We examine the effect of weather, accessibility and built-environment characteristics on overall travel experience as well as the experience with the latest trips. These are factors that are often disregarded in the travel satisfaction literature even though they are believed to largely influence the first mile of the door-to-door trip. This study fills a research gap in investigating all these factors by using, amongst other, a relatively large travel satisfaction survey from years 2009 to 2015 and by focusing on urban and peri-urban geographical contexts, the city and county of Stockholm (Sweden), respectively. The ordered logit model results show that county dwellers living close to a metro station and in well linked-to-all areas report higher overall travel satisfaction evaluations. In addition, precipitation and ground covered with snow have a negative influence on travel satisfaction. Our findings indicate that built-environment characteristics exert a rather weak influence on the travel experience, especially in the peri-urban context. However, some aspects such as living in areas with medium densities, low income and with high safety perceptions around public transport stations are associated with higher satisfaction levels. In turn, areas with single land uses are found to have lower travel satisfactions. These results are important for public transport planners and designers in devising measures to prevent and mitigate the negative outcome of some weather conditions and to conceive better designed transit oriented developments.
With climate change, weather has emerged as an important theme in transport research and planning. Although recent studies demonstrate profound weather effects on mobility in single case study areas, international cross-comparisons are required to reveal how effects differ between cities with different transport and climate regimes. This paper provides an international cross-comparison of the simultaneous effects of weather on destination choices, distances, trip chaining, and transport modes in the urban regions of Utrecht (Netherlands), Oslo and Stavanger (Norway), and Stockholm (Sweden). Hereto, regional subsamples of national travel survey data were linked to meteorological records for the three respective countries and analysed in generalised Structural Equation Models. Our findings generally indicate that light, calm, dry and warm atmospheric conditions may positively affect cycling and the selection of outdoor leisure destinations, while cold and to a lesser extent wet and windy weather conditions reduce cycling and enhance car use and travel optimising strategies like trip chaining, to reduce weather exposures. A positive effect of air temperature on cycling flattens out above 20–25 °C in most of our study areas, but hot weather does not seem to reduce cycling strongly. However, our findings also show considerable regional differences in the effects of weather on mobility. Both general effects and differences are interpreted in relation to geographical context, transport and land use, climate conditions, cultures, habits and adaptations and are discussed to formulate policies to mitigate active transport mode users’ exposures to adverse weather and make walking and cycling (even more) year-round modes.
Sweden has been a front runner in vertical separation. We use data from the business long-distance corridor in Sweden to calibrate and define a demand and supply model. We simulate how the profit, welfare, fares, frequencies, modal shares and train size depend on the level of the track charges. We simulate the welfare optimal track charges, given different levels of congestion on the track, hence using the charges as a pricing instrument to allocate the train slots efficiently. We find that increases in charges have a limited impact on fares but larger impacts on the frequency. When the length of the trains can be extended and when the crowding penalty is high, the impact of higher track charges on the frequencies is larger. Higher track charges increase the length of the trains if possible. The intermodal competition from road and air has a significant impact on rail fares. © 2021 The Authors
Under senare år har cykeln lyfts fram som ett transportmedel med många positiva egenskaper och i nationella strategidokument har det uttryckts en önskan om att cyklingen ska öka. Samtidigt poängteras att säkerheten för cyklister måste bli bättre så att en ökad cykling inte leder till fler skadade och omkomna cyklister. För att klara av att öka cyklandet utan att försämra säkerheten, behövs underlag för att fatta beslut om vilka åtgärder som behöver genomföras. Bland annat behövs bättre kunskap om sambandet mellan cykelflöde och skaderisk i olika trafikmiljöer.
I syfte att studera hur sättet att använda cykeln förändras över tid och hur cyklisters skaderisk påverkas av cykelflöde och trafikmiljön, har tre olika delstudier genomförts i det här projektet. I den första delstudien har en modell utvecklats som innehåller både färdmedelsval och destinationsval för cykel. I den andra delstudien har modeller för skaderisker hos cyklister utvecklats för olika olyckstyper och trafikmiljöer. I den tredje delstudien har interaktioner mellan olika trafikanter observerats, i syfte att studera hur dessa påverkas av nivån på cykelflödet. Sammantaget visar studierna i projektet att cykelflödet har betydelse för cyklisters olycksrisk. Högre flöden ger färre interaktioner per cyklist och lägre risk att skadas i såväl singelolyckor som kollision med motorfordon. Vi har också kunnat visa att det är möjligt att modellera färdmedels- och destinationsval för cykel såväl som att med hjälp av modeller beskriva effekter på cyklisters skaderisk. För att kunna göra bättre skattningar som mer rättvist beskriver verkligheten behövs dock ett bättre dataunderlag till modellerna, framförallt när det gäller cykelresor och beskrivning av cykelinfrastrukturen.
Trafikmodeller för cykeltrafik saknas till stor del vilket försvårar planering av effektiv, säker och attraktiv cykelinfrastruktur. Syftet med denna förstudie är att identifiera forsknings- och utvecklings-behov i Sverige inom området cykeltrafikmodellering, för att på så sätt vägleda framtida satsningar inom området. Förstudien har genomförts i två etapper: behovsanalys och sammanställning av kunskapsläge och forskningsbehov kring mikroskopiska och makroskopiska trafikmodeller. För att undersöka behov av modellstöd samt identifiera forsknings- och utvecklingsbehov i Sverige genomfördes dels intervjuer med konsulter verksamma inom området, dels en workshop med representanter från kommuner, regioner och Trafikverket. För att sammanställa kunskapsläget kring cykeltrafikmodeller har en litteraturstudie genomförts. Behovsanalysen i kombination med sammanställningen av kunskapsläget visar på att det finns ett tydligt behov av fortsatt forsknings- och utvecklingsarbete av makroskopiska och mikroskopiska cykeltrafikmodeller. Centralt för utveckling och tillämpning av båda modelltyperna är tillgången till data. För makroskopiska trafikmodeller finns ett långsiktigt behov av utveckling av efterfrågemodeller som inkluderar cyklister samt av ruttvals-modeller. När det gäller mikroskopiska cykeltrafikmodeller bör den långsiktiga utvecklingen inriktas mot vidareutveckling av antingen bilinspirerade eller kraftinspirerade modeller, alternativ nya modellansatser om så behövs.
The aim of the CoEXist project is to enable local road authorities and other urban mobility stakeholders to assess the impact of the introduction of connected and automated vehicles (CAVs). To achieve this, the PTV traffic modelling software Visum and Vissim are extended to handle traffic with various mixes of different types of CAVs. Also, a structured assessment approach is developed to analyse modelling results from Visum and Vissim which can be used by road authorities to assess the traffic impact of automation fora given road design, traffic control, regulations, etc.. This model-based assessment approach is tested and demonstrated by applying it to eight use cases in four European cities on both macro and micro levels. The conclusions of these assessments are briefly summarized in this deliverable and design recommendations for the studied infrastructures are provided.
Den långsiktiga nationella infrastrukturplaneringen behöver beakta hur investerings- och underhålls-åtgärder planeras både utifrån projektens genomförbarhet och trafikens påverkan, men det saknas idag kvantitativa metoder som kan ge ett sådant stöd i banarbetsplaneringen. Forskningsprojektet SATT (Samplanering av trafikpåverkande åtgärder och trafikflöden, modellstudie) har syftat till att ta fram en metod för att kunna optimera den långsiktiga schemaläggningen av större banarbeten utifrån såväl projektens genomförbarhet som trafikens framkomlighet. Som grund för detta har en översikt av förutsättningarna för den långsiktiga banarbetsplaneringen genomförts tillsammans med en litteraturstudie av vilka angreppssätt som förekommer i forskningslitteraturen. I samarbete med Trafikverket har sedan funktionella krav och behov inventerats och analyserats, med fokus på den ekonomiska planering som görs för ett specifikt produktionsår. Denna delrapport dokumenterar resultaten från litteraturstudien samt krav- och behovsanalysen.
Intercity travel congestion during the main national holidays takes place every year at different places around the world. Charge reduction measurements on existing toll roads have been implemented to promote an efficient use of the expressways and to reduce congestion on the public transit networks. However, some of these policies have had negative effects. A more comprehensive understanding of the determinants of holiday intercity travel patterns is critical for better policymaking. This paper aims to investigate the effectiveness of the road toll discount policy on mode choice behavior for intercity travel. A mixed logit model is developed to model the mode choices of intercity travelers, which is estimated based on survey data about intercity journeys from Beijing during the 2017 Chinese Spring Festival holiday. The policy impact is further discussed by elasticity and scenario simulations. The results indicate that the expressway toll discount does increase the car use and decrease the public transit usage. Given the decreased toll on expressways, the demand tends to shift from car to public transit, in an order of coach, high-speed rail, conventional rail, and airplane. When it comes to its effect on socio-demographic groups, men and lower-income travelers are identified to be more likely to change mode in response to variation of road toll. Finally, policy effectiveness is found to vary for travelers in different travel distance groups. Conclusions provide useful insights on road pricing management.
I forskningsprojektet SATT (Samplanering av trafikpåverkande åtgärder och trafikflöden, modellstudie) har en dynamisk trafiktilldelningsmetod (Dynamic Traffic Assignment, DTA) anpassats för att kunna simulera järnvägstrafik. Detta erbjuder ett alternativ till tidtabellsplanering. Till skillnad från flödesoptimering, simulerar DTA tågrörelser med en hög detaljeringsgrad (ner på sekundnivå) men kan ändå hantera stora trafikmängder med en rimlig beräkningstid. Metoden strävar däremot inte efter ett systemoptimum utan söker efter en jämviktslösning där inget enskilt tåg kan hitta alternativa vägar som förbättrar dess restid eller generaliserade kostnad. Denna jämviktslösning brukar benämnas som dynamisk användarjämvikt.
Denna rapport redovisar ett förslag på hur transportsimuleringsplattformen MATSim kan anpassas och användas för att göra dynamisk trafiktilldelning för järnvägstrafik, utan något krav på en känd tidtabell. Anpassningen inkluderar simulering av tågtrafik på enkelspårs-sträckor, hantering av tillfälliga kapacitetsreduktioner (motsvarande så kallade trafikpåverkande åtgärder, TPÅ), och olika tågtyper. Metoden har testats och utvärderats med hjälp av två små exempelfall. Resultaten visar att modellen ger realistisk hantering av tågtrafiken och dess förmåga att finna en rimlig tågplan baserat på en enkel värderingsfunktion. Fortsatt arbete bör inriktas på förfining av modellen och applicering på ett storskaligt nationellt nätverk.
The AV-ready tools developed within the CoEXist project will be used to test the automation-readiness of eight diverse use cases in four different cities. For five of the use cases a microscopic traffic model is applied and for three use cases a macroscopic traffic modelling approach is used. Applying traffic models for a specific use case commonly follow a process that include the following steps:
The aim of this report is to present the development of the baseline traffic models that will be run to investigate each use case. The purposes of the description of baseline microscopic and macroscopic models are:
China has recently initialised affordable housing policies to provide low rent housings for medium and low income households aiming to satisfy the growing demand in the housing market. The travel behaviour of residents in these two different types of housing is likely to differ, since public housing tenants have a limited choice of residential location, as the location of low-rent housing is fixed, while residents in commodity housing are able to take their travel patterns into account in choosing their housing location. Therefore, this paper investigates the differences in car ownership and trip chaining behaviour arising from living in different types of residential housing. The self-selection bias caused by the differences in the observed individual and household characteristics is partially controlled by a propensity score matching approach. The study further considers the endogenous effect of car ownership on travel chaining behaviour, thus controlling for the self-selection bias at car ownership level. The results show that residents in private commodity housing are more likely to own a car than those in low-rent housing with similar individual and household characteristics. Different life cycle stages play a vital role in car ownership after self-selection in residential housing has been taken into account. Living in private commodity housing has a direct negative effect on trip chaining complexity, after controlling for endogenous car ownership, although this effect is offset by the tendency for private commodity housing owners to do complex trip chaining because they have one or more cars.
The activity space of an individual is defined as the activity-travel environment which a traveller is using for his or her activities. It is limited by this individual's ability and resources, such as available time for travel as well as his or her anchor points. However, most existing studies have focused on single individual activity space, ignoring the fact that individuals’ activities often interact with that of his or her family members’. In this paper a multivariate model is proposed where the correlation between travel time of fathers and mothers, and the correlation between the activity space and travel time are modelled explicitly. The estimated correlations from these joint distributions provide insights into both the intra-household interactions in daily travel and the intrinsic relationships of the hidden limits in the dimensions of space and time. The travel time limits are modelled using a stochastic frontier model component, which can estimate an unobserved upper or lower limit for travel time expenditure. This limit usually refers to the maximum travel time budget or minimum travel time need, which denotes the maximum or minimum amount of travel time that an individual is willing or able to allocate per day. The concept of the confidence ellipse is used as a measure of activity space constructed from the multi-day travel diary data. It is hypothesised that the unobserved travel time limits and activity space sizes of fathers and mothers are correlated with each other, due to a similar spatial knowledge and accessibility to various facilities. The daily variations in the travel time expenditure of parents are also assumed to be correlated because of daily household task allocation and joint household travel. Data collected from a three-week household travel diary in the Bandung Metropolitan Area in Indonesia are used for estimation in this study. The estimated frontier model component shows that neither parent has reached their maximum travel time budget and/or minimum travel time need that they inherently must spend. Compared with other attributes, the perceived accessibility attributes play the most important role in influencing the activity space limits. For households with fully employed fathers, a trade-off mechanism is found in travel time expenditure between parents, which is likely due to the redistribution of household tasks. On the other hand, for households with fathers who are not fully employed, a complementary effect is found, arising from the joint travel among household members. The travel time budget and activity space limits of fathers are positively correlated with those of mothers. These findings call for the formulation of transport policies that consider the household as a unit, especially in developing countries such as Indonesia, to fulfil the mobility needs of different market segments, e.g., households with fully employed fathers and those with fathers who are not fully employed.
In this study, a nested multivariate Tobit model is proposed to model activity and travel time use jointly. This proposed model can handle: (1) The corner solution problem; (2) time allocation trade-offs among different types of activities; and (3) travel being treated as a derived demand of activity participation. The model is applied to the Swedish national travel survey (NTS). Evidence of the potential positive utility of travel time added on non-work activity time allocation in the Swedish case is also found. The proposed model is compared to an MDCEV model specification. The results show clear differences in marginal effect estimates. In terms of prediction, the nested multivariate Tobit model shows a slightly worse performance on the hit rate measure than the MDCEV model combined with a stochastic frontier model, but shows a slightly better performance on the SMAPE measure.
Given that severe weather conditions are becoming more frequent, it is important to understand the influence of weather on an individual’s daily activity-travel pattern. While some previously rare events are becoming more common, such as heavy rain, unpredicted snow, higher temperatures, it is still largely unknown how individuals will change and adapt their travel patterns in future climate conditions. Because of this concern, the number of research studies on weather and travel behaviour has increased in recent decades. Most of these empirical studies, however, have not used a cost–benefit analysis (CBA) framework, which serves as the the main tool for policy evaluation and project selection by stakeholders. This study summarises the existing findings regarding relationships between weather variability and travel behaviour, and critically assesses the methodological issues in these studies. Several further research directions are suggested to bridge the gap between empirical evidence and current practices in CBA.
Weather is fundamentally a perception rather than an objective measure. This study uses data from a four-wave travel diary survey and aims to answer two research questions, i.e. 1. How individuals from different socio-demographic groups perceive weather. 2. How an individual's weather perception affects his/her leisure activity participation decision. A thermal indicator, Universal Thermal Climate Index (UTCI) is used as a synthetic index that represents the thermal environment. Panel static/dynamic ordered Probit model is used to model leisure activity participation. The results show that the reference thermal environment, in general, corresponds to the historical mean of the thermal environment. Moreover, the effect of subjective weather perception on leisure activity participation is non-linear and asymmetric. Only 'very disappointed weather' and 'very satisfied weather' significantly influence leisure activity participation. The intra-individual heterogeneity in the effect of 'very good weather' has a smaller magnitude than that of 'very bad weather'.
This study presents a transport model to better model cycling demand. The model improves modelling of cycling in several ways compared to a conventional transport model. First, it uses a detailed bicycle network containing information about existing bicycle infrastructure. Second, generalised cost measures based on different bicycle route choice models are calculated and compared to evaluate how to best represent the impact of bicycle infrastructure in the model. Third, the model utilizes a refined zone system with smaller zones of size 250 m × 250 m. Using these smaller zones, more short-distance tours are included in the model, and these are predominantly walking and cycling trips. Fourth, the model considers cycling also as an access mode choice to public transport. Therefore, the model treats cycling and public transport as both competing and complementary modes. Results show that the model captures detailed individual heterogeneity in cycling demand for different trip purposes. Impacts of bicycle infrastructure, land use characteristics and individual/household socio-demographics are investigated. Detailed individual level travel time and generalised cost are derived for cyclists of different socio-demographics. The result highlights the importance of choosing a good measure of generalised cost, given that different bicycle route choice models result in different effects of bicycle infrastructure. In future applications, the model can be used to evaluate proposed bicycle investments regarding their impact on link flow, bicycle route choice, modal shift and generation of completely new tours. The model can also be a powerful tool in a cost-benefit analysis of bicycle investments.
Cost-benefit analysis (CBA) for cycling infrastructure investments are less sophistically developed compared to the ones for private cars and public transport, and one of main reasons is the lack of “well-developed” transport models for cycling. In this study, a dedicated transport model for cycling is used to appraise cycling infrastructure investments in Stockholm, Sweden. The model captures the impact of a change in cycling infrastructure on cycling route choice, mode choice, destination choice and trip generation and calculates cycling flow on link level. the generalised cost measure defined in the route choice model captures the impact of cycling infrastructure. Results suggest that although cycling flow on the links with investment may increase substantially, only a small share comes from modal shift and thus the external effects such as reducing car congestion and emissions are marginal. For all three scenarios investigated, over 97% of the benefits measured in the unit of generalised cost belong to the existing cyclists. The route choice model does not minimize travel time but generalised cost which also measures health, safety benefits and other possible benefits that may be considered by the cyclists when they choose to cycle. In fact, travel time saving benefits of the investments evaluated in this paper are all negative. The existing effect evaluation models therefore need to be adjusted to be more consistent with the transport model.
Ökad andel resor med hållbara färdmedel är en förutsättning för att kombinera fortsatt tillväxt med minskad resursförbrukning och miljöpåverkan. I många europeiska städer har cykel blivit ett alltmer populärt färdmedel under de senaste decennierna. Dagens storskaliga transportmodeller, som utgör viktiga verktyg för utvärderingar och samhällsekonomiska analyser, är dock oftast fokuserade på modellering av resor med bil eller kollektivtrafik. Den här rapporten presenterar en tur-baserad transportmodell med syfte att bättre modellera cykelresor. Nyheterna i denna modell är bland annat ett detaljerat cykelnät som innehåller mer än 200 000 länkar och att modellen nyttjar en mer detaljerad zonindelning. Jämfört med nuvarande verktyget för samhällsekonomisk analys av cykelåtgärder, GCkalk, beskriver modellen ett fullständigt utbud och efterfrågan för cykel på detaljerad geografisk nivå. Modellen har skattats på data från den senaste resvaneundersökningen i Stockholms län från 2015 och representerar därmed observerat resebeteende. Modellen beaktar även cykel som anslutningsfärdmedel till resor med kollektivtrafik. Därigenom behandlar modellen cykel- och kollektivtrafik både som konkurrerande och som komplementära färdmedel och modellen kan utvärdera effekten av en förbättring av cykelinfrastrukturen på både enbart cykelresande och på cykel som anslutningsfärdmedel till kollektivtrafikstationer. Modellen är validerad mot cykelräkningar i Stockholm stad från september och oktober 2015. Modellen har testats på sex scenarier valda från Stockholms stads investeringsplan. Resultaten visar att investeringarna har en begränsad effekt på överflyttning mellan färdmedel och en måttlig effekt på befintliga cyklisters ruttval, restid och generaliserad kostnad.
The transport impacts of collection-delivery points (CDPs), as an alternative to home delivery, are rarely studied. As e-shopping becomes increasingly popular, trips to collect deliveries at CDP, especially by car travel, may generate a considerable amount of external effects, such as emissions. Therefore, this paper analysed the "picking up/leaving goods" trips selected from the Swedish National Travel Survey and jointly modelled the individuals' mode choice and trip chaining decisions using a panel cross-nested logit model. The roles of trip chain characteristics, individual socio-demographics and land use characteristics on each trip chain and mode choice combination are investigated. The results indicate observed and unobserved heterogeneities of trip chaining and mode choice decisions among populations. Young adults living with partners/spouses, single adults with children and partnered adults with children have the preference of using cars in collection-delivery trips compared to other life-cycle groups. A sensitivity analysis is carried out to estimate the effect of distance to CDPs on vehicle kilometres travelled. The calibrated model is used to estimate the VKT of collection-delivery trips in the greater Stockholm area. The results indicate a 22.5% reduction of VKT from collection-delivery trips by relocating 5% CDPs from urban areas to suburban and rural areas.
Regeringen har uppdragit åt Statens väg- och transportforskningsinstitut (VTI) att ”bidra till kunskapsuppbyggnaden kring en snabb, smart och samhällsekonomiskt effektiv elektrifiering av transportsektorn”. Den här rapporten redovisar den del av uppdraget som handlar om att genomföra pilotprojekt och ta fram modeller för hur data i praktiken på bästa sätt kan tillgängliggöras, delas och nyttiggöras för att optimera planering, utveckling, drift samt affärsmodeller för laddinfrastruktur.
I rapporten ges en beskrivning av förekommande tekniker för laddning av elfordon, viktiga användarperspektiv, och hur affärsmodeller och system för laddinfrastruktur kan modelleras.
Rapporten fokuserar på datadelning och beskriver hur aktörer idag delar data samt vilka svårigheter de ser med datadelning. Detta omfattar bland annat datatillgänglighet, delning och nyttiggörande, samt hur aktörerna vill att det ska fungera framåt. En stor utmaning handlar om datatillgänglighet, där aktörer dels ser problem med att få tillgång till data och dels är avvaktande till att vilja dela med sig av egna data. Ofta handlar det om integritetsfrågor och reglering enligt GDPR.
Betydelsen av en väl fungerande samverkan mellan energi- och transportsektorn har lyfts i tidigare rapporteringar från det här uppdraget. Vikten av en digitalisering och digital infrastruktur som kopplar samman dessa sektorer betonas speciellt i detta arbete. Digitalisering behövs för att effektivisera planering, utveckling och drift av den infrastruktur som ett elektrifierat transportsystem kräver. De modelleringar som gjorts i den här delen av uppdraget handlar om transportmodellering och energimodellering samt utveckling för att få modellerna att samspela.
Road authorities need tools to assess potential impacts on traffic performance due to the introduction of automated vehicles. Extended traffic modelling tools offer possibilities to estimate impacts on traffic performance metrics such as travel time, delay and capacity. However, there are large uncertainties related to the future behavior of automated vehicles, and these need to be carefully handled. The aim of this paper is to present a systematic and sound approach that can be used by road authorities to assess the automation readiness of a specific infrastructure. We present a definition of automation readiness from a traffic performance point of view, and an approach for how to estimate the automation readiness for a specific road design taking the uncertainties in the development of automated vehicles into account. The developed approach is applied to both macroscopic and microscopic use cases, demonstrating the applicability of the approach for automation readiness assessment.
This report presents the results of the application of the extended traffic models to the eight CoEXist use cases. The aim is to provide a self-contained report on each use case, complete with everything from problem formulation, model development, and experimental design, to presentation of simulation results. The background and the development of the baseline models have already been reported in D4.1 but has been revised and is included in this deliverable to provide a self-contained and complete technical report of the modelling of each use case. A much briefer report on the application of the use cases will be given in D4.3 where the tools for assessing the impact of automated vehicles will be applied to the simulation outputs of the use cases, providing high level results and conclusions.
The capability of making structured and informed decisions about the comprehensive deployment of CAVs (connected and automated vehicles) in a mixed road environment. This capability requires:
The aim of this report is to present definitions of the metrics that will be utilised in CoEXist to assess the effects on traffic performance and space efficiency as well as to present the qualitative assessment approach used to assess potential effects on traffic safety. The definitions will be used as a basis for the development of the assessment tool. The definitions presented in this report may be revised, and the final definitions of the metrics will be presented in deliverable “D3.3: AV-ready hybrid road infrastructure assessment tool”.
The many uncertainties related to the introduction of automated vehicles imply a need to for a structured way of assessing impacts for different future development with respect to penetration rates of automated vehicles and mixes of different types of automated vehicles but also for different travel demand levels and behavioural changes of road users. In order to provide a summarized picture of potential impacts for different stages of coexistence between automated vehicles and other road users an assessment approach was developed (see D3.3 (Pereira et al., 2020) for details). To simplify the assessment and to create a standard way of presenting the results taking uncertainties into account the approach was implemented in one spreadsheet-based tool for assessment of traffic performance and space efficiency and one tool for qualitative safety assessment.
The aim of this report is to present the results from applying the tools for assessing traffic impacts of automated vehicles to the simulation outputs of the eight use cases within CoEXist. The aim of the traffic performance and space efficiency tool is to concisely present an assessment of the traffic performance impact of the introduction of automated vehicles, based on the output from models, including the uncertainties considered. The aim of the qualitative safety assessment tool is to provide rough estimates on how automated driving functions might affect safety for use case relevant accident types. Both of these tools are tested and demonstrated through the applications presented here.
Trafikmodeller för (bil)trafikprocesser har varit och är ett viktigt stöd vid trafikplanering, oavsett om planeringen sker på kommunal, regional eller statlig nivå. Trafikmodeller av olika slag har bland annat gjort det möjligt att med hög kvalitet utvärdera effekter av förändringar i trafiksystemet, att ta fram underlag till effektsamband och att styra trafik. Denna typ av modellstöd stöd saknas till stor del vid planering av cykelinfrastruktur, vilket exempelvis medför svårigheter att utvärdera investeringar i cykelinfrastruktur i samhällsekonomiska kalkyler, ger bristande underlag för effektsamband, samt försvårar planering av effektiv, säker och attraktiv cykelinfrastruktur.
Syftet med denna förstudie är att identifiera behov av modellstöd vid analys av cykeltrafik, i samband med att åtgärder inom gång-, cykel- och bilinfrastruktur analyseras, samt att identifiera forsknings- och utvecklingsbehov i Sverige inom området cykeltrafikmodeller. Ett av målen är att tydliggöra kommuner och regioners behov av modellstöd samt till att öka kommuners och regioners medvetenhet om vad cykeltrafikmodeller kan bidra med i arbetet för en ökad och säker cykling.
För att undersöka behoven av cykeltrafikmodeller har det inom projektet genomförts både intervjuer med konsulter och en workshop med kommuner, regioner och Trafikverket. Detta PM redovisar slutsatserna från dessa intervjuer och workshopen.
The prevalence of mobile technology has been significant in transport research. Despite a growing application spectrum of smartphone uses and interests in mobility inference, little effort has been put into discussing theories, models, and research topics based on a systematic study of scholarly sources rooted in the interdisciplinary area of mobile technology and transport. Therefore, a timely and comprehensive synthesis of the current state of research is deemed to be required. A literature analysis, following PRISMA guidelines, aims to identify the successful development and implementation of the mobile technology that can be employed for behavior studies in transport. A review of the Web of Science Core Collections, JSTOR and SAGE databases, is performed. A rigorous screening process is used to collect key articles to construct the general image of existing knowledge. In addition, this study suggests an integrated research model to summarize how previous studies attain behavioral outcomes and a research agenda to identify unresolved research questions that future research can address. Two hundred fourty-eight papers meet the inclusion criteria. This study demonstrates that mobile technology is helpful for a better understanding of the various types of transport behaviors. They can be categorized according to their system designs and research topics: (1) Smartphone apps in sustainable transport and travel planning were studied in a remarkable collection of articles. (2) As individual's mobility was under question, cellular signaling data were prominent for the formulation of analytical models. (3) CDRs, WiFi, and GPS data have increasingly been used, but the share of the modeling techniques for all mobile information systems has remained low. It shows that system designers could supply more desirable and appealing features in most areas. However, applications for the movement of goods are limited, although freighting has moved toward digitalization. © 2021 Yan Sun et al.
This chapter explores the patterns of time use and immobility behaviours in Bandung city, the second biggest metropolitan area in Indonesia. A three-week time-use and activity diary is used. The day-to-day variations in time use allocation across different socio-demographic groups are examined. The results show different distinct weekday and weekend patterns and mobile and immobile days’ patterns of respondents’ time use distribution. The results show a strong tendency of social exclusion resulting from transport poverty.
This chapter focuses on the six typical shared activities, i.e. grocery shopping, household chores, babysitting, picking up children, relaxing, and social activities, and investigates on how a husband/wife’s time allocation on such activities is influenced by his/her spouse’s participation on the same activities and vice versa. The results show that the altruism behaviors differ substantially across different activity types. Income and the presence of children polarize husband’s altruism behaviors, and wives have a lot of power in influencing husbands’ time use allocations for activities such as baby-sitting. At the same time, the results also show the significant role of opportunities, such as accessibilities to wider crowd and amenities, in shaping household members’ altruism behaviors.
This study utilised the Swedish national travel survey covering a period of over 30 years. We investigated the long-term trends in activity-travel patterns of individuals in different life-cycle stages and generations using cohort analysis and a path model. The main findings are summarised as follows. The women, including mothers, in younger generations have become more active in out-of-home non-work activities and their trip chaining has become more complex, compared to their male counterparts. While men are still driving more than women, the gap is decreasing in the younger generations. The gender difference among teenagers in terms of out-of-home time use diminishes in younger generations. Teenagers of younger generations spend more of their leisure time inside their homes, possibly due to the rise of online activities and gaming and more time-consuming school trips, the latter attributed to changes in school choice policy. Older adults travel more, possibly due to better paratransit transport service, supported by better health services.
In order to improve current rail timetabling processes, the suitability of train departure times for passengers should be included in timetable assessment. To achieve this, one possibility is to calculate the change in consumer and producer surplus (i.e., the economic welfare) resulting from departure time shifts in rail timetables. However, existing methods for this calculation are quite limited. To fill this gap, we propose a new method in the current paper. This method enables comparing most scenarios involved in interregional rail timetabling in terms of economic welfare. To this end, our method takes advantage of schedule-based models that allow assessing the impact of departure time shifts on the demand and valuation of each possible route using the timetable. As a proof of concept, we illustrate this method on a case study on the busiest Swedish interregional line. This case study shows the potential of the method to deliver detailed calculations with analysis of equity effects. To conclude, the method presented in this paper improves on the current literature, and it can be used to improve timetable optimisation algorithms or to better resolve conflicts between train path requests. © 2021 The Authors
Valuations for various attributes of the transport supply are key parameters in travel demand forecast models and cost-benefit analyses. In the case of interregional rail travel, such attributes are mostly travel time, departure/arrival time, and comfort/service levels. Although the valuations for travel time savings and comfort levels are well documented, literature concerning how much passengers are willing to pay to obtain the departure/arrival time that best suits their needs remains scarce. We present in this paper a new study that estimates passenger valuations for reduction of departure time displacement (also called schedule delay) through common adaptation of the scheduling model. Our goal is twofold: first, better understand how travel scheduling is influenced by socioeconomic backgrounds and trip characteristics; second, provide detailed figures that can be used to improve travel demand forecasts and cost-benefit analyses. To achieve this, we conducted a stated preference survey on several Swedish rail routes and determined the valuations for departure time scheduling as willingness to pay and time multipliers. The figures obtained show that departure time flexibility greatly depends on trip characteristics and travellers’ socio-economic background. In addition, the comparison of our figures with previous literature highlights the need to establish a standardised method to measure and use these valuations. Finally, we succeeded in providing valuations that can be used with care as approximations in demand modelling and cost-benefit analyses in the context of interregional rail travel.
This paper studies the role of potential investors in financing renewable energy systems—specifically, relating to crowdfunding as a financing mechanism, with the enhancement of internet and social-media tools. The research question in this study is whether crowdfunding with a novel socio-technical product reward program attracts potential customers to a more sustainable milk product with a specific integrated photovoltaic water pumping (PVWP) system. The particular case study we empirically investigated is product reward crowdfunding in dairy milk production in China. The milk production chain was supplied by PVWP system integration, which generated solar energy both for feed production for dairy cows and for the operation of dairy farms. 48 semi-structured in-depth interviews were conducted between the research team and customers in order to perform qualitative analyses of the determinants of customers’ milk purchase behaviors. In addition, 357 online surveys were collected for quantitative analysis. Binary and ordered probit regressions were employed to use survey date to systematically estimate purchase intention and willingness-to-pay for sustainable milk. Customer behaviors, environmental consciousness, and individual socio-demographic factors were investigated as potential explanatory variables.
This article evaluated key factors which may influence potential customers for crowdfunding, and used a discrete choice model to estimate customers’ willingness-to-pay for reward-based projects. These results could help producers of sustainable milk products to identify potential target groups in China and estimate market demand. This exploratory study could provide a framework with both quantitative and qualitative assessment of crowdfunding for renewable energy systems in a national or international context.
In comparison with current financing mechanisms for renewable energy systems, crowd-funding financing mechanism offers a new potential source of financing with recent use of social media. Crowd-funding financing mechanism can also increases the social supports for renewable energy systems as users and investors turn to be more actively engaged in energy systems. As a new potential source of financing, crowd-funding mechanism has different forms, including donation, lending, equity and product reward approaches. In this paper, discrete choice model was used to explore whether crowd-funding financing with a novel sociotechnical product reward practice, has the attractions for potential customers to pay for a more sustainable milk product with distributed photovoltaic (PV) system. We empirically investigated the reward-base crowd funding with the specific integrated photovoltaic water pumping (PVWP) system in dairy milk production in China. 48 in-depth interviews were adopted for qualitative analysis of determinants of customer milk purchase decision. The ordered probit regression was employed with 357 online surveys to systematically estimate the purchase intention for the online-crowd-funding sustainable milk. Customer behaviours, environmental consciousness, and the individual socio-demographic factors were tested as potential explanatory variables. In the survey and depth interview samples, we found interviewees as potential customers showed strong purchase intentions to the crowd funding dairy milk for noticing milk quality and nutritious improvement, emission reduction and environmental benefits by the integrated PVWP system. In our findings of the regression results, the females, customers with young children or planning to have children were found with higher willing to purchase than other customers for crowd funding the sustainable dairy milk. The familiarity and popularity with online shopping and pre-sale purchase in China made customers more open and active towards pre-pay and crowd-funding mechanism.