Travel Scenarios Research Articles

The Impact of Travel Scenarios and Perceptions on Choice Behavior towards Multi-Forms of Ride-Hailing Services: Case of Nanjing, China

The Impact of Travel Scenarios and Perceptions on Choice Behavior towards Multi-Forms of Ride-Hailing Services: Case of Nanjing, China

Life cycle costing analysis of a retrofitted hydrogen-powered locomotive: Canadian context

The transportation sector must adopt cleaner alternatives to meet global emission reduction goals and attain net-zero emissions by 2050. Hydrogen stands out as a promising solution for decarbonizing the railway sector. This study conducts an economic assessment of hydrogen locomotives, considering their entire life cycle. Life cycle costs are analyzed across various travel scenarios and life stages. For shorter distances, the operational phase and capital costs of retrofitting components contribute 64% and 21% to the total life cycle costs, respectively. In contrast, longer distances are dominated by the operational phase, representing nearly 90% of the total costs. Clean hydrogen must reduce costs to compete with diesel locomotives, as only non-sustainable hydrogen currently matches diesel operational expenses. Anticipated advancements in hydrogen technology are expected to make clean hydrogen more accessible, leading to a significant reduction in the life cycle costs of hydrogen locomotives.

An analysis of EV charging and route choice behavior considering the effects of planning ability, risk aversion and confidence in battery in long-distance travel

The increasing demand for long-distance and intercity travel is driven by the progress in regional transportation integration and the establishment of charging infrastructure. This increase suggests that the use of electric vehicles (EVs) for long-distance trips is likely to become more prevalent in the future. Therefore, there is an urgent need for more studies on the travel behavior of EV drivers for long-distance trips. However, there are few studies looking at the travel behavior of EV drivers on long-distance trip and multiple charging during trips. To fill this gap, this study identified EV drivers’ preferences for charging and route choice in long-distance or intercity travel on the basis of a stated preference survey, with the Shandong highway network as the travel scenario. A nested logit (NL)-based hybrid choice model was used to investigate the impacts of personal attitudes, namely planning ability, risk aversion and confidence in battery, on the drivers’ charging times choice behavior. The NL structure consists of two levels, with the upper level focusing on the charging times decision process, and the lower level analyzing the choice behavior of routes with no charging, routes with charging once, and routes with charging twice. The results show that the initial state of charge, and attitudes significantly influence the decision on charging times. In addition, EV drivers who are risk-averse and lack confidence in the battery tend to charge, whereas drivers with strong planning ability prefer to charge once in long-distance travel. Charging and resting simultaneously is the best way to meet the needs of charging and resting, and reduce the time lost while driving. These results provide insights on drivers’ travel planning and charging infrastructures planning for long-distance trips.

Measuring geographic access to emergency obstetric care: a comparison of travel time estimates modelled using Google Maps Directions API and AccessMod in three Nigerian conurbations.

Google Maps Directions Application Programming Interface (the API) and AccessMod tools are increasingly being used to estimate travel time to healthcare. However, no formal comparison of estimates from the tools has been conducted. We modelled and compared median travel time (MTT) to comprehensive emergency obstetric care (CEmOC) using both tools in three Nigerian conurbations (Kano, Port-Harcourt, and Lagos). We compiled spatial layers of CEmOC healthcare facilities, road network, elevation, and land cover and used a least-cost path algorithm within AccessMod to estimate MTT to the nearest CEmOC facility. Comparable MTT estimates were extracted using the API for peak and non-peak travel scenarios. We investigated the relationship between MTT estimates generated by both tools at raster celllevel (0.6 km resolution). We also aggregated the raster cell estimates to generate administratively relevant ward-level MTT. We compared ward-level estimates and identified wards within the same conurbation falling into different 15-minute incremental categories (<15/15-30/30-45/45-60/+60). Of the 189, 101 and 375 wards, 72.0%, 72.3% and 90.1% were categorised in the same 15- minute category in Kano, Port-Harcourt, and Lagos, respectively. Concordance decreased in wards with longer MTT. AccessMod MTT were longer than the API's in areas with ≥45min. At the raster cell-level, MTT had a strong positive correlation (≥0.8) in all conurbations. Adjusted R2 from a linear model (0.624-0.723) was high, increasing marginally in a piecewise linear model (0.677-0.807). In conclusion, at <45-minutes, ward-level estimates from the API and AccessMod are marginally different, however, at longer travel times substantial differences exist, which are amenable to conversion factors.

India’s G20 Presidency and Impact on Indian Tourism, Travel and Hospitality Business

It has been called Bharat’s G20 moment and how, the nation is using the opportunity to boost tourism and its vibrant culture. Milestones in any business are necessary, as they usher in a turning point. The push and pull factors of India, has ensured, not only inbound tourism, but galvanized domestic tourism on account of the facilities and opportunities and yes, the pride of every citizen to see his/her own country. If Covid-19 was a milestone with the learnings that it provided, G20 too has helped evoke the tourism, travel, and hospitality (TTH) business to reach the $1 trillion mark by 2047; when the nation celebrates its 100 years of existence as an independent nation. It was a moment of pride when Prime Minister Narendra Modi, leading the Indian delegation took over the G20 Presidency in 2022 from Indonesia and it was official that from 1st December 2022 to 30th November 2023. It was envisaged that a total of 215 G20 meetings would be conducted across 55 locations and tourism would have a total of four meetings. Three of the official meetings under the tourism track led by India’s G20 Sherpa, Mr. Amitabh Kant would be held at: Gujarat (Rann of Kutch), West Bengal (Siliguri) and Jammu and Kashmir (Srinagar). The fourth Ministerial Level tourism meeting of G20 leaders was organized in Goa where a multitude of decisions were taken on various domains that will impact the TTH businesses and yes, most importantly environmental. The research paper focuses on what that TTH stakeholders feel about the G20 meetings in India and how it would impact the Travel and Tourism scenario, both inbound tourism (IBT), outbound tourism (OBT) and domestic.

Beyond Relevance: Factor-level Causal Explanation for User Travel Decisions with Counterfactual Data Augmentation

Point-of-Interest (POI) recommendation, an important research hotspot in the field of urban computing, plays a crucial role in urban construction. While understanding the process of users’ travel decisions and exploring the causality of POI choosing is not easy due to the complex and diverse influencing factors in urban travel scenarios. Moreover, the spurious explanations caused by severe data sparsity, i.e., misrepresenting universal relevance as causality, may also hinder us from understanding users’ travel decisions. To this end, in this article, we propose a factor-level causal explanation generation framework based on counterfactual data augmentation for user travel decisions, named Factor-level Causal Explanation for User Travel Decisions (FCE-UTD), which can distinguish between true and false causal factors and generate true causal explanations. Specifically, we first assume that a user decision is composed of a set of several different factors. Then, by preserving the user decision structure with a joint counterfactual contrastive learning paradigm, we learn the representation of factors and detect the relevant factors. Next, we further identify true causal factors by constructing counterfactual decisions with a counterfactual representation generator, in particular, it can not only augment the dataset and mitigate the sparsity but also contribute to clarifying the causal factors from other false causal factors that may cause spurious explanations. Besides, a causal dependency learner is proposed to identify causal factors for each decision by learning causal dependency scores. Extensive experiments conducted on three real-world datasets demonstrate the superiority of our approach in terms of check-in rate, fidelity, and downstream tasks under different behavior scenarios. The extra case studies also demonstrate the ability of FCE-UTD to generate causal explanations in POI choosing.

Collaborative strategy for electric vehicle charging scheduling and route planning

AbstractDue to varying energy demands and supply levels in different regions, the distribution of power load exhibits an imbalanced state. It contributes to increased power loss and poses a threat to the security constraints of the electrical grid. Simultaneously, the global energy transition has led to a continuous increase in the proportion of renewable energy integrated into the grid. Electric vehicles (EVs), serving as representative of renewable energy, further magnify this load imbalance with their charging requirements, which poses a significant challenge to the stable operation of the grid. Therefore, to ensure the smooth operation of the grid under the context of renewable energy integration, the authors investigate the coordinated strategies of EV charging scheduling and route planning. The authors first model the coupling of the transportation network with the smart grid as a cyber‐physical system. Subsequently, the authors simulate and analyse the daily charging load curve of the network, capturing the travel characteristics of EVs. Based on this, the authors research the EV charging scheduling in both individual and collective travel scenarios during peak and off‐peak hours. For the off‐peak travel period of EVs, a charging schedule strategy based on travel plans is proposed, which reduces the time cost of EV owners' travel. Furthermore, for the collective travel of a large number of EVs within the system, a multi‐EV charging scheduling strategy based on charging station load balancing is presented. This strategy effectively balances the load levels of various charging stations while reducing the overall system travel time. Ultimately, through experimental results, the authors demonstrate that by deploying appropriate charging scheduling strategies, EVs cease to be a burden on the grid and can be transformed into tools for balancing the loads across different regions.

Accessibility and Equity Analysis of Highway-Railway Traffic Network Based on Real-Time Route Planning Data: A Case Study of Shandong Peninsula Urban Agglomeration, China

As a bond of geospatial and socioeconomic ties, transport supports the development of regions. With the rapid development of the economy, the coordinated development of regional transport has become a concern. To narrow the gap in transport development between cities and achieve sustainable development in regional transport, this study took the Shandong Peninsula urban agglomeration as the research object and using real-time path planning data assessed accessibility of the traffic network under two travel scenarios: cars and car-connected train. Based on the results of accessibility calculations, the Gini coefficient and Theil index were used to measure the equity of regional traffic networks. The results showed that (1) overall accessibility under the two travel scenarios showed a pattern of gradual decay from the center to the periphery; (2) both the accessibility and equity of the highway network were better than those of the railway network; (3) differences in regional development were the main sources of overall regional transport inequity. The research results provide a useful reference for the planning and construction of urban agglomeration traffic networks.

Exploring the Commuting Decision-Making Behavior of Low-Income Groups Based on Cumulative Prospect Theory

Based on cumulative prospect theory, this study proposes a decision-making model to reveal the commuting behavior of low-income groups under uncertain conditions. Considering the commuting characteristics of this group, travel economic cost is incorporated into the model. The decision-making behavior of low-income groups under different travel scenarios is analyzed to acquire the priority of commuting plans. Based on a stated preference survey of residents in Beijing, the commuting behavior of low-income groups is empirically analyzed. The results show that low-income groups will be affected by individual risk preference and characterized by bounded rational characteristics when making commuting decisions under uncertain conditions. Moreover, travel economic cost is a crucial factor for the decision-making of this group. When the travel budget time is less than the perceived time, they tend to seek risks and take punctual arrival as their primary goal. On the contrary, they tend to avoid risks. On the basis of ensuring the travel time meets their needs, low-income commuters always seek the economy and reliability of their travel plans. The empirical results further verify that the proposed model effectively describes the commuting decision-making behavior of low-income groups, and it is superior to the expected utility theory with respect to performance and behavior disclosure. This study provides a reference for improving the commuting efficiency and experience of low-income groups.

Predicting the carbon emission reduction potential of shared electric bicycle travel

Shared electric bicycle (SEB) has rapidly gained prominence as a mode of shared mobility in China. This study aims to explore the impact of SEB travel on carbon emissions reduction in urban transportation systems. Employing a system dynamics approach, a predictive model is developed with five subsystems: socio-economic subsystem, SEB travel subsystem, traditional travel subsystem, traffic congestion subsystem, and carbon emissions subsystem. Taking Changsha City as a case study, the carbon reduction potential of SEB is evaluated by analyzing different travel scenarios. The results show that urban transportation carbon emissions can be reduced by about 3.3% under the SEB travel alternative scenario. Compared to infrastructure development or private car restriction scenarios, the SEB alternative is more viable and sustainable. SEB exhibits advantages over other public transportation in alleviating urban transportation burdens and reducing emissions. Sensitivity analysis emphasizes the key role of increasing distance by SEB travel in enhancing carbon reduction.

Analisis Atribut Produk Wisata Sejarah Di Candi Tanjung Medan

Indonesia is the largest archipelagic country in the world which has cultural diversity. The development of the tourism sector in Indonesia continues to be carried out in various regions until now, one of which is the Tanjung Medan Temple. This research aims to analyze the attributes of historical tourism products at Tanjung Medan Temple. This research uses a descriptive method with a qualitative approach, with data collection through interviews, observation and documentation. Using qualitative descriptive data analysis that describes the attributes of historical tourism products at Tanjung Medan Temple. Determining research informants used snowball sampling with a total of 11 informants, but if no conclusions were found, the researcher had the right to add further informants, with the criteria being figures from the Tourism Office, managers, ninik mamak, the community, visitors to the Tanjung Medan temple. The results of the research show that cultural products are in the form of movable cultural heritage in the form of linga yoni, peripih, and jars made of clay. The narrative product at Tanjung Medan Temple consists of a tour guide and interpretation panels. Tourist products consist of travel scenarios and product packaging. Destination products consist of main attractions, accommodation, transportation, restaurants, souvenir shops, infrastructure. It can be concluded that the results of the document study during pre-research show that there are no tourist packages available in West Sumatra which makes Tanjung Medan Temple one of the destinations for tourist visits. So it is necessary to develop historical tourism product attributes at Tanjung Medan Temple.

Competitive advantage of car-sharing based on travel costs comparison model: A case study of Beijing, China

In recent years, car-sharing has emerged and developed in different cities in China, supplementing other urban transportation modes, but also triggering fierce competition with some of them, such as taxis. In this study, we use the car-sharing orders and GPS trajectory data of a company in Beijing, China, to discuss the competitive advantages, market, and development trends of car-sharing from the perspective of travel costs. By building a travel costs comparison model, we calculate the travel costs of car-sharing and taxis under the same travel scenario, comparing their cost differences in the dimensions of travel mileage, duration, utilization efficiency, etc., and locating the cost advantage space of car-sharing. Further, we discuss the impact of different elements of travel (such as time cost, waiting time, etc.) on the cost advantage of travel by car-sharing. The results reveal that, under the current pricing conditions, the cost advantage of car-sharing is particularly obvious when the rental duration is not too long (less than 14 h), the utilization efficiency is relatively high, and the stop time is shorter than 8 h. We also find that it makes great cost advantage of using car-sharing in periods or areas of urban taxi shortages. In the cases of short travel, car-sharing have bigger cost advantage for the middle and low-income groups. In addition, the popularity of bike-sharing can also increase the cost advantage of car-sharing, which indicates that the synergy of different travel models could promote the development of car-sharing. However, when people travel long, the cost advantage of car-sharing would be minimally affected by the elements, such as people's income and the development of bike-sharing. In other words, car-sharing would keep its cost advantage in the cases of long travel, especially when its utilization efficiency is high and the travel stop time is short.

TREND KESUKAAN PARK AND RIDE DENGAN METODE STATE PREFERENCE

Palembang city government chose light rail transit (LRT) as public transportation to overcome the problem of traffic congestion. However, the use of public transportation in the city of Palembang is not optimal, so traffic jams occur, It is necessary to develop facilities that can attract people's interest in using public transportation. This research uses the Stated Preference Method to determine socio-economic characteristics, travel characteristics, and people's preferences for the development of Park and Ride facilities in Palembang City. The respondents for this research were 100 LRT transportation passengers. From the research results, it is known that the majority of passengers are college students, aged between 19-25 years, with an income of less than IDR 1,000,000 and the reason for traveling is for recreation or entertainment. Based on descriptive analysis to determine respondents' preferences for the development of the Park and Ride concept offered in the Stated Preference Survey, the results obtained from 6 (six) travel scenarios obtained a total of 2400 choices from 100 respondents. Travel by private vehicle (Option A) was chosen 1512 (63%) times, while travel by the Park and Ride system integrated with public transportation was chosen 888 (37%) times.

How Memorable Are Agrifood Travel Experiences?

Destinations seek to increase their competitiveness by offering memorable experiences that can stimulate repeat visitation and positive word of mouth. Travel experiences centered on agrifood systems (i.e., agrifood tourism) encompass a set of attributes (e.g., authenticity and interaction with locals) that tend to be memorable. However, the extent to which these attributes contribute to memorability warrants further investigation. Thus, this study identified common and distinct elements of memorability across agritourism, culinary tourism, and craft-beverage tourism compared to beach tourism (control group). We surveyed a panel (n = 1019) in 2023 using a hypothetical travel scenario with four experience options. A multivariate analysis of variance showed high levels of memorability across various attributes of the agrifood experiences (e.g., learning opportunities and hands-on participation), with few differences across them, as compared to beach tourism. This study advances the scholarly construct of agrifood tourism by incorporating memorability within its complex dynamics. The study results also provide insights that marketers and managers of destinations with a mix of agrifood experiences can use to improve destination competitiveness and memorability (e.g., increasing educational offerings and adding more participative activities).

Research on the Factors Influencing Residential Energy Consumption Behaviour

In accordance with the double carbon target proposed in 2020: to achieve "carbon peak" by 2030 and "carbon neutrality" by 2060. The background of this research is how to optimize the industrial structure and guide low-carbon consumption through energy production and consumption restructuring. In the post-epidemic era, a series of changes in people's consumption concepts and behaviour have taken place, which made positive or negative impacts on low-carbon consumption. The research focus here is to adopt the survey analysis method, collecting primary analysis data through data collection, questionnaires, and interviews. This paper focuses on the validation and practice of this research method. Researches have found that the current direct energy consumption behaviours of residents concentrated in the household scenario and the travel scenario. The low-carbon nature of these scenarios is influenced by two main decisions: the choice of consumption mode at the first consumption stage and the choice of consumption mode at the ongoing consumption stage. The factors that influence these decisions vary from stage to stage, and different strategies can help guide residents' low-carbon consumption behaviour.

Revealing the travel community in the integrated system of free-floating bike and metro

The free-floating bike (FFB) program is embraced by the cities worldwide and has influenced the existing transit service, especially the metro system. However, the urban regional mobility of FFB under the mixed relationship with metro is still unclear. In this study, we address this issue based on the three-month weekday FFB trips data in Shenzhen. First, we quantify to what extent the FFB competes with, connects with and complements metro system, and identify the corresponding travel scenarios. Then, the scenario-oriented travel communities that can reflect the distinctive urban regional mobility are detected. From the result, four kinds of travel scenarios are recognized, where the difference of metro service coverage towards access and egress FFB trips is further discussed. Moreover, by analyzing the development of the travel communities, we reveal the spatial and temporal characteristics of urban regional mobility. The findings enhance the understanding about the travel behaviors of FFB-metro integrated system, and can improve the daily operation of the transportation system.

Defensive pessimism-like thinking in practice: the (dys)functional strategy for coping with risk uncertainty in the offshore oilfield?

UK Continental Shelf (UKCS) offshore oilfield drilling is recognised as a high-hazard occupation that occurs in one of the riskiest locations in the world. Dangerous machinery, combustible hydrocarbons, unpredictable weather conditions, rapidly shifting situational factors, rotating crews, and lengthy travel over rough seas by helicopter are just some salient risk-factors. At present, little scholarly research explores how regular offshore workers develop cognitive strategies to attempt to cope with ever-present risks. This research draws on an embedded ethnography of a remote offshore oilfield drilling platform in the UK North Sea. The risks of working offshore and the strategies workers developed and employed to deal with continual risk uncertainties were discussed in face-to-face interviews with thirty-five active drilling crew as they laboured on complex well-drilling operations. Notably, defensive pessimism (DP) like thinking was recurrently exhibited, with many workers recounting detailed narratives of mental role-play for ‘worst case’ offshore and helicopter travel scenarios. Often, thinking appeared interlinked with strengthening motifs for workers’ preparation and planning skills regarding occupational risk possibilities. These strategies are presented, as is a discussion of the effects such strategies had upon oilmen. The benefits of growing scholarly conversation surrounding DP-like thinking in practice are highlighted. alongside the methodological application of DP theory for further study surrounding practical development of coping strategies in similar high-risk workspaces.

Modelling Geographic Accessibility of Primary Health Care Facilities in Bauchi Local Government Area

Achieving universal health care (UHC) coverage has been at the forefront of the United Nations (UN) agenda for 2030. Inequality in health care service provision continues to increase, hence militating against the achievement of reducing unequal access to health care. Access is a critical component of the healthcare delivery system that is impacted by both spatial and non-spatial elements. This study utilized health facilities, population, and other open-source data to analyze the distribution and spatial accessibility of healthcare service centers by using Geospatial technologies in the Bauchi Local Government Area of Bauchi State - Nigeria. Two traveling scenarios (Driving and Walking) were used to determine the travel time to the nearest health facilities, defined within a maximum of 30 minutes traveling time using AccessMod (Online) and ArcGIS Pro. It was found that 87% and 75% of the population are within 15 and 30 minutes of travel time by driving and walking, respectively, while 1.3% of the population are outside a 15 km radius of any health facility with a ratio of 1 to 4,454 population to a health facility. The result shows a significant spatial disparity in geographic accessibility and spatial coverage, with some parts of the rural areas not having access to the existing health facility network, regardless of the travel scenario chosen. This will offer an innovative approach to reducing gaps in healthcare access and subsequently enhance the efficient and effective delivery of healthcare services in low- and middle-income countries (LMIC) to achieve UHC. Keywords: AccessMod, Bauchi Local Government Area, Geographic Accessibility, Health Facilities, Spatial Coverage, Universal Health Coverage.

Travel scenario workshops for geographical accessibility modeling of health services: A transdisciplinary evaluation study.

Limited geographical access to quality Emergency Obstetric and Newborn Care (EmONC) is a major driver of high maternal mortality. Geographic access to EmONC facilities is identified by the global community as a critical issue for reducing maternal mortality and is proposed as a global indicator by the Ending Preventable Maternal Mortality (EPMM) initiative. Geographic accessibility models can provide insight into the population that lacks adequate access and on the optimal distribution of facilities and resources. Travel scenarios (i.e., modes and speed of transport) used to compute geographical access to healthcare are a key input to these models and should approximate reality as much as possible. This study explores strategies to optimize and harmonize knowledge elicitation practices for developing travel scenarios. Knowledge elicitation practices for travel scenario workshops (TSW) were studied in 14 African and South-Asian countries where the United Nations Population Fund supported ministries of health and governments in strengthening networks of EmONC facilities. This was done through a mixed methods evaluation study following a transdisciplinary approach, applying the four phases of the Interactive Learning and Action methodology: exploration, in-depth, integration, and prioritization and action planning. Data was collected in November 2020-June 2021 and involved scoping activities, stakeholder identification, semi-structured interviews (N = 9), an evaluation survey (N = 31), and two co-creating focus group discussions (N = 8). Estimating realistic travel speeds and limited time for the workshop were considered as the largest barriers. The identified opportunities were inclusively prioritized, whereby preparation; a favorable composition of attendees; validation practices; and evaluation were anticipated to be the most promising improvement strategies, explaining their central place on the co-developed initial standard operating procedure (SOP) for future TSWs. Mostly extensive preparation-both on the side of the organization and the attendees-was anticipated to address nearly all of the identified TSW challenges. This study showed that the different identified stakeholders had contradicting, complementing and overlapping ideas about strategies to optimize and harmonize TSWs. Yet, an initial SOP was inclusively developed, emphasizing practices for before, during and after each TSW. This SOP is not only relevant in the context of the UNFPA EmONC development approach, but also for monitoring the newly launched EPMM indicator and even in the broader field of geographic accessibility modeling.

Value of travel time savings of autonomous vehicle commuters: a segmented valuation for local and inter-city travel

ABSTRACT In this study we aim to identify how the adoption of autonomous vehicles (AVs) affects the value of travel time savings (VOTTS) for commuting trips under different trip distance scenarios (local and inter-city travel). Using a stated preference survey administered to Korean commuters in 2019, two multinomial logit (MNL) mode choice models are developed. These models are stratified by trip length and include four alternatives: AV with a manual driving option (AVMD), AV with a self-driving option (AVSD), shared AV (SAV), and public transit (PT). The results show that the value of in-vehicle travel time savings for AVSD (on average, $7.61/hr) is lower than for the other two AV modes (AVMD = $10.26/hr, SAV = $13.67/hr). It suggests that travelers tend to pay less to reduce travel time while using a private hands-free mode because it allows travelers to use their travel time more productively and/or relieve stress for driving. In addition, changes in the VOTTS for each mode vary by trip length. As travel distance increases, VOTTS for shared modes (SAV and PT) tends to decrease. The value of in-vehicle travel time for SAV in the local travel scenario is the highest among the four modes but is considerably lower than that in the inter-city scenario. These differences suggest that travelers require a certain amount of time to fully use their in-vehicle time, highlighting the importance of trip length when determining the VOTTS. Interestingly, the VOTTS for PT is lower than three AV modes, implying that it might be too early to expect substantial reduction in the VOTTS for AVs due to potential risks of accidents, unfamiliarity with AVs, or immature technology of AVs. Highlights Likelihood of choosing autonomous vehicles is modelled based on trip length. Changes in value of travel time savings for each mode vary by trip length. Value of travel time savings for public transit is lower than autonomous vehicles. Self-driving vehicles have a low value of travel time savings than other modes. People need a certain amount of time to fully perform activities while traveling.