV under most conditions. Changes in demand elasticity and the value of travel time have the largest effect on vehicle miles traveled, which could be as much as 50 additional kilometers daily per driver. Even in a scenario consistent with the Paris Agreement, this implies an annual carbon footprint of 0.42 – 0.86 metric tons of CO2 per driver from personal car travel in Sweden.

Who will board urban air taxis? An analysis of advanced air mobility demand and value of travel time for business, airport access, and regional tourism trips in Iran

Recent advancements in the development of a comprehensive urban air mobility ecosystem promise the opportunity for its implementation in the near future. However, the utility of this emerging mode of transportation in comparison to the existing modes varies for different trip purposes and geographical contexts. It is, therefore, imperative to assess its usage potential for various scenarios before moving forward with implementation efforts. This paper presents the findings of three stated preference surveys aimed at characterizing prospective urban air mobility travel demand for weekly business, airport access, and regional tourism trips in Iran. Hybrid multinomial logit and hybrid nested logit models are estimated for each trip purpose. The results indicate that urban air mobility for weekly business trips represents the most viable market segment. Value-of-time estimates for weekly business trips are more than two and a half times higher than those for airport access trips, and tourism trips are valued even less. There is a trend towards delaying the adoption of air taxis to gain trust, and reducing ticket prices is seen as the most effective incentive for increasing the adoption rate. This study pioneers research on urban air mobility in a developing country context, offering valuable insights into market viability for investors and policymakers.

Assessing the Impacts of Autonomous Vehicles on Urban Sprawl

Background: Urban sprawl adversely effects the sustainability of urban environments by promoting private vehicle use, decreasing the viability of active/public transport, and increasing the cost of public service provision. Autonomous vehicles could change the desirability of different residential locations due to resulting changes to urban design and decreased value of travel time. Methods: Adult Australians (n = 1078) completed an online survey that included a description of a future where autonomous vehicles are widely available. The respondents reported anticipated changes in residential location in this autonomous future. Frequency analyses were conducted, and three logistic generalised linear models were run to identify factors associated with staying in the same area or moving to higher- or lower-density locations. Results: Autonomous vehicles are likely to have mixed effects on people’s desired residential locations. Most respondents (84%) elected not to move location, 11% intended to move to lower-density locations, and 6% to higher density locations. Reasons for moving included a desire for more space, the ease of travelling in urban areas, and the reduced value of travel time. Conclusion: The introduction of autonomous vehicles will need to be managed to avoid fostering increased urban sprawl and the associated negative consequences. Strategies that increase the liveability of higher density urban environments are likely to discourage urban sprawl in a future characterised by autonomous transport options.

Analysis of Traffic Performance and Passenger Car Equivalent Value in Tangerang – Merak Toll Road Section

Economic growth involves massive movement of logistics, where goods transported by land become the main choice by supplier. One of them being the main access for connecting Java and Sumatera is the Tangerang – Merak toll road. An increase in traffic volume occurs every year, followed by additional problems such as congestion which obviously affects traffic performance. Given this reason, it is necessary to evaluate traffic performance through parameter assessments, which are the degree of saturation and travel speed. This research was carried out on the Tangerang - Merak toll road section KM 32,300 to KM 35,500 towards Jakarta for one week using traffic CCTV recordings, then selected on 17 April 2024. The calculation results obtained for each average weighted value for the degree of saturation (Ds) at 0.36 and average of the Space Mean Speed is at 33.08 kph. Based on traffic performance analysis, the volume parameter does not indicate a problem, and is included in the LOS A category. However, the travel speed parameter shows an issue and included in the LOS F category. This will be the focus problem within the scope of the research. On the other side, traffic composition which includes variations in the number of vehicles per time and type of vehicle. Given this kind of variation, a Passenger Car Unit value is needed that can equalize the existing different vehicle types into a uniform standard, including who commit over dimensional violations. Where the value of passenger car equivalent of an over-dimensional vehicle is changing, it is necessary to re-calibrate the emp value. Researchers used the Volume Delay Function formula to calculate travel time, then explore a combination of emp values using the dynamic programming method by comparing survey travel time with the simulation one. The difference between the PKJI standard value and the calibrated pce value proves the problem of these vehicles commit over dimension violations on the Tangerang – Merak toll road. For this reason, it is hoped that this research which evaluate traffic performance, travel time and passenger car equivalent values, can be used as a basis for further policy making to improve the performance of the Tangerang – Merak toll road.

Strategic integration of vertiport planning in multimodal transportation for urban air mobility: A case study in Beijing, China

In pursuit of strategic sustainable development goals, this study seeks to analyze the spatial placement of vertiports for urban air mobility, positioning them as integral components within the multimodal transportation system. We propose an iterative weighted k-means clustering method that incorporates the value of travel time of different transportation modes to identify potential vertiport locations. A multi-objective optimization model that maximizes total air taxi ridership and minimizes total facility costs and travel distances to vertiports is developed considering the constraints of the distance from vertiports to existing mobility hubs. A case study is conducted using the data of Beijing city, incorporating the modes of taxis and metro. We found that 19 vertiports can guarantee a robust performance of urban air mobility service. Users of urban air mobility can benefit from substantial travel time savings of 80% (48 min on average). This study contributes to a deeper understanding of the optimal setting of urban air mobility facilities from the perspective of network synchronization, offering useful insights into policy decision-making for sustainable infrastructure planning.

Analyzing the welfare economic of freight transport companies with disaggregated data for Brazilian states

Efficient use of transport systems can increase well-being and ensure benefits for society. Reducing the costs involved in transport operations can occur through management, investments, or using more efficient infrastructures. Well-being gains are weighted based on economic theory, particularly with the classical welfare function that measures consumer surplus gains. Therefore, this article aims to analyse the economic well-being of freight transport companies with disaggregated data for Brazilian states. Data from a stated preference survey were used for the entire Brazilian territory. We estimate logit models to determine the value of travel time, and a logsum measure was used to calculate differences in well-being for freight transport companies. The results show the heterogeneity of Brazilian shippers when choosing the mode of mode of transport for freight transport companies. Research deepens the investigations underway in Brazil, disaggregating the analysis at the state level and simulating different scenarios to describe well-being and the value of travel time. The results show significant differences in the choice of road modes compared to their competing modes by region in Brazil. The findings indicate that states may have greater marginal benefits in well-being with changes in transport costs, transport time, delivery reliability, and flexibility.

High-Profile Convoy Disruptions: Exploring Socioeconomic and Environmental Ramifications of Road Closures

Congestion persists despite various demand management techniques, particularly for handling recurrent congestion. However, non-recurrent congestion from events like VIP movements poses unique challenges, especially during peak hours. This study investigates the environmental and economic impacts of road blockages due to VIP movements in developing countries, focusing on Pakistan. Considering practiced standard operating procedures associated with VIP movements, this study finds significant delays and economic burdens in debt-ridden economies. It uses discrete choice modeling and microsimulation techniques to evaluate the value of travel time and quantifies road blockage effects on fuel consumption, travel time, and carbon emissions. Data from central blockage locations in Rawalpindi and Islamabad reveal a value of travel time estimated at 1.77 USD/h, with income and gender significantly influencing mode choices during VIP movements. Moreover, road blockages exceeding two minutes substantially negatively impact the environment and economy, particularly in developing nations. Urgent action is needed for effective mitigation strategies and sustainable transportation policies to address the detrimental effects and promote alternative transportation modes. Recommendations include limiting VIP blockages to a maximum of two minutes and implementing policies to discourage private car usage. Despite limitations, the study emphasizes the critical role of sustainable transportation policies in enhancing the well-being of road users in developing nations.

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 value(s) of travel time savings considering in-vehicle activities.

In this note I present a theoretical formulation that incorporates the main elements behind the performance of work or leisure activities while travelling, obtaining an expanded interpretation of the values of time in terms of the role played by the values of work and leisure inside the vehicle. We conclude that the value of in-vehicle time is expected to decrease as the conditions to perform those activities inside the vehicle improve. The framework admits the possibility of negative travel time values if there are leisure activities that can only be performed while traveling and are preferred over those that can be done elsewhere.

Relax on the way to work or work on the way to relax? Influences of vehicle interior on travel time perceptions in autonomous vehicles

The impending arrival of autonomous vehicle (AV) technology has the potential to transform how individuals perceive time spent travelling. By removing the need to drive and pay attention to the road, AV users could perform other activities, including those for work or leisure. As a result, AVs are expected to lower the burden of travel and, therefore, the value of travel time (VOTT). Despite the significant impacts that AVs may have on individuals’ choices and the transportation system, few have studied their impacts on travel time perceptions, and even fewer have examined the extent to which these impacts will vary depending on the types of tasks that can be performed within an AV. This study uses stated preference data collected in Fall 2022 to develop mode choice models and subsequently quantify how the availability of three types of AV: privately-owned, exclusive, and pooled AV may shift perceived travel times in the Greater Toronto and Hamilton Area. The error-component mixed logit models highlight the cross-nesting between privately-owned AVs and driving. In addition, this study is the first in Canada to distinguish the VOTT reductions by AV type, trip purpose, and interior description (which caters to different tasks). VOTT reductions as large as 42% less than driving a conventional vehicle were estimated. The results of this study provide additional empirical evidence for AV VOTT reductions (particularly in the Canadian context) and can be used to help craft policies in preparation for the arrival of AVs.

Applying a Bayesian network for modelling the shift from motorcycle to public transport use in Vietnam

Transport mode choice models commonly incorporate factors such as utility maximisation, socio-ecological considerations, socio-demographic characteristics, and psychological factors. However, there is still a lack of integrated models linking objective factors, such as travel mode attributes, demographic & socio-economic characteristics and built environmental characteristics, with subjective factors, such as attitudes, personal norms, and perceived behavioural control, to better understand the commuters’ modal choices. Furthermore, a clear research gap exists on mode choice behaviour in Southeast Asian countries, where motorcycling is widespread. This study aims to address these research gaps by analysing data gathered from 618 Vietnamese motorcyclists between December 2020 and February 2021. Reliability analysis and a Bayesian network are used to identify the objective and subjective factors influencing the intention to use public transport among Vietnamese motorcyclists. The findings highlight that among five subjective factors, personal norm is the most sensitive parameter in calculating the posterior probability distribution of intention and decision to use public transport along with other objective factors, namely travel time and travel cost. The results also reveal that motorcyclists aged 23 + have a higher perceived value of travel time than those aged 23–. In contrast, motorcyclists aged 23– and female motorcyclists have a higher perceived value toward environment-friendly travel modes, such as public transport. At the same time, they do not try to differentiate themselves from the societal standards in terms of motorcycle usage. The findings of this study provide valuable insights to local urban/transport planners and policymakers in Southeast Asian countries.

Application of Generalized Reciprocal Method on 2D Seismic Refraction Data in Mt. Manglayang, West Java

The imaging of shallow subsurface structures, weathered rock thickness and velocity propagation distribution of the rocks can be identified by seismic refraction. This method is one of the geophysical exploration methods utilizing refracted wave once it reaches the boundary of subsurface layer. In this research we used the generalized reciprocal method (GRM) as one of the robust processing methods in analyzing subsurface data. This method was chosen due to its accuracy in interpreting shallow subsurface layer with highly undulating refractors by determining time velocity analysis, XY optimum distances, and time depth analysis, then, the expected depth values can be achieved. The acquisition of data for this research was conducted using 13 geophones with forward and reverse sources, the data were then picked to get travel time values and inverted to obtain real geological setting of the earth. The results were interpreted as 2 layers, the first layer had a velocity distribution of 499.289 m/s which was identified as a weathered layer with a thickness of about 4.74 meters, whereas the second layer was interpreted as clay rock with velocity distribution of 1270.433 m/s with the thickness reached up to 16 meters.
 Keywords: generalized reciprocal method, 2D seismic refraction

Computation and Modelling of Seismic Refraction Tomography for Anisotropic Medium Based on Pseudo Bending Method

Seismic refraction tomography is one of the imaging techniques in geophysical methods used to remodel the near-surface velocity layer structure of the Earth. In this study, we carried out a new computational approach and modelling of seismic refraction tomography using the pseudo-bending method. The true model of the near-surface is designed to be anisotropic medium which is having a low velocity anomaly distribution. This anomaly is constructed in such a way as to be similar to a model of liquid waste away spreading, which exhibits seismic velocities ranging from 1600 m/s to 1800 m/s. Based on our computations and numerical modelling results, it was found that the ray tracing path using pseudo-bending method displays an asymmetrical trajectory when the positions of the source and geophone are exchanged. Altering the shooting configuration from direct shoot (DS) to reversed shoot (RS) also reveals a significant difference in travel time values. The results of delay time tomography inversion, which represents the difference between travel times in the true model and the initial model using the SIRT method, indicate the presence of a low velocity anomaly that can be interpreted as the distribution of liquid waste.

Value of Travel Time is Lower When Being Driven than when Driving Oneself

How does the value of travel time (VOTT) differ between time spent driving and time spent being driven in a car? We examined revealed choices between ridehailing and free-float carsharing using data from an aggregator app that allowed users to choose between these alternatives based on real-time conditions. We used a mixed logit model to control for price, in-vehicle time, and out-of-vehicle time (walk or wait time). The model results indicate that VOTT declines by an average of $23 per hour (approximately 60%) for members of our sample when riding in a ridehailing vehicle versus driving a carsharing vehicle.

Modeling of GPM and LPM in Centrifugal Pump for Obtaining Hydraulic Flow Pattern Types

The types of hydraulic flow patterns in laboratory testing through the use of physical modeling tools often encounter several challenges when confronted with the use of empirical model scales, namely, the issue of scale. Water structures in the horizontal dimension do not experience highly complex issues because there are many measuring instruments available, whether self-made, home industry-produced, or industrial-grade. The presence of water volume in storage can only be tested at a clear scale, especially when it is already within a water tower (reservoir) installation with a specific height. Determining the need for water storage in a water tower is not an easy task to calculate due to differences in height, diameter, and storage capacity. Hydraulic experts often overlook these differences, which can become a problem when there is a demand for the volume of water during peak flow conditions. The solution to this issue needs to be verified by conducting model tests using a device known as the Centrifugal Pump, which has not been previously explored for laboratory research. GPM LPM model tests on this device make use of instruments and numerous pressure measuring tools supplied with pressurized water by a pump at specific, measurable volumes. To analyze the flow rate, flow coefficients, flow velocity, Reynolds number, Froude number, and test results with various speeds (speed meter), researchers test and measure the capacity of GPM LPM for each valve opening, starting with openings of 0.5, 0.75, 1.00, reading the instruments, shifting the speed from 1, 2, 3, 4, up to the highest speed, which is 12. A graph is created to display the test results of the GPM LPM speed booster device, which contains an electric motor. The test is conducted with three repetitions for each valve opening, and the speed and travel time values from the instruments on the test device are recorded and mapped. Subsequently, the analysis results of the GPM LPM test are recommended to provide information to construction planners of water structures. These results show that, under specific conditions of different speeds and valve openings, there are variations in the volume and travel time values. This information can be applied to determine the required storage capacity for each water tower building with a hydraulic flow pattern based on Reynolds number (Re) and Froude number (Fr).

Optimal lane allocation strategy for shared autonomous vehicles mixed with regular vehicles

Autonomous driving technology has the potential to alter the way we travel and is rapidly evolving. Sharing rides in autonomous vehicles may become a popular mode of public transportation in the future. One strategy to enhance operational efficiency is to deploy designated autonomous vehicle (AV) lanes for shared autonomous vehicles (SAVs). This study investigated optimal allocation for dedicated AV lanes considering mixed SAVs and regular vehicles (RVs) flows. First, the standard bottleneck model for morning rush hour was extended to account for both ridesharing and automation, and user equilibrium (UE) solutions were obtained by assuming dedicated AV lanes co-exist with general-purpose (GP) lanes. The equilibrium capacity allocation for dedicated AV lanes was determined for multi-modal traffic scenarios. The study found that commuters may prefer to use SAVs because SAVs were more cost-effective and time-saving. Furthermore, analysis of the fixed payment for ridesharing in SAVs revealed that the system performance could be negatively impacted by high fixed payments. The study proposed an enumeration algorithm for developing lane strategies for discrete lane settings. It was found that the deployment of dedicated AV lanes should be matched to the penetration rate of SAVs and different management objectives, following a gradual rather than a radical process. Finally, a sensitivity analysis was performed considering the value of travel time for SAVs and the bottleneck capacity of a dedicated AV lane. This work provides a new solution to AV lane capacity allocation and offers theoretical support for managers to deploy dedicated AV lane allocation.

Analyzing global passenger flows based on choice modeling in the air transportation system

Airline passenger decisions determine operation of airlines and aircraft. Therefore, global air transport models need to consider these decisions. Thereby, we develop a discrete choice model for passenger decisions describing global passenger flows based on different parameters. The model distinguishes between passenger itineraries defined by attributes like ticket price, travel time and number of transfers. Additional attributes are added gradually. It is estimated using schedule and passenger demand data. Hence, based on topological structures of the air transport system, global passenger flows and elasticities can be identified. Additionally, we provide quantified results describing the elasticity of several types of attributes, the values of travel time, the quality of travel and compare them for different regions, itineraries and travel types.