Transportation Research Part A-Policy and Practice最新文献

{"title":"Corrigendum to “Public-Transportation Credits: The potential of three-part tariffs in public transportation” [Trans. Res. Part A 182 (2024) 104022]","authors":"Silvio Sticher, Kevin Blättler","doi":"10.1016/j.tra.2024.104282","DOIUrl":"10.1016/j.tra.2024.104282","url":null,"abstract":"","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"190 ","pages":"Article 104282"},"PeriodicalIF":6.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A flight risk field model for advanced low-altitude transportation system using field theory","authors":"Zhenyu Zhao,&nbsp;Lanfang Zhang,&nbsp;Ruida Zhou,&nbsp;Genze Li,&nbsp;Shuli Wang,&nbsp;Tingyu Liu,&nbsp;Yating Wu","doi":"10.1016/j.tra.2024.104268","DOIUrl":"10.1016/j.tra.2024.104268","url":null,"abstract":"<div><div>Traffic congestion, as a global issue, often leads to adverse social impacts and huge economic losses, especially in urban areas. Utilizing the available urban low-altitude airspace (ULA) is a potential and promising solution to this problem. To fully leveraging ULA and establishing an advanced low-altitude transportation (ALT) system, ensuring the safety of low-altitude flight is of critical importance. However, the ALT system is currently in the exploratory and developmental stage, and the assessment of flight safety relies primarily on pre-flight evaluations and third-party risk indicators. This study introduces a novel flight risk field model considering risk factors during UAV cruising by introducing a new concept of a flight risk field. The model takes into account the key factors influencing the safety of low-altitude flights, considering both the static characteristics of buildings and the dynamic movements of unmanned aerial vehicles (UAVs). It is capable of reflecting the spatiotemporal variations in flight risks during the UAV cruising process. Finally, the model is validated through numerical examples and simulations. The contribution of this paper is to provide a new idea and method for the safety assessment of the ALT system, which can be further applied to airspace structure design, route optimization, and constitution of traffic regulations, to ensure a reasonable airspace design and enhance the safety of low-altitude flight activities.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"190 ","pages":"Article 104268"},"PeriodicalIF":6.3,"publicationDate":"2024-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Con-Accessibility: Logit-based catchment area modeling for strategic airport system planning","authors":"Sebastian Birolini,&nbsp;Nicolò Avogadro,&nbsp;Paolo Malighetti,&nbsp;Stefano Paleari","doi":"10.1016/j.tra.2024.104270","DOIUrl":"10.1016/j.tra.2024.104270","url":null,"abstract":"<div><div>National airport system plans serve as the primary programmatic documents employed by policy-makers to outline the roles of different airports and devise strategies for their coordinated and integrated development, encompassing economic, environmental, and social perspectives. This paper proposes a modeling framework to estimate the strength of each airport’s influence and contribution to the surrounding territories, providing methodological foundation for assessing airport demand and delineating the scope of airport interactions. We propose a novel origin-based nested logit model of airport demand based on a comprehensive utility function—denoted as <em>con-accessibility</em>—integrating advanced metrics of ground accessibility and airport connectivity. To address the lack of extensive pairwise municipality–airport data, we cast the estimation problem as a nonlinear constrained least-squares optimization problem, solved via a differential evolution algorithm. The framework’s applicability and insights are demonstrated in a real-world case study of the latest Italian national airport system plan. We highlight the model’s capability in addressing three key policy questions: (i) characterizing airport catchments toward investigating the degree of overlap and airport interactions in serving contended areas; (ii) systematically quantifying the overall level of con-accessibility in any region to assess deficits or surpluses and pinpoint areas for strategic interventions; (iii) supporting the assessment and prioritization of various initiatives, including the upgrade of ground access networks, the expansion of airport supply, and the establishment of new airport facilities.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"190 ","pages":"Article 104270"},"PeriodicalIF":6.3,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling COVID-19 travel rebound with automated land use identification","authors":"Jielun Liu,&nbsp;Mei San Chan,&nbsp;Ghim Ping Ong","doi":"10.1016/j.tra.2024.104280","DOIUrl":"10.1016/j.tra.2024.104280","url":null,"abstract":"<div><div>As movement restrictions during the COVID-19 pandemic forced urban workforces around the world to temporarily adopt telecommuting or flexible working arrangements, some speculate that these practices could remain as the ‘future-of-work’. Therefore, transportation and urban planners would both need to react to new post-pandemic work-based travel patterns. Unlike most common methods of analysing post-COVID telecommuting trends that rely on survey responses, this study develops a two-stage methodology of automatic land use identification (ALI) and mixed effects regression for the synthesis of both land use and transportation data with the aim of monitoring the post-pandemic travel recovery situation. Firstly, clustering methods are used for ALI around public transport destinations to generate different classes of regions based on land use characteristic. Mixed effects regression is then conducted to estimate the variability between different classes of regions. To gain insights on the travel rebound in Singapore, the case study focuses on business entity locations and bus transit volumes during the peak hours. Predictive modelling of a hypothetical travel recovery situation indicates that pre-COVID levels of traffic demand could likely return. The findings from this study have implications on transportation and urban planning, as well as decision-making in the post-COVID world and can be used as a basis for further COVID-related behavioural studies.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"190 ","pages":"Article 104280"},"PeriodicalIF":6.3,"publicationDate":"2024-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling the complementarity and flexibility between different shared modes available in smart electric mobility hubs (eHUBS)","authors":"Fanchao Liao ,&nbsp;Dilum Dissanayake ,&nbsp;Gonçalo Homem de Almeida Correia","doi":"10.1016/j.tra.2024.104279","DOIUrl":"10.1016/j.tra.2024.104279","url":null,"abstract":"<div><div>eHUBS are physical locations that integrate two or more electric shared mobility modes. As they provide transport users easier access to a wide range of transport modes, multimodal behaviour is expected to be more common. However, this issue has not been addressed in previous stated preference studies on mode choices involving innovative transport modes. In this study, multimodal behaviour is explicitly addressed both in measurement and in modelling by adopting the multiple discrete–continuous (MDC) modelling framework in contrast to discrete choice models. Instead of asking transport users to indicate the most preferred alternative, they were allowed to choose more than one alternative by allocating trips between several modes. This study aims to answer two questions: 1) whether there is complementarity between the multiple shared modes offered in eHUBS and 2) how would transport users adapt when one of the shared modes that they plan to use becomes unavailable. Using stated mode choice data of non-commuting trips from transport users whose current mode is driving a private car in Manchester, UK, several models under the MDC framework were estimated including Multiple Discrete-Continuous Extreme Value (MDCEV) model, mixed MDCEV model, and the extended Multiple Discrete Continuous (eMDC) model. The results show that there is complementarity between shared electric vehicle (EV) and electric bike (e-bike) offered in the eHUBS. In addition, the research show that the flexibility between those two shared modes is stronger than assumed in the MDCEV model, and common preference heterogeneity cannot fully account for this phenomenon.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"190 ","pages":"Article 104279"},"PeriodicalIF":6.3,"publicationDate":"2024-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142425162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comprehensive impacts of high-speed rail and air transport on tourism development in China","authors":"Wei Wei ,&nbsp;Fengyi Wang ,&nbsp;Tao Li ,&nbsp;Fangzhou Li","doi":"10.1016/j.tra.2024.104263","DOIUrl":"10.1016/j.tra.2024.104263","url":null,"abstract":"<div><div>The comprehensive impacts of different transportation systems on tourism development (TD) are becoming more and more profound. High-speed rail (HSR) and air transport (AT), two closely related, convenient, and fast-traffic options, have increasingly become the preferred choice for travelers. Based on a panel data set of 287 cities in China from 2011 to 2019, the impacts of HSR and AT operations on TD and the heterogeneity of these impacts are explored by using multi-period difference-in-differences (DID) and dose–response (DR) models. The results reveal that AT operation and the simultaneous operations of HSR and AT (HSR-AT operations) have a positive and significant impact on TD. However, the significance of the positive impact of HSR operation on TD is not stable. Furthermore, HSR operation and AT operation have different impacts on the TD of the cities in various regions and the cities with various tourism resource endowments. The findings by the DR model indicate that there are differences in terms of the level of HSR and AT operations in small-medium cities compared to large cities. Meanwhile, HSR and AT operations have different impacts on various classes of cities, and the impacts of HSR and AT operation levels on the TD is positive. The obtained results imply that when seizing the development opportunities of HSR and AT to promote TD, administrators should implement different strategies according to local conditions and the current status of TD.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"190 ","pages":"Article 104263"},"PeriodicalIF":6.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel data-driven approach for customizing destination choice set: A case study in the Netherlands","authors":"Bin Zhang ,&nbsp;Soora Rasouli ,&nbsp;Tao Feng","doi":"10.1016/j.tra.2024.104278","DOIUrl":"10.1016/j.tra.2024.104278","url":null,"abstract":"<div><div>Modeling the destination choice has been of great interest for travel behavior community as well as policymakers in understanding the demand for land use and transportation infrastructures at aggregate and disaggregate levels and possibly devising policies to balance the demand and supplies. One of the challenges underlying predictions of location choice is the large choice set. While traditionally many methods had been devised to limit the choice set size either on a rather ad hoc basis or based on space–time prism by removing the locations out of reach of the subjects, the current study takes a substantially different approach and proposes a data-driven method to customize the generation of the choice set. The proposition is that observing the mobility patterns of citizens for multiple weeks would enable us to limit the choice set, depending on how far the subjects travel (beyond or within the distance they travel for their most frequent activities) to conduct their various activities. More precisely, using longitudinal trajectory data, we first classify people into two subgroups: returners and explorers, based on the size of the area (around their <em>k</em> most visited locations: <em>k</em>-radius of gyration) they move during the observation period. The destination choice set for four types of activities is then customized for returners (and explorers) and is used in a sequence of decisions represented by decision trees for the prediction of their destinations. The models for the whole sample and each subgroup separately are compared. The results suggest that the accuracy of destination prediction improves substantially for all four selected activity types, especially for the returners whose choice sets are formed based on their radius of gyration.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"190 ","pages":"Article 104278"},"PeriodicalIF":6.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A dynamic discrete choice modelling approach for forward-looking travel mode choices","authors":"Joseph Leong,&nbsp;Neema Nassir,&nbsp;Seyed Sina Mohri,&nbsp;Majid Sarvi","doi":"10.1016/j.tra.2024.104272","DOIUrl":"10.1016/j.tra.2024.104272","url":null,"abstract":"<div><div>In this paper, we present a systematic approach based on dynamic discrete choice models (DDCM) to investigate individuals’ forward-looking mode choice behaviours in daily travel tours with multiple destinations. We propose a novel network transformation model that encompasses the entire decision space of all feasible mode combinations for every observed trip/tour in the dataset. By applying the well-established Recursive Logit model structure commonly used in path choice modelling, we address the tour mode choice problem effectively and quantify forward looking considerations in the mode choice process. The proposed model captures the complex considerations individuals take into account when making mode choices. The network transformation incorporates downstream mode limitations into the preceding mode choice options, enabling us to model individuals’ forward-looking behaviour and gain insights into how considerations of future trips such as a shopping in the evening, or school pick-up trip influence previous mode choice decisions earlier in the day. Uncovering and quantifying these hidden forward-looking factors can help modellers better explain the private car usage usually observed for the entire sequences of daily trips, even in presence of competitive alternative modes. The proposed network transformation also enables us to measure the effect of the requirement/preference to return private vehicles (car, motorcycle, and bicycle) home on mode choices in home-bound trips, and subsequently, on the entire daily mode choice decisions. To validate the proposed model, we utilise the VISTA household travel survey data from the Melbourne Metropolitan area in Australia. The model is compared against baseline models, demonstrating its statistical advantages. Additionally, intuitive illustrations using the data showcase the model’s efficacy. From transport planning and policy perspective, tour-based mode choice modelling provides a more comprehensive and precise understanding of travel behaviour by considering the sequence of trips made by an individual. This can help capture the interactions and dependencies between different trips, which trip-based models may overlook. The proposed model is more suitable for analysing the effects of policy interventions like congestion pricing, public transport investments, or new mobility initiatives, as they can better represent the cascading effects of such policies across multiple trips.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"190 ","pages":"Article 104272"},"PeriodicalIF":6.3,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142424617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Do ride-hailing congestion fees in NYC work?","authors":"Yanchao Li,&nbsp;Daniel Vignon","doi":"10.1016/j.tra.2024.104274","DOIUrl":"10.1016/j.tra.2024.104274","url":null,"abstract":"<div><div>What is the impact of congestion policies targeting ride-hailing systems? This work empirically evaluates NYC’s congestion surcharge policy, particularly in light of the city’s forthcoming implementation of congestion pricing. Using a Difference-in-Differences (DiD) framework, our analysis reveals a statistically significant reduction of approximately 11% in overall ride-hailing travel volume following the implementation of the policy. In particular, Lyft experienced a 17% reduction in travel demand while Uber and yellow-cabs experienced reductions of about 9% and 8% respectively. We further elucidate two key mechanisms — travel distance and subway station availability — to explain this reduction. The surcharge policy has a more pronounced impact on shorter trips (with the most significant decline observed in trips less than one mile), and on ride-hailing trips originating from areas with at least one substitute (such as subway or Citi Bike). Furthermore,the policy’s effect seems more pronounced in lower-income areas of the city and seems to reduce street-hailing industry revenues by 8%. However, despite these reductions, the policy does not result in a corresponding decrease in traffic congestion. Thus, it seems that the policy results in a net welfare loss for the city, at least in the shorter term. Our findings provide insights for understanding the dynamics of congestion policies focused on the ride-hailing industry, especially as New York City prepares to introduce congestion pricing.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"190 ","pages":"Article 104274"},"PeriodicalIF":6.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142425164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Year-to-year time allocation and spatial structure of Americans’ daily schedules from 2019 to 2022 and a detailed analysis of the stay-at-home all-day patterns","authors":"Hui Shi,&nbsp;Konstadinos G. Goulias","doi":"10.1016/j.tra.2024.104190","DOIUrl":"10.1016/j.tra.2024.104190","url":null,"abstract":"<div><div>While numerous studies have examined the effects of COVID-19 on our lives, few of them take into account the simultaneous changes in people’s daily routines from both time allocation and spatial movement perspectives. Based on the American Time Use Survey, this study proposes a novel methodology that combines sequence analysis and labeled motifs to probe the evolution of individuals’ time allocation and mobility movements from the pre-COVID period to the post-vaccination period using activity-travel sequences and network-like daily combinations of destinations and trips called motifs.<!--> <!-->Additionally, the relationship between socio-demographic characteristics and the time allocation and spatial movement of people’s daily schedules are investigated using a multinomial logit model and binary logit models. The results show that: (1) each ATUS year (from 2019 to 2022) contains mixed days, work days, and leisure days; (2) most trips decreased and increased proportionally from 2019 to 2022<!--> <!-->and have not returned to pre-pandemic levels; (3) the stay-at-home motif shows the highest percentage and Americans tend to<!--> <!-->follow<!--> <!-->motifs with fewer destinations; and (4) personal and household characteristics influence people’s time allocation and spatial movements differently at different stages of the pandemic outbreak. Our analysis can assist in predicting travel time to reduce traffic congestion and also the timing of energy consumption to avoid energy demand spikes.</div></div>","PeriodicalId":49421,"journal":{"name":"Transportation Research Part A-Policy and Practice","volume":"190 ","pages":"Article 104190"},"PeriodicalIF":6.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}