Article
Engineering, Civil
Yang Zhou, Yuantao Zhang, Quan Yuan, Chao Yang, Tangyi Guo, Yinhai Wang
Summary: Travel data is crucial for understanding individual travel behaviors and estimating travel demand. This study proposes a high-accuracy data collection system based on smartphones, and a hybrid random forest and merging algorithm is used to more accurately and efficiently identify travel modes in complex trips.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Transportation Science & Technology
Jiaqi Zeng, Yi Yu, Yong Chen, Di Yang, Lei Zhang, Dianhai Wang
Summary: In this paper, a sequence-based framework is proposed for travel mode identification from GPS tracks. The framework employs a sequence-to-sequence model to obtain accurate and reasonable travel mode label sequences by constructing feature sequences for each GPS trajectory. Comprehensive evaluations of real-world applications show that the sequence-based TaaS outperforms segment-based models in practice.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Engineering, Civil
Xiatian Wu, Don MacKenzie
Summary: This study uses representative samples from the 2001, 2009, and 2017 National Household Travel Surveys to explore the impacts of taxis and ridesourcing services on people's travel behavior. It found that ridesourcing has greatly increased T/R trips, mostly occurring in densely populated and transit-oriented regions.
Article
Engineering, Civil
Suxing Lyu, Tianyang Han, Peiran Li, Xingyu Luo, Takahiko Kusakabe
Summary: This study proposes a framework called DACross for inferring the chained trip purpose by innovatively forming trip chains that treat trip activities and travelled geographic zones as two chains with mutual interactions. DACross consists of two parallel attentive branches and a co-attentive feature crossing module to fully learn the intra- and inter-chain dependencies. Extensive experiments on four large-scale real-world datasets prove the overall superiority of the proposed DACross and its generalizability among different cities and scenarios.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Economics
Antonio Ross-Perez, Neil Walton, Nuno Pinto
Summary: This study explores the application of a Bayes ruled-based algorithm to uncover the purpose of trips from a dockless bike-sharing system in Manchester. The findings indicate that the user's relationship with the service is complex, with trips to residential areas being the most important. The study provides insights into people's travel preferences and bridges the gap between new mobility systems and traditional transport strategies.
JOURNAL OF TRANSPORT GEOGRAPHY
(2022)
Article
Transportation
Sicheng Wang, Joy Jeounghee Kim, Yanfeng Xu
Summary: This study analyzed the association between daily trips and multidimensional disadvantages in demographic characteristics, socioeconomic status, transportation barriers, and internet use based on the 2017 U.S. National Household Travel Survey. The results revealed that these disadvantages varied in their impact on trip likelihood depending on the type of disadvantage, trip purpose, and trip day. The findings provide policy implications for reducing the effects of these disadvantages on trip likelihood.
TRAVEL BEHAVIOUR AND SOCIETY
(2022)
Article
Computer Science, Interdisciplinary Applications
Michael J. Campbell, Philip E. Dennison, Matthew P. Thompson
Summary: Accurately predicting pedestrian travel times is crucial in various fields such as emergency response, firefighting, disaster management, law enforcement, and urban planning. However, the relationship between pedestrian movement and landscape conditions varies greatly among individuals, posing challenges in estimating travel times for broad populations. This study presents an approach using a large crowdsourced GPS database to predict the variability in pedestrian travel rates and times. The results demonstrate the ability to estimate travel time variability with less than 10% error, providing valuable insights for urban planning and path analysis.
COMPUTERS ENVIRONMENT AND URBAN SYSTEMS
(2022)
Article
Geography
Yehua Dennis Wei, Weiye Xiao, Yangyi Wu
Summary: The study examines polycentric development in the Wasatch Front Region (WFR), Utah, finding that it is still dominated by a single urban center rather than being polycentric. However, walking and biking trip chains are common in urban centers, indicating a potential need for polycentric development. The results emphasize the importance of job opportunities and amenities in achieving functional polycentricity.
Article
Engineering, Civil
Yicong Liu, Eric J. Miller, Khandker Nurul Habib
Summary: This paper examines the feasibility of using discrete choice models and machine learning models for trip purpose inference based on smartphone GPS trajectories and land-use data. The results show that both discrete choice models and machine learning models can achieve high prediction accuracies for home trips and work trips, but lower accuracies for most of the discretionary trip purposes. The study suggests that machine learning models may not be the best solution for trip purpose inference due to their lack of theoretical background.
JOURNAL OF TRANSPORTATION ENGINEERING PART A-SYSTEMS
(2023)
Article
Transportation Science & Technology
Yitao Yang, Bin Jia, Xiao-Yong Yan, Rui Jiang, Hao Ji, Ziyou Gao
Summary: In this study, a data-driven method is proposed to identify the origins and destinations of freight trips by analyzing a large amount of heavy truck GPS trajectories. By objectively defining speed and time thresholds and considering the city freight context and activity patterns, the accuracy of the method is improved.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Computer Science, Information Systems
Ji Li, Xin Pei, Xuejiao Wang, Danya Yao, Yi Zhang, Yun Yue
Summary: This study presents a novel method for inferring transportation modes from GPS and GIS data, achieving 91.1% accuracy on the GeoLife dataset by using feature extraction and machine learning with GIS features. Geographic Information System (GIS) features improved overall accuracy by 2.5% and recall of bus and subway modes by 3.4% and 18.5%.
TSINGHUA SCIENCE AND TECHNOLOGY
(2021)
Article
Economics
Punyabeet Sarangi, M. Manoj
Summary: This paper investigates household task allocation decisions for non-work activity episodes by considering the purpose of the activity and accompanying person arrangements. The findings provide valuable insights into the preferences and tendencies of household members, shedding light on intra- and inter-group interactions and highlighting the importance of understanding individual characteristics, household demographics, and seasonal/temporal factors in activity choices.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2022)
Article
Engineering, Civil
Anna Reiffer, Lukas Barthelmes, Martin Kagerbauer, Peter Vortisch
Summary: This paper examines the representation of work-related travel patterns in household travel surveys and commercial travel surveys. The findings indicate that work-related travel patterns are complex, and the household travel survey does not adequately capture the travel patterns of mobile workers. Additionally, not all commercial trips are generated by motorized vehicles, as a significant proportion of work-related trips are undertaken using public transport or active modes of transport that are not accounted for in commercial travel surveys. The results suggest that researchers and transport planners should pay more attention to work-related travel behavior and recognize that traditional household travel surveys may not provide a comprehensive understanding of the population's travel patterns.
TRANSPORTATION RESEARCH RECORD
(2022)
Article
Green & Sustainable Science & Technology
Zihao An, Eva Heinen, David Watling
Summary: This research examines the differences in the level and correlates of multimodality based on trip purpose. The study uses one-week travel diaries from the English National Travel Survey and finds that the level of multimodality varies depending on the purpose of the trip, as well as the time-space variability and number of trip stages. The research also identifies disparities in correlates of multimodality across trip purposes. These findings can support the development of purpose-specific policies to promote multimodality.
INTERNATIONAL JOURNAL OF SUSTAINABLE TRANSPORTATION
(2023)
Article
Economics
Dorian Antonio Bautista-Hernandez
Summary: This study examines the driving factors of non-work travel trip chaining in the Mexico City Metropolitan Area and analyzes the travel patterns of students and other travelers using the 2017 Household Origin-Destination Survey data. The findings suggest that car users, mixed transportation users, and others have the most complex travel patterns, and urban dense and diverse environments are associated with increased trip chaining and tour complexity.
JOURNAL OF TRANSPORT GEOGRAPHY
(2022)
Article
Economics
Valeria Bernardo, Xavier Fageda, Jordi Teixido
Summary: The study finds that flight ticket taxes have a significant impact on low-cost airlines' supply and carbon emissions, resulting in a decrease of 12% in the number of flights and a 14% reduction in carbon emissions. Additionally, the burden of the taxes is higher for passengers paying low fares, affecting avoidable flights more significantly.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2024)
Article
Economics
Xingxing Fu, Dea van Lierop, Dick Ettema
Summary: This study investigates the relationship between multimodality and perceived transport adequacy and accessibility. The results show that multimodality is burdensome, especially for car-dependent individuals, and leads to lower perceived achievement or accessibility for those with limited access to a car.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2024)
Article
Economics
Henrik Johansson Rehn, Lars E. Olsson, Margareta Friman
Summary: This paper presents the Framework of RoUtIne Transitions in daily travel (FRUIT), which analyzes the impact of life events on travel behavior changes and identifies the critical phases in this process. By integrating theories and concepts, the framework provides a theoretical basis for interventions aimed at improving sustainable travel. The applicability of FRUIT is illustrated through an empirical case, and the implications for future research and policy are discussed.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2024)
Article
Economics
Peng-Cheng Xu, Qing-Chang Lu, Chi Xie, Taesu Cheong
Summary: This study investigates the resilience evaluation of interdependent networks. A model is developed to quantify the impacts of network interdependency on the resilience of interdependent transit networks, considering interdependency relations, network topology, flow characteristics, and demand distribution. The model is applied to the metro and bus networks of Xi'an, China. Results show that node degree heterogeneity in topology, bidirectional function dependency among networks, and flow matching between networks are important factors influencing network resilience.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2024)
Article
Economics
Jeppe Rich, James Fox
Summary: Many transport models allocate all costs to the car driver without considering the cost sharing among passengers. This paper questions this premise and argues that cost sharing can occur in various forms, which should be properly accounted for in transport models. The empirical evidence from Denmark suggests that not accounting for cost sharing may result in biased cost elasticities and occupancy rates.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2024)
Article
Economics
Jorik Grolle, Barth Donners, Jan Anne Annema, Mark Duinkerken, Oded Cats
Summary: High-speed rail is considered a promising alternative for long-distance travel, but the current state of the European HSR network is poorly connected. This study presents a customized version of network design and frequency setting problem for HSR, and analyzes the performance under various policies and design variables. The results show that considering externalities leads to more extensive networks and mode shifts, but requires high public investments. The importance of network integration and cross-border cooperation is highlighted. The findings aim to contribute to the design of an attractive and competitive European HSR network.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2024)
Article
Economics
Mounisai Siddartha Middela, Gitakrishnan Ramadurai
Summary: This study addresses the research gaps in understanding the effect of regression models, measurement period, and spatial dependence on Freight Trip Generation (FTG) modeling and freight-related policies. The results show that the spatial Zero-Inflated Negative Binomial (ZINB) model is the best for daily and weekly Freight Trip Production (FTP), while the non-spatial Negative Binomial (NB) model is the best for daily and weekly Freight Trip Attraction (FTA). The study also highlights the importance of considering spatial dependence and using count models with a week as the measurement period.
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2024)
