Search

Tutkimuksen tavoitteena oli arvioida viiden eri maanteiden nopeusrajoitusta muuttavan toimenpiteen vaikutuksia liikenteen turvallisuuteen, keskimääräiseen matkaaikaan, polttoaineenkulutukseen, energiankulutukseen, CO2-päästöihin ja liikennemeluun, ja vaikutusten yhteiskuntataloudellisia hyötyjä ja haittoja. Lisäksi arvioitiin, miten toimenpiteet tukevat valtakunnallisen liikennejärjestelmäsuunnitelman tavoitteita. Tutkimusmenetelmänä oli teoreettinen tarkastelu eri vaikutuksista perustuen nopeusrajoitusten muutosten aiheuttamiin keskinopeuden muutoksiin. Tarkasteltavat toimenpiteet olivat talviajan nopeusrajoitusten ympärivuotinen käyttö (TP1), yleisrajoitus 70 km/h taajaman ulkopuolella ja 40 km/h taajamissa (TP2), nopeusrajoitus ≥ 100 km/h vain rakenteellisesti erotetuilla tiejaksoilla (TP3), nopeusrajoitus enintään 100 km/h moottoriteillä (TP4) ja nopeusrajoitus 60–80 km/h kaupunkiseutujen sisääntuloväylillä (TP5). Kaikkien toimenpiteiden arvioitiin vähentävän vuosittaisia henkilövahinko-onnettomuuksia (-10...-77) sekä liikenteessä kuolleiden (-1...-14) ja vakavasti loukkaantuneiden (-1...-12) määrää. Suurimmat vaikutukset liikenneturvallisuuteen arvioitiin TP1:lle ja TP3:lle. Keskimääräisen matka-ajan arvioitiin kasvavan (3,7–9,6 %) kaikilla toimenpiteiden verkoilla. Sähköautojen vuosittaisen energiankulutuksen arvioitiin vähenevän kaikilla toimenpiteillä (-150...-1 280 MWh), ja polttoaineen vuosittaisen kulutuksen vähenevän lähes kaikilla toimenpiteillä (bensiini: 534...-6 274 kl ja diesel: -596...-7083 kl). Poikkeuksena on TP2, jonka arvioitiin johtavan kulutuksen maltilliseen kasvuun (bensiini: 228 kl ja diesel: 1 036 kl). Myös CO2-päästöjen arvioitiin vähenevän kaikilla toimenpiteillä (-2,3...-26,8 kt CO2) paitsi TP2:lla (2,5 kt CO2). Kaikkien toimenpiteiden arvioitiin vähentävän haitalliselle liikennemelulle altistuneiden määrää. Toimenpiteiden yhteiskuntataloudelliset vaikutukset laskettiin tieliikenteen hankearvioinnin yksikköarvojen avulla. Suurimmat arvioidut hyödyt syntyisivät henkilövahinkojen vähentymisestä (-3,7...-59,2 M€/v.) ja suurimmat haitat keskimääräisen matka-ajan kasvusta (8,3...59,2 M€/v.). Laskemalla yhteen kaikkien vaikutusalueiden arvioidut hyödyt ja haitat, TP3 ja TP5 olivat arvion mukaan yhteiskuntataloudellisesti hyödyllisiä (kustannussäästö noin -1,5 M€/v. molemmissa toimenpiteissä). Suurimmat arvioidut yhteiskuntataloudelliset haitat syntyisivät TP1:lle ja TP4:lle (kustannusten kasvu 4,9–6,7 M€/v). Kaikkien toimenpiteiden arvioitiin kasvattavan matka-aikoja hieman, minkä johdosta mikään toimenpide ei edistä saavutettavuustavoitetta. Kaikki toimenpiteet edistäisivät kestävyystavoitetta, koska ne vähentävät henkilövahinkoja, polttoaineen- ja sähkönkulutusta, hiilidioksidipäästöjä sekä haitalliselle liikennemelulle altistuneiden määrää. Kahdella toimenpiteen (TP3 ja TP5) arvioidut vaikutukset aikaan saavat yhteiskuntataloudellista hyötyä eli parantaisivat tehokkuustavoitetta.

The objective of the study was to identify the number and national fraction of crashes that could be affected by universal adoption of conditionally automated vehicles (SAE3) based on the expected number of injury crashes, fatalities, and serious injuries in Finland. The study considered passenger cars with automated driving systems (ADS) for motorways and urban areas. The results show that of the national annual average, the motorway ADS has the potential to affect at maximum 3.3% of injury crashes, 3.1% of fatalities, and 3.2% of serious injuries. The corresponding fractions for urban ADS in the four largest Finnish cities were: 2.2%, 1.1% and 2.5%. Of the cities’ annual average, urban ADS has the potential to affect at the most 17.4% of injury crashes, 17.1% of fatalities, and 26.8% of serious injuries. Although the market introduction of these ADS is on the horizon, deployment can be expected to be slow, indicating a need for additional measures to reach the traffic safety goals.

Road conditions and surface temperatures are known to influence the abrasion rate of road vehicle tyres. Tyre abrasion has the side effect of generating tyre and road wear particles belonging to microplastics that end up in soils and sediments. Therefore, it is necessary to know when, where and under which conditions vehicles drive to understand tyre abrasion.This study examined the prevalence of road weather conditions and road temperatures in Finland as vehicle kilometres driven. The distribution of conditions was estimated for main roads using road surface sensor data. The estimate for regional and connecting roads and urban street networks was derived from the main roads estimate with input from road weather experts.The results show that the most prevalent road condition on Finnish roads as kilometres driven is a dry road surface (56%), followed by wet and moist surfaces (29%). However, wintery conditions such as snow, ice and sleet still account for a large presence overall (12%), and especially during winter months (38%). 26% of annual vehicle kilometres are driven on surfaces below zero degrees Celsius. The distribution of conditions and temperatures is influenced both by time of the year and geography, with winters being at least partially snowy in the whole country and much colder and snowier in the north. The main result of this study is that the share of conditions in the annual kilometres driven in Finland are influenced by road class, geographic location and seasonal variation.

The goals of the project were to 1) assess the feasibility of the selected motorway section for the operation of SAE Level 3 and 4 automated vehicles, 2) propose a framework for service level classification for automated vehicles and 3) prepare a proposal for further research, R&D and international cooperation.The feasibility of the current road network for automated vehicles was assessed with a detailed inventory of the selected motorway section on E12 highway between Helsinki and Tampere, the overall length of 160 km per direction. Overall, the assessment proved, that the current physical and digital infrastructures provide good support for the basic use cases of level 3 or 4 highway autopilot. The project team did not identify any major defects that would require immediate corrective actions with regards to supporting automated driving on motorways. The service level classification builds on the ISAD (Infrastructure Support for Automated Driving) levels but has been extended to other relevant attribute areas of physical infrastructure, environmental conditions, and dynamic elements. The five ISAD levels from E to A have been maintained and the new attribute areas have been labeled following the original logic in digital infrastructure. The level thresholds are partly quantitative, where applicable data exists, and partly qualitatively described.The likely ODD attributes were compiled based on existing literature, and the validation and reformulation of the attributes based on the implemented field measurements and the views of subtask experts. The ODD attribute list was compressed to the most critical attributes, that are applicable in motorway environment and that can be provided with threshold values between the service levels, based on the current knowledge. The accomplished work should give the national authorities and operators a solid understanding of the most critical parts of the infrastructure regarding conditionally or highly automated driving. The created framework should work well in the communication of the overall and thematical AV support for the users and developers.There are many topics that require active follow-up of international standardization of AV support and related technological development. Topics suitable for national development include the need and requirements for positioning-support landmarks, new solutions for fast detection of road surface defects, and the development of improved road weather information. The next steps regarding the classification are to widen the mapping of the current Finnish motorway network against the classification and the development of similar type of classifications to other road environments. It would also be extremely useful to test the proposed classification in practice, e.g. in European projects and actions to find out about the applicability of the classification in other countries, even though the classification was designed especially the Finnish conditions in mind.

NordicWay 2 Version 1.0

Version: 1.0

The L3Pilot project, funded by H2020, is conducting the first large-scale piloting of SAE Level 3 automated driving in Europe. The main aim of the project is to address a number of key questions in a step towards introducing automated vehicles on European roads. This paper discusses the approach taken by the L3Pilot project, to evaluate user behaviour in, and acceptance of, automated driving in real-world pilots. Although some technical challenges associated with the development and demonstration of such technologies are well-documented, current methodologies, such as those used to evaluate Field Operational Tests (FOTs), offer little guidance about assessing the impact of automated driving on users’ behaviour and acceptance. This paper outlines the methods used and developed for assessing user behaviour and acceptance within the project, summarises some of the methodological challenges involved in collecting data during an automated driving pilot, and discusses some approaches we havedeveloped to solve these multifaceted challenges.

System dynamics offers a rigorous approach to modelling the sometimes-surprising dynamics endogenous in complex systems and is ideal for gaining insight into potential impacts of automation in transport. Researchers from Europe and the U.S. are developing a consensus model, starting from an impact assessment framework presented at TRA 2018 and published shortly thereafter. This paper reports on a 2019 group model building workshop, which collated the intelligence of a diverse international group of modelling, transport and liveability/equity experts, focusing on socioeconomic impacts of highly automated vehicles, from household and public authority standpoints. Subsequent work developed a general framework from which detailed system dynamics models can be created for specific research questions. The ultimate goal is to develop a quantitative tool that can help planners and policy-makers understand how highly automated vehicles may fit within the transport system, and to begin to explore consequences of potential actions under various scenarios.

Ylinopeuksien ja punaista päin ajamisen automaattivalvonta yleistyy kaupunkiympäristössä, mutta Suomessa ei ole tehty laajempaa selvitystä tällaisen valvonnan vaikutuksista. Tämän työn tarkoitus oli kerätä kaupunkialueiden automaattivalvonnan vaikutusarviointitutkimusta varten ennen-aineisto. Aineisto kerättiin Helsingissä, missä on suunniteltu rakentaa 70 valvontapistettä vuosien 2020–2024 aikana. Työssä tehtiin nopeusmittauksia neljässä tutkimus- ja kontrollikohteessa. Kohteet valittiin yhdessä Helsingin kaupungin edustajien kanssa. Kussakin kohteessa mitattiin ajoneuvojen: 1) pistenopeus kahdessa paikassa ja 2) matka-aika mahdollisimman pitkältä yhtenäiseltä katuosuudelta. Kerätystä aineistosta laskettiin tunnuslukuja kuvaamaan autoilijoiden nopeuksia ennen-tilanteessa. Varsinaista vaikutusarviointitutkimusta varten tarvittava jälkeen-aineisto tulee kerätä ennen-aineistoa vastaavalla tavalla valvontapisteiden asentamisen ja valvonnan käyttöönoton jälkeen. Jälkeen-mittauksia suunniteltaessa ja toteutettaessa tulee huomioida mahdolliset muutokset kohteissa ja katuympäristössä sekä lainsäädännössä yleisesti.

Laki liikennejärjestelmästä ja maanteistä edellyttää Euroopan laajuisen tieverkon (TEN-tiet) turvallisuustarkastelua vähintään joka kolmas vuosi. Tämä tutkimus sisältää Suomen alueella olevien TEN-teiden turvallisuusluokittelun direktiivin 2008/96/EY edellyttämällä tavalla. Taustaksi tarkastellaan pääteiden turvallisuutta eri palvelutasoilla.

Following the Deliverable D3.1 "From research questions to logging requirements", Deliverable D3.2 "Experimental Procedure" continues the L3Pilot methodology work. Deliverable D3.2 shows the experimental procedures for the L3Pilot pilot-sites with also an introduction how to organise the collected data so that results can be evaluated across the various pilot-sites.

This report documents the survey, which was designed to investigate views on the importanceof different key performance indicator (KPIs) for expressing the impact of automation in roadtransportation in several impact areas. It documents the rating results and additional KPIsproposed by the 77 experts in Europe, US and Japan who filled in the survey.The Trilateral Impact Assessment Subgroup of ART WG will use these results when decidingthe recommendations for the KPIs to be used in the impact assessment studies. Therecommendations and a full list of potential KPIs (KPI repository) will be added to the version2.0 of their impact assessment framework (expected in April 2018).

Automated driving in all its different forms is now underway and large European projects have been launched to investigate the effects in real life. Field Operational Tests are typically used to gather evidence to assess the impacts. The FESTA methodology was developed to design and conduct FOTs and analyse the outcomes. Currently the methodology is being updated to address the challenges of the upcoming pilots on road automation. The ultimate goal of performing automated driving studies is to gain insight into the impacts automation will have on transport and on society in general. In this paper we will explain how the series of FOT-Net (2008-2016) and the CARTRE (2016-2018) coordination and support actions address the development of a common methodology. Questions around the formulation of research questions, data analysis, user acceptance and impact assessment are addressed. One of the most important ways forward is the sharing of data, knowledge and experiences. Only by combining the knowledge sources will we be able to get a clearer picture of what the future impacts of road automation will be. FOT-Net has developed a data sharing framework and recommendations from this framework will be described.