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From a passenger perspective, the duration of trip delays is a major concern, and passenger trip delays may be longer than the train delays. Several studies have focused on predicting train delays, but the research on the duration of the disruption impacts on passenger trips is limited given that the duration is not observed directly. This paper proposes a probabilistic method to estimate the disruption impact duration using smartcard data, explores statistical and machine learning models to predict the duration of impacts on passengers, and identifies influencing factors including incident characteristics, operating conditions, infrastructure, external factors, and demand. The results highlight that prediction accuracies are acceptable for multiple linear regression, accelerated failure time, and random forest models. Disruptions caused by power failures have longer impact durations than other causes, followed by platform screen doors. The fixed block signaling system leads to a larger disruption duration than the moving block system. The study provides, for the first time, a data-driven approach to understanding the duration of the impact of disruptions on passenger trips using smartcard data which can facilitate timely and informed decision-making under unplanned disruptions.",{"EN":168},"Modeling the Duration of the Impact of Unplanned Disruptions on Passenger Trips Using Smartcard Data in Urban Rail Systems",{"VOID":170},"Currie G, Muir C (2017) Understanding passenger perceptions and behaviors during unplanned rail disruptions. Transp Res Procedia 25:4392–4402\nLiu TY, Ma ZL, Koutsopoulos HN (2021) Unplanned disruption analysis in urban railway systems using smart card data. Urban Rail Transit. Urban Rail Transit 7:177–190\nValenti G, Lelli M, Cucina D (2010) A comparative study of models for the incident duration prediction. Eur Transp Res Rev 2:103–111\nOzbay K, Noyan N (2006) Estimation of incident clearance times using Bayesian Networks approach. Accid Anal Prev 38(3):542–555\nNam D, Mannering F (2000) An exploratory hazard-based analysis of highway incident duration. Transp Res A Policy Pract 34(2):85–102\nWei C-H, Lee Y (2007) Sequential forecast of incident duration using artificial neural network models. Accident Analysis Prevention 39(5):944–954\nWeng JX, Zheng Y, Yan XD, Meng Q (2014) Development of a subway operation incident delay model using accelerated failure approaches. Accident Anal Prevent 73:12–19\nWeng JX, Zheng Y, Qu XB, Yan XD (2015) Development of a maximum likelihood regression tree-based model for predicting subway incident delay. Transp Res C 57:30–41\nWang HY, Li LY, Pan PJ, Wang YK, Jin YK (2019) Online detection of abnormal passenger out-flow in urban metro system. Neurocomputing 359:327–340\nLapamonpinyo S, Derrible S, Corman F (2022) Real-time passenger train delay prediction using machine learning: a case study with Amtrak passenger train routes. IEEE Open J Intell Transp Syst 3:539–550\nShi ZB, Zhang N, Zhang YL (2016) Hazard-based model for estimation of congestion duration in urban rail transit considering loss minimization. Transp Res Record J Transp Res Board 2595:78–87\nGu JJ, Jiang ZB, Fan W, Wu JM, Chen JJ (2020) Real-time passenger flow anomaly detection considering typical time series clustered characteristics at metro stations. J Transp Eng A Syst 146(4)\nChen XX, Yang CH, Xu XD, Gong YB (2016) Anomaly detection in metro passenger flow based on random matrix theory. In: IEEE intelligent transportation systems conference (ITSC), Auckland, NZ, pp 525–630\nWang XH, Zhang Y, Liu H, Wang Y, Wang L-CH, Yin BC (2018) An improved robust principal component analysis model for anomalies detection of subway passenger flow. Journal of Adv Transp 2018:12\nMalandri C, Fonzone A, Cats O (2018) Recovery time and propagation effects of passenger transport disruptions. Physica A 505:7–17\nYap M, Cats O (2021) Predicting disruptions and their passenger delay impacts for public transport stops. Transportation 48:1703–1731\nWebb A, Kumar P, Khani A (2020) Estimation of passenger waiting time using automatically collected transit data. Public Transport 12:299–311\nCamponogara E, Nazari LF (2015) Models and algorithms for optimal piecewise-linear function approximation. Math Probl Eng 2015\nZhou XS, Cheng QX, Wu X, Li PH, Belezamo B, Lu JW et al (2022) A meso-to-macro cross-resolution performance approach for connecting polynomial arrival queue model to volume-delay function with inflow demand-to-capacity ratio. Multimodal Transp. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.multra.2022.100017\nChow WK, Qu L, Pang EC (2004) Incidents on fire and ventilation provision in subway systems in Hong Kong. Int J Eng Perform Based Fire Codes 10(3):41–47\nHamad K, Ai-Ruzouq R, Zeiada Dabous SA, Khalil MA (2020) Predicting incident duration using random forests. Transportmetrica A 16(3):1269–1293\n“Historical Weather”. Forecasts|World Weather. https:\u002F\u002Fwww.worldweatheronline.com\u002Fhong-kong-weather.aspx, accessed on 18 Jun 2021.\nMonjo R (2016) Measure of rainfall time structure using the dimensionless n-index. Climate Res 67(1):71–86\nStehman SV (1997) Selecting and interpreting measures of thematic classification accuracy. Remote Sens Environ 62(1):77–89\nWang P, Zhang QP (2019) Train delay analysis and prediction based on bid data fusion. 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         \u003Cjats:p>Under the background of urbanization and the rapid development of urban rail transit (URT), serious attention has been focused on URT network reliability in recent years. In this work, in order to measure network reliability, three indicators are constructed based on passengers’ tolerable travel paths, passenger travel efficiency and passenger travel realization on a URT network. The passenger tolerability coefficient, which is the ratio of passengers’ tolerable travel time to the shortest possible travel time, is proposed and added to the indicators. It reflects passengers’ behavior with respect to choice of travel paths. The ratio of affected passenger volume (RAPV) is proposed to identify important stations. Finally, the connectivity reliability of Wuhan’s subway network is analyzed by simulating attacks on stations. The results show that the degree centrality, betweenness centrality and RAPV indicators of stations can effectively identify the important stations that have a significant impact on the connectivity reliability of the network. In particular, the RAPV indicator effectively identifies stations that have the greatest influence on passenger travel realization. The connectivity reliability of Wuhan’s subway network is sensitive to passenger tolerability coefficient, and reliability is greater during non-peak hours than during peak hours. In addition, the stations that are important to the connectivity reliability of the Wuhan subway have two features, i.e., they are located at the center of the city, and they are important for connecting subgraphs of the network.\u003C\u002Fjats:p>",{"EN":324},"Connectivity Reliability on an Urban Rail Transit Network from the Perspective of Passenger 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V, Marchiori M (2002) Is the Boston subway a small-world network? Physica A 314(1–4):109–113",{"doi":481},"10.1016\u002FS0378-4371(02)01089-0",{"id":20,"text":483,"url":20,"identifiers":484},"Derrible S, Kennedy C (2010) The complexity and robustness of metro networks. Physica A 389(17):3678–3691",{"doi":485},"10.1016\u002Fj.physa.2010.04.008",{"id":20,"text":487,"url":20,"identifiers":488},"Seaton KA, Hackett LM (2004) Stations, trains and small-world networks. Physica A 339(3–4):635–644",{"doi":489},"10.1016\u002Fj.physa.2004.03.019",{"id":20,"text":491,"url":20,"identifiers":492},"Hosseini S, Wadbro E (2016) Connectivity reliability in uncertain networks with stability analysis. Expert Syst Appl 57:337–344",{"doi":493},"10.1016\u002Fj.eswa.2016.03.040",{"id":20,"text":495,"url":20,"identifiers":496},"Zhang YS, Yao EJ (2015) Splitting travel time based on AFC data: estimating walking, waiting, transfer, and in-vehicle travel time in metro system. Discrete Dyn Nat Soc 2015:1–11",{},{"id":20,"text":498,"url":20,"identifiers":499},"Du MQ, Jiang XW, Cheng L et al (2017) Robust evaluation for transportation network capacity under demand uncertainty. J Adv Transp 2017:1–11",{},{"id":20,"text":501,"url":20,"identifiers":502},"Mine H, Kawai H (1982) Mathematics for reliability analysis. Asakura-shorten, Tokyo",{},{"id":20,"text":504,"url":20,"identifiers":505},"Bell MGH, Iida Y (1997) Transportation network analysis. Wiley, Chichester",{"doi":506},"10.1002\u002F9781118903032",{"id":20,"text":508,"url":20,"identifiers":509},"Wakabayashi H, Iida Y (1992) Upper and lower bounds of terminal reliability in road networks: an efficient method with Boolean algebra. J Nat Disaster Sci 14:29–44",{},{"id":20,"text":511,"url":20,"identifiers":512},"Jiang CZ, Xu F, Yuan JX (2013) Characteristics and reliability analysis of the complex network in Guangzhou rail transit. Intell Autom Soft Comput 19(2):217–225",{"doi":513},"10.1080\u002F10798587.2013.787189",{"id":20,"text":515,"url":20,"identifiers":516},"Liu ZQ, Song R (2010) Reliability analysis of Guangzhou rail transit with complex network theory. J Transp Syst Eng Inf Technol 10(5):194–200",{},{"id":20,"text":518,"url":20,"identifiers":519},"Wang ZQ, Xu RH (2009) Reliability simulation analysis of urban rail transit networks based on complex network. J Syst Simul 21(20):6670–6674",{},{"id":20,"text":521,"url":20,"identifiers":522},"Zhang JH, Hong L, Wang SL, et al (2011) Reliability assessments of Chinese highspeed railway network. In: IEEE international conference on intelligent rail transportation, Beijing, China",{"doi":523},"10.1109\u002FSOLI.2011.5986595",{"id":20,"text":525,"url":20,"identifiers":526},"Zhang X, Miller-Hooks E, Denny K (2015) Assessing the role of network topology in transportation network resilience. J Transp Geogr 46:35–45",{"doi":527},"10.1016\u002Fj.jtrangeo.2015.05.006",{"id":20,"text":529,"url":20,"identifiers":530},"Mattsson LG, Jenelius E (2015) Vulnerability and resilience of transport systems – A discussion of recent research. Transp Res Part A 81:16–34",{},{"id":20,"text":532,"url":20,"identifiers":533},"Zhang X, Jia L, Dong H, et al (2009) Analysis and evaluation of connectivity reliability for dynamic transportation network. In: 2009 Fifth international joint conference on INC, IMS and IDC. Seoul, South Korea",{"doi":534},"10.1109\u002FNCM.2009.180",{"id":20,"text":536,"url":20,"identifiers":537},"Liu J, Lu H, Ma H et al (2017) Network vulnerability analysis of rail transit plans in Beijng-Tianjin-Hebei region considering connectivity reliability. Sustainability 9:1479",{"doi":538},"10.3390\u002Fsu9081479",{"id":20,"text":540,"url":20,"identifiers":541},"Guidotti R, Gardoni P, Chen Y (2017) Network reliability analysis with link and nodal weights and auxiliary nodes. Struct Saf 65:12–26",{"doi":542},"10.1016\u002Fj.strusafe.2016.12.001",{"id":20,"text":544,"url":20,"identifiers":545},"Li M, Jia L, Wang Y (2015). Research and implementation on connectivity reliability calculation algorithm of Urban Rail Transit network operation. In: Proceeding of the 11th world congress on intelligent control and automation, Shenyang, China",{},{"id":20,"text":547,"url":20,"identifiers":548},"Reggiani A, Nijkamp P, Lanzi D (2015) Transport resilience and vulnerability: the role of connectivity. Transp Res Part A 81:4–15",{},{"id":20,"text":550,"url":20,"identifiers":551},"Liu J, Xiong Q, Shi W et al (2016) Evaluating the importance of nodes in complex networks. Phys A 452:209–219",{"doi":552},"10.1016\u002Fj.physa.2016.02.049",{"id":20,"text":554,"url":20,"identifiers":555},"Rodriguez-Nunez E, Garcia-Palomares JC (2014) Measuring the vulnerability of public transport networks. J Transp Geogr 35:50–63",{"doi":556},"10.1016\u002Fj.jtrangeo.2014.01.008",{"id":20,"text":558,"url":20,"identifiers":559},"Hu P, Fan W, Mei S (2015) Identifying node importance in complex networks. Phys A 429:169–176",{"doi":560},"10.1016\u002Fj.physa.2015.02.002",{"id":20,"text":562,"url":20,"identifiers":563},"Liu J, Zhou X (2016) Capacitated transit service network design with boundedly rational agents. Transp Res Part B Methodol 3:225–250",{"doi":564},"10.1016\u002Fj.trb.2016.07.015",{"id":20,"text":566,"url":20,"identifiers":567},"Shang P, Li R, Guo J et al (2019) Integrating Lagrangian and Eulerian observations for passenger flow state estimation in an urban rail transit network: a space-time-state hyper network-based assignment approach. Transp Res Part B Methodol 121:35–167",{"doi":568},"10.1016\u002Fj.trb.2018.12.015",{"id":20,"text":570,"url":20,"identifiers":571},"Zhu W, Hu H, Xu R et al (2013) Modified stochastic user-equilibrium assignment algorithm for urban rail transit under network operation. J Cent South Univ 20(10):2897–2904",{"doi":572},"10.1007\u002Fs11771-013-1811-5",{"id":20,"text":574,"url":20,"identifiers":575},"Han B, Zhou W, Li D et al (2015) Dynamic schedule-based assignment model for urban rail transit network with capacity constraints. Sci World J 2015:1–12",{},{"id":20,"text":577,"url":20,"identifiers":578},"Wardman M, Whelan G (2011) Twenty years of rail crowding valuation studies: evidence from lessons from British experience. Transp Rev 31(3):379–398",{"doi":579},"10.1080\u002F01441647.2010.519127",{"id":20,"text":581,"url":20,"identifiers":582},"Zhang Y, D’Ariano A, He B, Peng Q (2019) Microscopic optimization model and algorithm for integrating train timetabling and track maintenance task scheduling. Transp Res Part B Methodol 127:237–278",{"doi":583},"10.1016\u002Fj.trb.2019.07.010",{"id":20,"text":585,"url":20,"identifiers":586},"Zhang Y, Peng Q, Yao Y, Zhang X, Zhou X (2019) Solving cyclic train timetabling problem through model reformulation: extended time-space network construct and alternating direction method of multipliers methods. Transp Res Part B Methodol 128:344–379",{"doi":587},"10.1016\u002Fj.trb.2019.08.001",{"id":20,"text":589,"url":20,"identifiers":590},"Zhong Q, Lusby RM, Larsen J, Zhang Y, Peng Q (2019) Rolling stock scheduling with maintenance requirements at the Chinese high-speed railway. Transp Res Part B Methodol 126:24–44",{"doi":591},"10.1016\u002Fj.trb.2019.05.013",{"id":593,"createTime":594,"updateTime":595,"relativeEntities":596,"slug":597,"properties":598,"entityType":173,"verifyStatus":174,"verifyTime":595,"verifyNote":175,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":607,"fullTextUrl":20,"authors":608,"publicationType":237,"publisherRelationship":637,"citationCount":20,"citationInfo":20,"publishDate":705,"publishYear":706,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":707,"openAccess":20,"references":20,"isForceReanalyzing":309},"478d9312-ba15-4bef-b46b-3b3dfb31b545","2023-12-21T08:35:12.514+00:00","2025-02-25T12:48:07.123+00:00",[],"Innovative-Interior-Designs-for-Urban-Freight-Distribution-Using-Light-Rail-Systems",{"abstract":599,"title":601,"references":603,"doi":605},{"EN":600},"High levels of pollution and congestion in urban centres are an increasing concern for local councils in the UK. Heavy goods vehicles delivering urban freight to city centres are a leading cause of this problem. This paper discusses the concept of using light rail networks to deliver freight to city centres from surrounding businesses. Specifically, various innovative designs are considered for the interior of the metro carriage and developed into visual models using Autodesk Inventor software. A full evaluation of all the designs developed is completed, resulting in a proposed design for consideration. The conclusion reached is that the proposed interior design is viable and coincides with the future metro fleet designs and concepts.",{"EN":602},"Innovative Interior Designs for Urban Freight Distribution Using Light Rail Systems",{"VOID":604},"Independent Transport Commision: Improving the Efficiency of Freight Movements: the Contribution to UK Economic Growth. London (2014)\nDepartment for Transport: Domestic Road Freight Statistics, United Kingdom 2015, UK (2016)\nBBC News: UK Pollution, how bad is it? (2014) (online Blog). http:\u002F\u002Fwww.bbc.co.uk\u002Fnews\u002Fuk-26851399. Accessed 13 Feb 2017\nCrainic, T.G., Ricciardi, N., Storchi, G.: Models for Evaluating and Planning City Logistics Systems. CIRRELT (2009)\nAirqualitynews.com: Pollution from HGVs ‘Costs Europe Nearly £40 Billion (2013) (online). http:\u002F\u002Fwww.airqualitynews.com\u002F2013\u002F02\u002F28\u002Fpollution-from-hgvs-costs-europe-nearly-40-billion. Accessed 14 Mar 2017\nCenex-Atkins: Low Carbon Truck and Refuelling Infrastructure Demonstration Trial Evaluation—First Annual Report to the DfT Executive Summary for publication, UK (2014)\nEuropean Commission: A Call to Action on Urban Logistics. Brussels (2013)\nTaniguchi E, Thompson RG, Yamada T (2014) Recent trends and innovations in modelling city logistics. Proc. Soc. Behav. Sci. 125:4–14\nDiziain D, Taniguchi E, Dablanc L (2014) Urban logistics by rail and waterways in France and Japan. Soc. Behav. Sci. 125:159–170\nDampier A, Marinov M (2015) A Study of the Feasibility and Potential Implementation of Metro-Based Freight Transportation in Newcastle upon Tyne. Springer, Newcastle Upon Tyne\nWallace School of Transport: What is the Difference Between LGV Training and HGV Training? (2016) (online). http:\u002F\u002Fwww.wallaceschool.co.uk\u002Fblog\u002FHGV_or_LGV. Accessed 14 Feb 2017\nHMRC: Department for Transport, Licensed Heavy Goods Vehicles, by Region: Great Britain and United Kingdom (2016) (online). https:\u002F\u002Fwww.gov.uk\u002Fgovernment\u002Fstatistical-data-sets\u002Fveh05-licensed-heavy-goods-vehicles. Accessed 12 Apr 2017\nHMRC: Moving goods by road (2016) (online). https:\u002F\u002Fwww.gov.uk\u002Fguidance\u002Fmoving-goods-by-road. Accessed 09 Apr 2017\nCampaign for Better Transport: Air Pollution Matters (online). http:\u002F\u002Fwww.bettertransport.org.uk\u002Fair-pollution-matters. Accessed 10 Apr 2017\nCrainic TG, Ricciardi N, Storchi G (2004) Advanced freight transportation systems for congested urban areas. Transp. Res. Part C 12:119–137\nTransport for London: Electric Vehicles (2016) (online). https:\u002F\u002Ftfl.gov.uk\u002Fmodes\u002Fdriving\u002Felectric-vehicles. Accessed 16 Apr 2017\nDutch Amsterdam: Amsterdam to Get Freight Trams (2007) (online). http:\u002F\u002Fwww.dutchamsterdam.nl\u002F207-207. Accessed 16 Feb 2017\nShen, J., Qiu, F., Li, W., Feng, P.: A new urban logistics transport system based on a public transit service. In: CICTP, pp. 651–661 (2015)\nDepartment for Transport: The Pathway to Driverless Cars: A Detailed Review of Regulations for Automated Vehicle Technologies, UK (2015)\nFlickr: Tyne and Wear Metro (2013) (online). https:\u002F\u002Fwww.flickr.com\u002Fphotos\u002Femdjt42\u002F10870475016. Accessed 16 Feb 2017\nMonash University: An Innovative Approach to Metropolitan Train Carriage Interior Configuration—To Improve Boarding, Alighting, Dwell Time, Stability and Passenger Experience, Melbourne (2013)\n123 Royalty Free: London Underground (2017) (online). https:\u002F\u002Fwww.123rf.com\u002Fphoto_18402815_interior-from-london-underground-train.html. Accessed 13 Feb 2017\nCoxon, S., Burns, K., de Bono, A, Napper, R.: An Examination of Three Approaches to Metro Rolling Stock Design to Ameliorate Extended Dwell Times Due to Passenger Growth and Associated Crowding. Institute of Transport Studies, Monash University (2011)\nNexus: Metro Strategy 2030 (2014) (online). http:\u002F\u002Fwww.nexus.org.uk\u002Fsites\u002Fdefault\u002Ffiles\u002FMetro%20Strategy%202030%20summary%20document.pdf. Accessed 19 Apr 2017\nWikiwand: Tyne and Wear Metro Rolling Stock (online Blog). http:\u002F\u002Fwww.wikiwand.com\u002Fen\u002FTyne_and_Wear_Metro_rolling_stock. Accessed 17 Feb 2017\nMarinov, M., Toal, J.: A Study by Product Design into the Potential for a Check-In and Bag Drop. Newcastle upon Tyne (2016)\nRailway-technology.com: Tyne and Wear Metro, UK (online). http:\u002F\u002Fwww.railway-technology.com\u002Fprojects\u002Ftyne\u002F. Accessed 19 Apr 2017\nMarcle Leisure: Seat Bed Mechanism for Motor Homes and Caravans (online). http:\u002F\u002Fwww.marcle-leisure.co.uk\u002Finformation\u002Frock-n-roll-hinges.htm. Accessed 20 Mar 2017\nRockwell Collins: B\u002FE Aerospace (2016) (online). http:\u002F\u002Fbeaerospace.com\u002F. Accessed 02 Mar 2017\nTelegraph, T.: Legroom Wars: The Seat to Change it All (2017) (online). http:\u002F\u002Fwww.telegraph.co.uk\u002Ftravel\u002Fnews\u002FLegroom-wars-the-seat-to-change-it-all\u002F. Accessed 02 Mar 2017\nHow Stuff Works: How RFID Works (2017) (online). http:\u002F\u002Felectronics.howstuffworks.com\u002Fgadgets\u002Fhigh-tech-gadgets\u002Frfid.htm. Accessed 08 Apr 2017\nMotion Controls Robotics: Automatic Guided Carts (AGCs)—End-of-Line Automation—Integrated Material Handling Systems (online). http:\u002F\u002Fmotioncontrolsrobotics.com\u002Frobotic-applications\u002Fautomated-material-handling\u002Fautomatic-guided-carts-agc\u002F. Accessed 08 Mar 2017\nTechnovelgy.com: What is RFID? (online). http:\u002F\u002Fwww.technovelgy.com\u002Fct\u002Ftechnology-article.asp. Accessed 06 Apr 2017\nBrowning R, Parker E, Herron J, Kram R (2006) Effects of obesity and sex on the energetic cost and preferred speed of walking. J. Appl. Physiol. 100:390–398\nThe Journal: Bakery giant Greggs opens doors on £16.5 m site (2011) (online). http:\u002F\u002Fwww.thejournal.co.uk\u002Fbusiness\u002Fbusiness-news\u002Fbakery-giant-greggs-opens-doors-4417628. Accessed 25 Feb 2017\nTraffic Technology International: Autonomous Vehicle Safety Regulation World Congress 2017 (2017) (online). http:\u002F\u002Fwww.autonomousregulationscongress.com\u002F. Accessed 14 Apr 2017\nFrevue: Freight Electric Vehicles in Urban Europe (2016) (online). http:\u002F\u002Ffrevue.eu. Accessed 16 Feb 2017\nMaes, J.; Vanelslander, T.: The Use of Urban Rail Transport as Part of the Supply Chain in an Urban Logistics Context, Lisbon (2010)\nBrice D, Marinov M, Rüger B (2015) A newly designed baggage transfer system implemented using event-based simulations. Urban Rail Transit 1(4):194–214\nMarinov M, Giubilei F, Gerhardt M, Özkan T, Stergiou E, Papadopol M, Cabecinha L (2013) Urban freight movement by rail. J Transp Lit 7(3):87–116",{"VOID":606},"10.1007\u002Fs40864-017-0073-1","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40864-017-0073-1",[609,624],{"id":610,"sortIndex":21,"researcher":20,"roles":611,"affiliations":612,"properties":621,"displayName":623,"givenName":20,"familyName":20},"844cb5db-ee5a-4e28-8d1d-6b0506a569e5",[181],[613],{"id":614,"sortIndex":21,"affiliation":615,"properties":20},"6b2a16ef-c2f5-4092-85cb-8a64594c3aa8",{"id":614,"createTime":20,"updateTime":20,"relativeEntities":616,"slug":20,"properties":617,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":620,"statistic":20},[],{"title":618},{"VI":619},"NewRail, Mechanical and Systems Engineering School, Newcastle University, Newcastle upon Tyne, UK",[],{"title":622},{"VI":623},"James 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is home to the biggest light rail network and the industry is currently undergoing a renaissance. However, there is little\nresearch to indicate the extent to which well-informed human factors and ergonomics practises are being incorporated into tram cab design. A lack of standardised features may create transfer conflicts between cabs, as well as operational issues and concerns for occupational health. The aim of this paper is to improve our understanding of the socio-technical complexity of light rail and to enhance how design standards are informed in this domain. Various human factors methods were used, including observational cab rides, objective force assessments, interviews, and focus groups. Data were collected across two sites and analysed thematically. Analysis of data suggested a substandard level human factors and ergonomics input in the design of the cab and driver interface that violated many key tenets of established design guidelines. These were particularly concerned with the usability of the master controller (i.e. throttle lever) and various issues in the design of the tram driver workspace. Findings also revealed a number of subtle yet significant features associated with delivery of service that created safety-performance conflicts. In conclusion, very little human factors input of tram driving, and the ergonomics considerations of the driver’s workplace in general, appear to be going into the design of tram cabs. This may be related to the practice of using non-specific standards for developing trams and\u002For poorly integrating human factors and ergonomics into their specification processes. Some considerations for future work are given.",{"EN":718},"A Streetcar Undesired: Investigating Ergonomics and Human Factors Issues in the Driver–cab Interface of Australian Trams",{"VOID":720},"Currie G, Burke M (2013) Light rail in Australia—performance and prospects. Paper presented at the Australasian Transport Research Forum, Brisbane, Australia\nAustralasian Railway Association (2015) Capital metro: Canberra’s light rail project in a global context. Author, Canberra\nNye B (2015) Light rail in Australasia: the economic, social and environmental case. In: Proceedings of 2015 light rail conference, NSW, AU March 5–6 2015\nMacdonald A, Coxon S (2011) Towards a more accessible tram system in Melbourne—challenges for infrastructure design. Paper presented at the Australasian Transport Research Forum, Adelaide, Australia\nAlstom Transport (2011) What will your Citadis be? Author. http:\u002F\u002Fwww.alstom.com\u002Ftransport\u002Fproducts-and-services\u002Ftrains\u002Ftramway-citadis\u002F\nGood Design Australia (2014) Good design awards 2014. Crowther Blayne, Surfers Paradise\nCarey A (2012,) Tram cop a low blow as report slams design flaws. The Age (July 14)\nWickens CD, Hollands JG (2000) Engineering psychology and human performance, 3rd edn. Prentice-Hall, Upper Saddle River\nMitra B, Al Jubair J, Cameron PA, Gabbe BJ (2010) Tram-related trauma in Melbourne, Victoria. Emerg Med Australas 22(4):337–342. doi:10.1111\u002Fj.1742-6723.2010.01309.x\nMiddendorp C (2010) Hop on tram for on hell of a scary ride. The Sydney Morning Herald, December 23\nUnion Internationale des Chemins der fer (2009) Driver machine interfaces for EMU\u002FDMU, locomotives and driving coaches—functional and system requirements associated with harmonised Driver Machine Interfaces. Author, Paris, France\nWoods D, Hollnagel E (2006) Joint cognitive systems: patterns in cognitive systems engineering. Taylor & Francis, Boca Raton\nGould JD, Lewis C (1985) Designing for usability: key principles and what designers think. Commun ACM 28(3):300–311\nNorman D (1988) The design of everyday things. Basic Books, New York\nPreece J, Rogers Y, Sharp H (2002) Interaction design: beyond human-computer interaction. Wiley, New York\nFoot R, Doniol-Shaw G (2008) Questions raised on the design of the “dead-man” device installed on trams. Cogn Technol Work 10(1):41–51\nCooke NJ (1994) Varieties of knowledge elicitation techniques. Int J Hum Comput Stud 41(6):801–849\nNaweed A (2014) Investigations into the skills of modern and traditional train driving. Appl Ergon 45(3):462–470. doi:10.1016\u002Fj.apergo.2013.06.006\nNaweed A, Balakrishnan G, Bearman C, Dorrian J, Dawson D (2012) Scaling generative scaffolds towards train driving expertise. In: Contemporary ergonomics and human factors 2012, pp 235–236\nNaweed A (2013) Psychological factors for driver distraction and inattention in the Australian and New Zealand rail industry. Acc Anal Prev 60:193–204. doi:10.1016\u002Fj.aap.2013.08.022\nHuberman MA, Miles MB (1994) Data management and analysis methods. In: Denzin NK, Lincoln YS (eds) Handbook of qualitative research. Sage, Thousand Oaks, pp 209–219\nCharmaz K (2006) Constructing grounded theory: a practical guide through qualitative analysis. SAGE Publications Ltd, London\nNaweed A, Rainbird S, Dance C (2015) Are you fit to continue? Approaching rail systems thinking at the cusp of safety and the apex of performance. Saf Sci. doi:10.1016\u002Fj.ssci.2015.1002.1016\nNaweed A, Balakrishnan G, Bearman C, Dorrian J, Dawson D (2012) Scaling generative scaffolds towards train driving expertise. In: Anderson M (ed) Contemporary ergonomics and human factors 2012: proceedings of the international conference on ergonomics & human factors 2012. CRC Press, Blackpool, p 235–236\nPowell C (2003) The Delphi technique: myths and realities. J Adv Nurs 41(4):376–382\nHsu CC (2007) The Delphi technique: making sense of consensus. Pract Assess Res Eval 12(10):1\nEdworthy J, Hellier E, Noyes J, Aldrich K, Naweed A, Metcalfe GR (2008) Good practice guide for the design of alarms and alerts. Rail Safety Standards Board, London\nBranton P (1979) Investigations into the skills of train-driving. Ergonomics 22(2):155–164\nCœugnet S, Naveteur J, Antoine P, Anceaux F (2013) Time pressure and driving: work, emotions and risks. Transp Res Part F 20:39–51. doi:10.1016\u002Fj.trf.2013.05.002\nMoD (2000) Human factors integration: an introductory guide. HMSO, London\nBisantz A, Roth (2008) Analysis of cognitive work. In: Boehm-Davis DA (ed) Reviews of human factors and ergonomics. Human Factors and Ergonomics Society, Santa Monica, pp 1–43",{"VOID":722},"10.1007\u002Fs40864-015-0021-x","2025-02-25T06:24:14.978+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40864-015-0021-x",[726,741],{"id":727,"sortIndex":21,"researcher":20,"roles":728,"affiliations":729,"properties":738,"displayName":740,"givenName":20,"familyName":20},"82d032bd-3a36-4614-8b48-cfa7e1bc8ad9",[181],[730],{"id":731,"sortIndex":21,"affiliation":732,"properties":20},"5b8a5180-bc76-45bf-ae1e-ec0eb1df8182",{"id":731,"createTime":20,"updateTime":20,"relativeEntities":733,"slug":20,"properties":734,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":737,"statistic":20},[],{"title":735},{"VI":736},"Appleton Institute for Behavioural Science, Central Queensland University, Wayville, Australia",[],{"title":739},{"VI":740},"Anjum 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global trend for rail automation is increasing but there are very few publications on public perception of the ongoing changes in the railways. In order to fill this gap and to better understand people’s perception of driverless trains, the paper focuses on automation of metro systems with a particular interest in unattended train operation (UTO). A survey seeking a public opinion on UTO was conducted, and the results show that 93 % of female and 72 % of male respondents think that a “fake” driver room should be present on a driverless train. In terms of human error, a great majority of respondents expressed no worries about a train design or maintenance issues. However, staff communication, selected by 36 % males and 43 % females, and a technical failure, highlighted by 50 % of males and 43 % of females, were two issues that raised most safety concerns amongst the respondents. Other results related to passenger’s safety, employment, advantages and limitations of the UTO, amongst other issues, are presented and discussed in the paper.",{"EN":836},"Public Perception of Driverless Trains",{"VOID":838},"BBC (2014) Driverless tube trains: Unions vow ‘war’ over plan. http:\u002F\u002Fwww.bbc.co.uk\u002Fnews\u002Fuk-england-london-26381175. Accessed 9 Dec 2014\nBerwell FT (1973) Automatic railways: automation and control in transport. Pergamon Press, Oxford, pp 177–191\nBrown P (2014) Are driverless trains the future? Rail Technology Magazine, February\u002FMarch 2014, p 19\nFisher E (2011) Justifying automation. In: Railway technology. http:\u002F\u002Fwww.railway-technology.com. Accessed 5 Dec 2014\nFraszczyk A, Magalhães da Silva J, Gwóźdź A, Vasileva G (2014) Metro as an example of an urban rail system. Four case studies from Europe. Transp Probl 9:101–107\nHasham N (2013) Driverless trains plan must overcome public scepticism. http:\u002F\u002Fwww.smh.com.au\u002Fnsw\u002Fdriverless-trains-plan-must-overcome-public-scepticism-20130607-2nvjq.html. Accessed 9 Dec 2014\nKarvonen H, Aaltonen I, Wahlström M, Salo L, Savioja P, Norros L (2011) Hidden roles of the train driver: a challenge for metro automation. Interact Comput 23:289–298\nMalla R (2014) Automation sets a new benchmark. Metro report, May 2014\nRumsey A (2009) Communications based train control. IRSE seminar\nTransLink (2014) SkyTrain. http:\u002F\u002Fwww.translink.ca\u002Fen\u002FSchedules-and-Maps\u002FSkyTrain.aspx. Accessed 9 Dec 2014\nUIC (2014) Automatic train control. Energy efficiency technologies for railways. http:\u002F\u002Fwww.railway-energy.org\u002Fstatic\u002FAutomatic_train_control_79.php. Accessed 9 Dec 2014\nUITP (2011) Media backgrounder. Metro automation facts, figures and trends. UITP, Brussels\nUITP (2013) Metro automation in 2013. Observatory of Automated Metros World Atlas Report. UITP, Brussels\nUITP (2014) Statistics brief. World metro figure. UITP, Brussels\nVuchic V (2014) Maintaining performance with full automation. Metro report international, March 2014, pp 36–39",{"VOID":840},"10.1007\u002Fs40864-015-0019-4","2025-02-25T03:43:34.003+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40864-015-0019-4",[844,859,872],{"id":845,"sortIndex":21,"researcher":20,"roles":846,"affiliations":847,"properties":856,"displayName":858,"givenName":20,"familyName":20},"cddeb5a9-1069-4f53-8c74-d7899637a53b",[181],[848],{"id":849,"sortIndex":21,"affiliation":850,"properties":20},"4065abf8-e22e-4b02-ad9a-fc717cf70831",{"id":849,"createTime":20,"updateTime":20,"relativeEntities":851,"slug":20,"properties":852,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":855,"statistic":20},[],{"title":853},{"VI":854},"NewRail, Newcastle University, Newcastle upon Tyne, UK",[],{"title":857},{"VI":858},"Anna 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increasing environmental concerns, light rail transit (LRT) has drawn attention for consideration in urban transportation planning by various levels of authorities in the US Government. Advocacy groups need an effective method for viability assessment of the alternatives. Environmentalists may want to support LRT, but assessment of its viability is important to provide judgment of any future transportation project . This paper presents a method for LRT viability assessment through a case study of the “Oasis Line,” as part of the Eastern Corridor Major Investment Study (MIS) by the Ohio Kentucky and Indiana Council of Governments (OKI). The study attempts to evaluate chances for “success” of the rail transit component of the MIS. An integrated method is used with a traditional four-step-based demand forecast by OKI, and a development of station-based Light Rail Ridership Regression demand forecast by Pelz. The problem to be solved—whether the line has a good enough chance at success to support and advocate for it—did not demand a full rerunning of the models. A review of appropriate literature—largely assessments of already-built light rail lines in other US cities—is used to characterize the predicted ridership as a success or failure. The predicted ridership falls comfortably above the low end of LRT systems in other US cities. The ridership predictions are found favorable to support the Oasis Line. Extensive literature review suggested that the public’s assessments behave in an almost entirely political fashion.",{"EN":964},"Viability Assessment of Light Rail Line Planning: Case Study of Cincinnati Eastern Corridor",{"VOID":966},"Wikipedia (2017) “Rail transportation in the United States.” Available at https:\u002F\u002Fen.wikipedia.org\u002Fwiki\u002FRail_transportation_in_the_United_States. Accessed 9 March 2017\nBureau of Economic Analysis (BEA) (2017) National data. Accessible at https:\u002F\u002Fwww.bea.gov\u002Fregional\u002Findex.htm. Accessed 9 March 2017\nHickman L (2016) “The rising demand for public transport in the US”. Accessible at http:\u002F\u002Fblog.marketresearch.com\u002Fthe-rising-demand-for-public-transport-in-the-us. Accessed 9 March 2017\nAmerican Public Transportation Association (APTA) (2017) Public transportation fact book. Accessible at http:\u002F\u002Fwww.apta.com\u002Fresources\u002Fstatistics\u002FPages\u002Ftransitstats.aspx. Accessed 7 March 2017\nBrown JR, Neog D (2008) “Urban structure and transit ridership: a reexamination of the relationship in the United States.” In: Compendium of papers CD-ROM, 87th transportation research board annual meeting, January 13–17, 2008, in Washington, DC\nFederal Highway Administration (FHWA) (2005) Traffic congestion and reliability: trends and advanced strategies for congestion mitigation. Available at http:\u002F\u002Fwww.ops.fhwa.dot.gov\u002F congestion_report\u002Findex.htm\nPages ER, Lombardozzi B, Woolsey L (2016) The emerging U.S. rail industry: opportunities to support American manufacturing and spur regional development. Available at https:\u002F\u002Fwww.nist.gov\u002Fsites\u002Fdefault\u002Ffiles\u002Fdocuments\u002Fmep\u002FRail-Report.pdf. Accessed 9 March 2017\nSchrank D, Lomax T (2007) The 2007 urban mobility report. Available at http:\u002F\u002Fmobility.tamu.edu\u002F\nWeisbrod G, Fitzroy S (2008) “Defining the range of urban congestion impacts on freight and their consequences for business activity.” In: compendium of papers cd-rom, 87th transportation research board annual meeting, 13–17 Jan 2008, in Washington, DC\nEastern Corridor Program (ECP) (2017) “Oasis rail transit overview.” Available at http:\u002F\u002Feasterncorridor.org\u002Fprojects\u002Foasis-rail-transit\u002Foasis-rail-transit-project-overview\u002F. Accessed 9 March 2017\nOhio, Kentucky, and Indiana Council of Governments (OKI) (1999) 1999—eastern corridor major investment study (MIS). Available at http:\u002F\u002Fwww.easterncorridor.org. Accessed 30 May 2008\nOhio, Kentucky, and Indiana Council of Governments (OKI) (2005) Eastern corridor tier one draft EIS. Available at http:\u002F\u002Fwww.easterncorridor.org. Accessed 29 May 2008\nSierra Club (2008) “Stop sprawl.” Available at www.sierraclub.org\u002Fsprawl. Accessed 8 June 2008\nMcKinley SA (2008) A feasibility analysis of hamilton county’s proposed oasis light rail line through traditional and advanced demand forecasting vs. best practices. In: Course project report for CEE605 travel demand forecasting offered at University of Cincinnati, Spring Quarter, 2008\nPelz ZL (2007) A station level analysis of competing light rail alternatives in cincinnati’s eastern corridor. Master’s thesis in community planning approved by the University of Cincinnati, June 2007, University of Cincinnati: Cincinnati\nAmerican Public Transit Association (APTA) (2008) Light rail agency ridership for Q1 2008. Available at www.apta.com\u002Fresearch\u002Fstats\u002Frail\u002Flrmiles.cfm. Accessed 1 June 2008\nHoffman K (2000) “It’s a smooth ride in mile high city,” Houston Chronicle June 6, 2000. Available at http:\u002F\u002Fbicycleaustin.info\u002Frail\u002FHouston-chronicle-06-06-00.html. Accessed 9 June 2008\nKuby M, Barranda A, Upchurch CD (2004) Factors influencing light-rail station boardings in the United States. Transp Res Part A 38:223–247\nLight Rail Now (LRN) (2017) “Light rail now! light rail progress.” Available at www.lightrailnow.org. Accessed 3 June 2008; re-accessed 20 Jan 2017\nUpchurch CD (2005) A spatial decision support system for predicting light-rail transit ridership in phoenix. Master’s thesis approved by Arizona State University, September 2005\nWeyrich PM, William OSL (1999) “Does transit work? A conservative reappraisal.” Available at http:\u002F\u002Fwww.apta.com\u002Fresearch\u002Finfo\u002Fonline\u002Fweyrich2new2.cfm. Accessed 9 June 2008\nPortune T (2008) April 10, 2008 interview by Author, with other members of Sierra Club\nSiemens AG (2008) Light rail system references (Internet database). Available at http:\u002F\u002Freferences.transportation.siemens.com\u002Frefdb\nOrtuzar JdD, Willumsen LG (2001) Modelling Transport Third Edition 2001. Wiley, Chichester\nOhio, Kentucky, and Indiana Council of Governments (OKI) (2008) DRAFT 2030 OKI regional transportation plan update. Available at http:\u002F\u002Fwww.oki.org. Accessed 9 May 2008\nHDR (2016) OASIS rail conceptual alternative solutions HAM\u002FCLE—OASIS rail corridor. In: PID No. 86463 final report for Ohio Department of Transportation. 8 Feb 2016",{"VOID":968},"10.1007\u002Fs40864-017-0059-z","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40864-017-0059-z",[971,986],{"id":972,"sortIndex":21,"researcher":20,"roles":973,"affiliations":974,"properties":983,"displayName":985,"givenName":20,"familyName":20},"b57d50ac-9f8b-4008-bf43-c2d100624e44",[181],[975],{"id":976,"sortIndex":21,"affiliation":977,"properties":20},"df1daae1-0800-45f7-8d31-51a9f467219f",{"id":976,"createTime":20,"updateTime":20,"relativeEntities":978,"slug":20,"properties":979,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":982,"statistic":20},[],{"title":980},{"VI":981},"Price Hill Will, Cincinnati Area, USA",[],{"title":984},{"VI":985},"Samuel A. 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research assesses the appreciation in residential property values in connection with proximity to the Little Miami Scenic Trail, a multi-purpose biking, hiking, and jogging trail built along an abandoned railroad corridor near Cincinnati, Ohio, USA. Applying two spatial hedonic frameworks, the spatial lag of X (SLX) model and the spatial Durbin error model, we conclude that proximity to trail entrances had significant impacts on property values for both, Euclidean and network distance measures. Specifically, the SLX results indicate that decreasing the distance to the closest trail entrance by one foot (meter) increases a house’s property value by US$0.92 (US$3.02) when using network distances.",{"EN":1098},"Transforming Abandoned Rail Corridors into Multi-purpose Trails: Applying a Spatial Hedonic Approach to Estimating the Economic Benefits of the Little Miami Scenic Trail in Cincinnati, Ohio, USA",{"VOID":1100},"Rails-to-Trails Conservancy (n.d.) What is a rail-trail? https:\u002F\u002Fwww.railstotrails.org\u002Fbuild-trails\u002Ftrail-building-toolbox\u002Fbasics\u002Ftrail-building-basics\u002F. Accessed 22 Oct 2018\nRovelli R, Senes G, Fumagalli N (2004) Ferrovie dismesse e greenways: Il recupero delle linee ferroviarie dismesse per la realizzazione di percorsi verdi. Associazione Italiana Greenways, Milan, p 132\nQuattrone M, Tomaselli G, Demilio A, Russo P (2018) Analysis and evaluation of abandoned railways aimed at greenway conversion: a methodological application in the Sicilian landscape using multi-criteria analysis and GIS. J Agric Eng. https:\u002F\u002Fdoi.org\u002F10.4081\u002Fjae.2018.744\nChina, Beijing Tourism Development Commission, Industrial Development Promotion Office (2015) Study of general planning & pilot schemes for recreational trail systems in Beijing. http:\u002F\u002Flyw.beijing.gov.cn\u002Fxxgk\u002Fghjh\u002F373221.htm. Accessed 22 Oct 2018\nYu Q, Lin S, Mo W (2013) The development and management of national scenic trails for America: take appalachian national scenic trail for example. Urban Plan Int 28(4):108–114\nDing H, He J, Liu J (2017) A China–America comparative study of Beijing pedestrian system planning. Planners 2:98–103\nXu D, Guo J, Gao L (2014) The planning & construction strategy and management & maintenance mechanism of American greenway. Urban Plan Int 29(3):83–90\nQin X, Wei M (2013) The comparative study on the Chinese greenway and the American greenway. Chin Landsc Archit 4:119–124\nParent O, vom Hofe R (2013) Understanding the impact of trails on residential property values in the presence of spatial dependence. Ann Reg Sci 51:355–375. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00168-012-0543-z\nRail-Trail History (n.d.) https:\u002F\u002Fwww.traillink.com\u002Ftrail-history\u002Flittle-miami-scenic-trail\u002F. Retrieved 15 Oct 2018\nSorens J (2013) Public policy and quality of life: an empirical analysis of interstate migration, 2000–2012. SSRN Elec J. http:\u002F\u002Fdx.doi.org\u002F10.2139\u002Fssrn.2298744\nGlaeser EL, Kolko J, Saiz A (2001) Consumer city. J Econ Geogr 1(1):27–50. https:\u002F\u002Fdoi.org\u002F10.1093\u002Fjeg\u002F1.1.27\nLancaster KJ (1966) A new approach to consumer theory. J Polit Econ 74(2):132–157\nRosen S (1974) Hedonic prices and implicit markets: product differentiation in pure competition. J Polit Econ 82(1):34–55\nLi H, Wei YD, Yu Z, Tian G (2016) Amenity, accessibility and housing values in metropolitan USA: a study of Salt Lake County, Utah. Cities 59:113–125. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.cities.2016.07.001\nNilsson P (2014) Natural amenities in urban space: a geographically weighted regression approach. Landsc Urban Plan 121:45–54. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.landurbplan.2013.08.017\nSaphores JD, Li W (2012) Estimating the value of urban green areas: a hedonic pricing analysis of the single family housing market in Los Angeles, CA. Landsc Urban Plan 104:373–387. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.landurbplan.2011.11.012\nBrasington D, Haurin DR (2006) Educational outcomes and house values: a test of the value added approach. J Reg Sci 46(2):245–268\nLa V (2015) Capitalization of school quality into housing prices: evidence from Boston Public School district walk zones. Econ Lett 134:102–106. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.econlet.2015.07.001\nHess DB, Almeida TM (2007) Impact of proximity to light rail rapid transit on station-area property values in Buffalo, New York. Urban Stud 44(5–6):1041–1068. https:\u002F\u002Fdoi.org\u002F10.1080\u002F00420980701256005\nMartinez LM, Viegas JM (2009) Effects of transportation accessibility on residential property values hedonic price model in the Lisbon, Portugal, metropolitan area. Transp Res Rec 2115:127–137\nDv Dijk, Rosi S, Brouwer R, Logar I, Sanadgol D (2016) Valuing water resources in Switzerland using a hedonic price model. Water Resour Res 52:3510–3526. https:\u002F\u002Fdoi.org\u002F10.1002\u002F2015WR017534\nWen H, Xiao Y, Zhang L (2017) Spatial effect of river landscape on housing price: an empirical study on the Grand Canal in Hangzhou, China. Habitat Int 63:34–44. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.habitatint.2017.03.007\nKim S, Lee KO (2018) Potential crime risk and housing market responses. J Urban Econ 108:1–17. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jue.2018.09.001\nPope JC (2008) Fear of crime and housing prices: household reactions to sex offender registries. J Urban Econ 64:601–614. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jue.2008.07.001\nHanninger K, Ma L, Timmings C (2017) The value of brownfield remediation. J Assoc Environ Resour Econ 4(1):197–241\nMihaescu O, vom Hofe R (2012) The impact of brownfields on residential property values in Cincinnati, Ohio: a spatial hedonic approach. 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Reg Sci Urban Econ 36(6):773–789. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.regsciurbeco.2006.03.007\nKong F, Yin H, Nakagoshi N (2007) Using GIS and landscape metrics in the hedonic price modeling of the amenity value of urban green space: a case study in Jinan City, China. Landsc Urban Plan 79(3–4):240–252. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.landurbplan.2006.02.013\nEspey M, Owusu-Edusei K (2001) Neighborhood parks and residential property values in Greenville, South Carolina. J Agric Appl Econ 33(3):487–492. https:\u002F\u002Fdoi.org\u002F10.1017\u002FS1074070800020952\nShultz SD, King DA (2001) The use of census data for hedonic price estimates of open-space amenities and land use. J Real Estate Finance Econ 22(2–3):239–252\nAsabere PK, Huffman FE (2009) The relative impacts of trails and greenbelts on home price. 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Accessed 28 Oct 2018",{"VOID":1102},"10.1007\u002Fs40864-018-0094-4","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40864-018-0094-4",[1105,1120,1133],{"id":1106,"sortIndex":21,"researcher":20,"roles":1107,"affiliations":1108,"properties":1117,"displayName":1119,"givenName":20,"familyName":20},"a96a8714-d977-4708-8f8b-7a9874aed9ec",[181],[1109],{"id":1110,"sortIndex":21,"affiliation":1111,"properties":20},"86166d0c-cd1f-43ad-8367-8b44348ff30a",{"id":1110,"createTime":20,"updateTime":20,"relativeEntities":1112,"slug":20,"properties":1113,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1116,"statistic":20},[],{"title":1114},{"EN":1115},"School of Planning, University of Cincinnati, Cincinnati, USA",[],{"title":1118},{"VI":1119},"Wen Zhang",{"id":1121,"sortIndex":193,"researcher":20,"roles":1122,"affiliations":1123,"properties":1130,"displayName":1132,"givenName":20,"familyName":20},"c7cc935b-1c8d-44ae-b7a1-2439b1974236",[181],[1124],{"id":1110,"sortIndex":21,"affiliation":1125,"properties":20},{"id":1110,"createTime":20,"updateTime":20,"relativeEntities":1126,"slug":20,"properties":1127,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1129,"statistic":20},[],{"title":1128},{"EN":1115},[],{"title":1131},{"VI":1132},"Seunghoon 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transportation planning is a continuous, multi-phase, functioning scale that is based on reconstructing the spatial system, thus contributing to build a more quality-focused, long-term-oriented and balanced approach. This paper presents cartographic modelling and multi-criteria analysis (CMCA) for the optimum route\u002Fstation location in accordance with selected criteria and constraints for rail transit system planning. The methodology is based on overlay analysis (cartographic modelling) to combine diverse criteria maps and the  analytic hierarchy process (AHP) method for criteria weighting. The purpose of the study is to examine a GIS multiple-criteria decision-making (MCDM) framework by considering Stream, Geology, Slope, Land use and Population decision criteria. The decision modelling framework conceives an additional prominent approach by co-producing with the public, especially for underserved areas of low socio-economic status and public user expectations in the railway transport planning process. This model applied to a candidate metro line referred to as M 18 (Başakşehir-Esenyurt-Beylikdüzü) with eight railway stations for the preliminary stage evaluation. The outcomes of this research will close the gap by establishing a novel suitability framework which can be used as a preliminary analysis for transforming and developing urban rail transit networks.",{"EN":1227},"Cartographic Modelling and Multi-Criteria Analysis (CMCA) for Rail Transit Suitability",{"VOID":1229},"Johansson E, Anund A, Koglin T (2019) Appraisal of a regional public transport project: a document and interview analysis on a light rail case in Sweden. Case Stud Transp Policy. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.cstp.2019.04.007\nTudela A, Akiki N, Cisternas R (2006) Comparing the output of cost benefit and multi-criteria analysis: an application to urban transport investments. Transp Res Part A: Policy Pract 40(5):414–423. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.tra.2005.08.002\nMalczewski J (2010) Multiple Criteria Decision Analysis and Geographic Information Systems. Trends in Multiple Criteria Decision Analysis, International Series in Operations Research and Management Science Chapter 13:369–395. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-1-4419-5904-1_13\nMalczewski J, Jankowski P (2020) Emerging trends and research frontiers in spatial multicriteria analysis. Int J Geogr Inf Sci 34(7):1257–1282. https:\u002F\u002Fdoi.org\u002F10.1080\u002F13658816.2020.1712403\nYannis G, Kopsacheili A, Dragomanovits A, Petraki V (2020) State-of-the-art review on multi-criteria decision-making in the transport sector. J Traffic Transp Eng 7(4):413–431. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jtte.2020.05.005\nBroniewicz E, Ogrodnik K (2020) Multi-criteria analysis of transport infrastructure projects. Transp Res Part D. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.trd.2020.102351\nKırlangıçoğlu C (2016) Urban Railway Corridor Planning Based on Multi Criteria Decision Making Techniques. https:\u002F\u002Fwww.researchgate.net\u002Fpublication\u002F312200077_Cok_Kriterli_Karar_Verme_Yontemleri_ile_Kent_Ici_Rayli_Sistem_Koridor_Planlamasi_Urban_Railway_Corridor_Planning_Based_on_Multi_Criteria_Decision_Making_Techniques. Accessed 15 Dec 2019\nYücel N (2019) The selection of railway system projects with multi criteria decision making methods: a case study for Istanbul. In: 3rd World conference on technology, ınnovation and entrepreneurship (WOCTINE) Procedia Computer Science, Vol 158, pp 382–393\nGamper CD, Turcanu C (2007) On the governmental use of multi-criteria analysis. Ecol Econ 62:298–307. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ecolecon.2007.01.010\nAhmed CH (2016) GIS and genetic algorithm based ıntegrated optimization for rail transit system planning. Dissertation, Centre for Transport Studies Department of Civil and Environmental Engineering\nParry JA, Ganaie SA, Bhat MS (2018) GIS based land suitability analysis using AHP model for urban services planning in Srinagar and Jammu urban centers of J&K, India. J Urban Manag 7:46–56. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jum.2018.05.002\nÖzkan B, Özceylan E, Sarıçiçek İ (2019) GIS-based MCDM modeling for landfill site suitability analysis: A comprehensive review of the literature. Environ Sci Pollut Res 26:30711–30730. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11356-019-06298-1\nAhmed C, Nur K, Ochieng W (2020) GIS and genetic algorithm based integrated optimization for rail transit system planning. J Rail Transp Plan Manag 16:100222. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.jrtpm.2020.100222\nTischler S (2017) Finding the right way—a new approach for route selection procedures?. Transp Res Procedia 25:2809-2823. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.trpro.2017.05.247\nGiuffrida N, Le Pira M, Inturri G, Ignaccolo M (2019) Mapping with stakeholders: an overview of public participatory GIS and VGI in transport decision-making. Int J Geo-Inf 8:198. https:\u002F\u002Fdoi.org\u002F10.3390\u002Fijgi8040198\nQuick KS (2014) Public Participation in Transportation Planning. In Encyclopedia of Transportation: Social Science and Policy, edited by Mark Garrett, pp 1132-37. Thousand Oaks, CA: Sage Publications. University of Minnesota. https:\u002F\u002Fwww.researchgate.net\u002Fpublication\u002F264956681_Public_Participation_in_Transportation_Planning. Accessed 20 Feb 2021\nIstanbul Transport Annual Report (2016) https:\u002F\u002Ftuhim.ibb.gov.tr\u002Fmedia\u002F2131\u002Fimm_transport_report.pdf. Accessed 10 Dec 2020\nIstanbul Metropolitan Municipality’s Directorate of Earthquake and Ground Research (2018) Understanding Social Vulnerability Against Disasters Survey Results in Istanbul\nThe Ministry of Industry and Technology (2019) ‘Measuring Urbanization Level in Turkish Districts by Population Density and Urban Functions’ national study report in Turkey. https:\u002F\u002Fwww.mevka.org.tr\u002FYukleme\u002FUploads\u002FDsyMU6cBf913201941250PM.pdf. Accessed 5 Jan 2021\nDogru A, Goksel C, David RM, Tolunay D, Sözen S, Orhon D (2020) Detrimental environmental impact of large scale land use through deforestation and deterioration of carbon balance in Istanbul Northern Forest Area. Environ Earth Sci 79:270. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12665-020-08996-3\nPacheco-Raguz JF (2010) Assessing the impacts of Light Rail Transit on urban land in Manila. J Transp Landuse. https:\u002F\u002Fdoi.org\u002F10.5198\u002Fjtlu.v3il.13\nKarlson M, Karlsson CSJ, Mörtberg U, Olofsson B, Balfors B (2016) Design and evaluation of railway corridors based on spatial ecological and geological criteria. Transp Res Part 46: 207–228\nIstanbul Metropolitan Municipality’s Directorate of Eartquake and Geotechnical Investigation (2020) Istanbul Geological Map (1\u002F100 000) (jpeg).\nIstanbul Metropolitan Municipality’s Directorate of Geographic Information Systems (2020) Digital Topographical maps for Istanbul, Land use Map for Istanbul\nMalczewski J (2000) On the use of weighted linear combination method in GIS: common and best practice approaches. Trans GIS 4(1):5–22\nIstanbul Metropolitan Municipality (2021) Transport and Mobility Report",{"VOID":1231},"10.1007\u002Fs40864-023-00186-1","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs40864-023-00186-1",[1234,1249],{"id":1235,"sortIndex":21,"researcher":20,"roles":1236,"affiliations":1237,"properties":1246,"displayName":1248,"givenName":20,"familyName":20},"f0c57896-45df-48a2-8d54-31439ee66882",[181],[1238],{"id":1239,"sortIndex":21,"affiliation":1240,"properties":20},"0cfb944c-c9d6-476d-b8e5-386fb1cb5bfc",{"id":1239,"createTime":20,"updateTime":20,"relativeEntities":1241,"slug":20,"properties":1242,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1245,"statistic":20},[],{"title":1243},{"VI":1244},"Department of Civil Engineering, Transportation Engineering, Istanbul Technical University, Ayazağa Campus, Istanbul, Turkey",[],{"title":1247},{"VI":1248},"Berna 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the background of the rapid development of urban rail transit in China, the development demand of urban underground space has also greatly increased especially in the rail transit station areas. In this paper, taking the high-speed railway station area of Xuzhou Metro Line 1 as an example, the underground space development demand evaluation is conducted by considering the principle of urban underground space stock planning, the local underground space development conditions, as well as the special planning of the local urban constructions. Using the Analytic Hierarchy Process (AHP), a specific weight indicator scale is employed after the rationality of different weight indicator scales being compared. And then the weight indicator of different function types, i.e., commercial, parking, road, etc., are calculated and laterly utilized to forecast the recent development demand of underground space in the station area. Moreover, the steps to forecast the underground space development demand in rail transit station area are proposed, which can provide a reference for the forecasting of underground space development demand in the urban rail transit station areas.",{"EN":1341},"Research on Quantitative Demand of Underground Space Development for Urban Rail Transit Station Areas: A Case Study of Metro Line 1 in Xuzhou, China",{"VOID":1343},"Li H, Li X, Soh CK (2016) An integrated strategy for sustainable development of the urban underground: from strategic, economic and societal aspects. Tunn Undergr Space Technol 55:67–82. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.tust.2015.12.011\nBobylev N (2009) Mainstreaming sustainable development into a city’s Master plan: a case of urban underground space use. Land Use Policy 26(4):1128–1137. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.landusepol.2009.02.003\nLi XZ, Xu H, Li C et al (2016) Study on the demand and driving factors of urban underground space use. Tunn Undergr Space Technol 55:52–58. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.tust.2016.02.010\nZhao Y, Wu K (2016) Quantitative evaluation of the potential of underground space resources in urban central areas based on multiple factors: a case study of Xicheng district, Beijing. Proc Eng 165:610–621. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.proeng.2016.11.757\nXia FZ, Shen Y, Yan J et al (2016) On the potential of urban three-dimensional space development: the case of Liuzhou, China. Habitat Int 51:48–58. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.habitatint.2015\nHe L, Song Y, Dai S et al (2012) Quantitative research on the capacity of urban underground space–the case of Shanghai, China. Tunn Undergr Space Technol 32:168–179. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.tust.2012.06.008\nWang XM (2011) Underground space utilization and development of a Nanjing metro transfer station. Urban Rapid Rail Transit 24(1):11–14. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1672-6073.2011.01.003 (in Chinese)\nChen SZ, Yuan MZ, Lei HM (2011) Practice and experience of the underground space development of Guangzhou rail transit. Urban Rapid Rail Transit 24(1):5–10. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1672-6073.2011.01.002 (in Chinese)\nSong MH, Feng AJ, Wang XJ (2005) Promote underground space development through urban rail transit. Urban Rapid Rail Transit 18(1):21–25. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1672-6073.2005.01.006 (in Chinese)\nXiao HP, Shi PP, Bai YC (2016) Study on the large-scale development of underground spaces of rail transit. Urban Rapid Rail Transit 29(6):16–19. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1672-6073.2016.06.004 (in Chinese)\nGuo C, Wang LJ (2007) Improving the public space environment around the stations on Beijing urban rail way Line 13. Urban Rapid Rail Transit 20(1):68–71. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1672-6073.2007.01.020 (in Chinese)\nNie HB, Wang M (2015) “Subway + Property” in line with urban land use planning. Urban Rapid Rail Transit 28(2):41–44. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1672-6073.2015.02.010 (in Chinese)\nChen ZL, Zhang P, Wang YB (2006) Discussion on forecast method of underground space demand in urban central area. In China urban planning annual conference proceedings, p 618–621 (in Chinese)\nDong PL (2006) The scale prediction of urban underground space development demand. Shanghai Constr Sci Technol 2:35–38. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1005-6637.2006.02.011 (in Chinese)\nChen ZL, Wang YB, Liu H et al (2007) Prediction of underground space needs. Planners 23(10):9–13. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1006-0022.2007.10.002 (in Chinese)\nGou CF, Ye F, Zhang JL (2012) Demand forecasting and demand distributional system development method of urban underground space. J Chang’an Univ (Nat Sci Ed) 32(5):58–64. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1006-0022.2007.10.002 (in Chinese)\nCao Y, Feng YJ (2013) Exploration on demand model of urban underground space in view of linkage method. Chin J Undergr Space Eng 9(6):1215–1222 (in Chinese)\nZhao JW, Wang P, Wang J et al (2015) Underground space development of key districts: Sino-German Eco-park underground space regulatory planning, Qingdao. Planners 8:54–59 (in Chinese)\nZou L, Hu YJ, Chen ZF et al (2017) Underground space plan of small and medium-sized city based on demand oriented. Chin J Undergr Space Eng 13(1):7–13 (in Chinese)\nGu Q, Li XZ, Sun LP et al (2017) Comparison and analysis of multiple demand forecasting methods for urban underground space. J PLA Univ Sci Technol (Nat Sci Ed). https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.undsp.2016.08.002\nYin M, Rui Y, Zhu HH et al (2010) Comprehensive evaluation for underground demonstration project. Chin J Undergr Space Eng 6(2):219–223. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1673-0836.2010.02.001\nZhou YH, Maumbe K, Deng J et al (2015) Resource-based destination competitiveness evaluation using a hybrid analytic hierarchy process (AHP): the case study of West Virginia. Tour Manag Perspect 15:72–80. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.tmp.2015.03.007\nSingh RP, Nachtnebel HP (2016) Analytical hierarchy process (AHP) application for reinforcement of hydropower strategy in Nepal. Renew Sustain Energy Rev 55:43–58. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.rser.2015.10.138\nDu D (2001) Study on 0.1–0.9 scale in AHP. Syst Eng Electr 23(5):36–38. https:\u002F\u002Fdoi.org\u002F10.3321\u002Fj.issn:1001-506x.2001.05.012 (in Chinese)\nLu YJ, Zhang W, Zeng XL (2003) Exponential scale not being consistent with l-9 scale. J Eng Math 20(8):77–81 (in Chinese)\nXiong L, Liang L, Wang GH (2005) Method research on selection and valuation of numeric scale in analytic hierarchy process. Syst Eng Theory Pract 25(3):72–79. https:\u002F\u002Fdoi.org\u002F10.3321\u002Fj.issn:1000-6788.2005.03.011 (in Chinese)\nSun DS, Zhu Y, Zhou SX (2010) Application of exponential scale of AHP in bridge evaluation. J Chongqing Jiaotong Univ (Nat Sci) 29(6):867–870 (in Chinese)\nDong S, Wang YJ, Liu L (2011) Research on methods for improving consistency of judgement matrix based on exponential scale. Comput Technol Autom 30(4):1–4. https:\u002F\u002Fdoi.org\u002F10.3969\u002Fj.issn.1003-6199.2011.04.001 (in Chinese)\nYan MH, Yao XP, Zhang JF (2014) Determining weight coefficients of meteorological service evaluation criteria with AHP. J Appl Meteorol Sci 25(4):470–475",{"VOID":1345},"10.1007\u002Fs40864-018-0091-7","https:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs40864-018-0091-7",[1348,1363,1378,1393,1406],{"id":1349,"sortIndex":21,"researcher":20,"roles":1350,"affiliations":1351,"properties":1360,"displayName":1362,"givenName":20,"familyName":20},"0f934215-53ca-4790-aad7-cbe313f3f098",[181],[1352],{"id":1353,"sortIndex":21,"affiliation":1354,"properties":20},"0ae61993-0804-482b-a3d9-e81bb798f09e",{"id":1353,"createTime":20,"updateTime":20,"relativeEntities":1355,"slug":20,"properties":1356,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1359,"statistic":20},[],{"title":1357},{"VI":1358},"School of Civil Engineering, Beijing Jiaotong University, Beijing, China",[],{"title":1361},{"VI":1362},"Liming Wu",{"id":1364,"sortIndex":193,"researcher":20,"roles":1365,"affiliations":1366,"properties":1375,"displayName":1377,"givenName":20,"familyName":20},"585565fb-e2bd-4e29-a790-6d811d20a84b",[181],[1367],{"id":1368,"sortIndex":21,"affiliation":1369,"properties":20},"c0ad9715-9f0f-4596-b295-9eb680892a98",{"id":1368,"createTime":20,"updateTime":20,"relativeEntities":1370,"slug":20,"properties":1371,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1374,"statistic":20},[],{"title":1372},{"VI":1373},"School of Architecture and Design, Beijing Jiaotong University, Beijing, China",[],{"title":1376},{"VI":1377},"Haishan Xia",{"id":1379,"sortIndex":223,"researcher":20,"roles":1380,"affiliations":1381,"properties":1390,"displayName":1392,"givenName":20,"familyName":20},"0a835ba4-053a-486c-a11a-4b6bdfc6451e",[181],[1382],{"id":1383,"sortIndex":21,"affiliation":1384,"properties":20},"d59ba44c-e316-49ee-9b2d-e5acdbad54c4",{"id":1383,"createTime":20,"updateTime":20,"relativeEntities":1385,"slug":20,"properties":1386,"entityType":20,"verifyStatus":20,"verifyTime":20,"verifyNote":20,"languages":20,"translateLanguages":20,"viewCount":20,"url":20,"parentIds":1389,"statistic":20},[],{"title":1387},{"VI":1388},"Department of Engineering and Construction, Xuzhou Urban Rail Transit Co. 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the acceleration and deceleration of trains within a railway network can improve the performance of the system. However, the risk of passengers losing their balance and falling is also increased. The purpose of this paper is therefore to examine the effect of longitudinal vehicle accelerations on passenger safety and comfort. The literature review brings together two separate disciplinary areas, considering the effects of acceleration on balance from a physiological\u002Fkinesiological perspective, as well as looking at the results of previous empirical studies on the levels of acceleration that railway passengers will tolerate. The paper also describes an experiment carried out on the Tyne and Wear Metro, which gathered data on typical acceleration levels to compare against the findings of the literature review. It was found that both the magnitude of the accelerations and their rate of change (jerk) are important. The results also suggest that there may be scope to improve the trade-off between journey times, energy consumption and passenger comfort by fine control of the acceleration\u002Fjerk profile. This is particularly relevant to urban rail systems, as they typically feature relatively high acceleration and deceleration. However, the findings for passenger comfort are equally applicable to conventional regional and intercity services.",{"EN":1498},"Passenger Stability Within Moving Railway Vehicles: Limits on Maximum Longitudinal Acceleration",{"VOID":1500},"Abernethy CN, Jacobs HH, Plank GR, Stoklosa JH, Sussman ED (1980) Maximum deceleration and jerk levels that allow retention of unrestrained, seated transit passengers. Transp Res Rec 774:45–51\nAllum JHJ (1983) Organization of stabilizing reflex responses in tibialis anterior muscles following ankle flexion perturbations of standing man. 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John Wiley & Sons, Hoboken\nWatkins J (1983) An introduction to mechanics of human movement. Boston, [Mass.]; Lancaster: MTP Press\nZigmond MJ (1999) Fundamental neuroscience. 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