Autonomous vehicle fleets for public transport: scenarios and comparisons

Autonomous vehicles (AVs) are becoming a reality and may integrate with existing public transport systems to enable the new generation of autonomous public transport. It is vital to understand what are the alternatives for AV integration from different angles such as costs, emissions, and transport performance. With the aim to support AV integration in public transport, this paper takes a typical European city as a case study for analyzing the impacts of different AV integration alternatives. A transport planning model considering AVs is developed and implemented, with a methodology to estimate the costs of the transport network. Traffic simulations are conducted to derive key variables related to AVs. An optimization process is introduced for identifying the optimal network configuration based on a given AV integration strategy, followed by the design of different AV integration scenarios, simulation, and analyses. With the proposed method, a case study is done for the city of Uppsala with presentation of detailed cost results together with key traffic statistics such as mode share. The results show that integrating AVs into public transport does not necessarily improve the overall cost efficiency. Based on the results and considering the long transition period to fully autonomous vehicles, it is recommended that public transport should consider a gradual introduction of AVs with more detailed analysis on different combination and integration alternatives of bus services and AVs.Peer ReviewedPostprint (published version

Topological Magnetoresistance of Magnetic Skyrmionic Bubbles

Magnetic skyrmions offer promising prospects for constructing future energy-efficient and high-density information technology, leading to extensive explorations of new skyrmionic materials recently. The topological Hall effect has been widely adopted as a distinctive marker of skyrmion emergence. Alternately, here we propose a novel signature of skyrmion state by quantitatively investigating the magnetoresistance (MR) induced by skyrmionic bubbles in CeMn2Ge2. An intriguing finding was revealed: the anomalous MR measured at different temperatures can be normalized into a single curve, regardless of sample thickness. This behavior can be accurately reproduced by the recent chiral spin textures MR model. Further analysis of the MR anomaly allowed us to quantitatively examine the effective magnetic fields of various scattering channels. Remarkably, the analyses, combined with the Lorentz transmission electronic microscopy results, indicate that the in-plane scattering channel with triplet exchange interactions predominantly governs the magnetotransport in the Bloch-type skyrmionic bubble state. Our results not only provide insights into the quantum correction on MR induced by skyrmionic bubble phase, but also present an electrical probing method for studying chiral spin texture formation, evolution and their topological properties, which opens up exciting possibilities for identifying new skyrmionic materials and advancing the methodology for studying chiral spin textures.Comment: 17 pages,5 figures,submitte

Modified nusinersen intrathecal injection method: inclusion of a septal needle-free closed infusion connector

ObjectiveNusinersen, an extremely expensive biologic drug (around 100,000 US$ per dose) that needs to be administered intrathecally, is approved for the treatment of 5q-spinal muscular atrophy (SMA). Because of the low muscle tone of the back muscles of pediatric SMA patients, especially type 1 SMA patients, the safe, effective, and fast execution of sheath injection is needed. Therefore, a modified intrathecal injection method was developed accordingly. This paper aims to describe the applicability and safety of this modified method.MethodsThe modified intrathecal injection method (MIIM) mainly includes a septal needle-free closed infusion connector between the lumbar puncture needle and the syringe, besides the procedures of routine lumbar puncture. Its applicability and safety were evaluated through clinical observation.ResultsA total of 92 children with SMA have successfully received nusinersen treatment at our hospital using the modified method since 2019 without obvious adverse events related to the modified injection method. Based on the clinical feedback of operators, the advantages of the modified method include successfully injecting the total dose of nusinersen with constant injection rate and a more stable fixation of the puncture needle, as well as making the operator more relaxed. However, compared with the routine method, the procedure of the modified method has additional steps.ConclusionThe modified intrathecal injection method is an effective and safe method to inject nusinersen when weighing the pros and cons, and it may also be used for administering intrathecal injections of other expensive medicines or for patients with other strict requirements for intrathecal injection

Somatic SF3B1 hotspot mutation in prolactinomas.

The genetic basis and corresponding clinical relevance of prolactinomas remain poorly understood. Here, we perform whole genome sequencing (WGS) on 21 patients with prolactinomas to detect somatic mutations and then validate the mutations with digital polymerase chain reaction (PCR) analysis of tissue samples from 227 prolactinomas. We identify the same hotspot somatic mutation in splicing factor 3 subunit B1 (SF3B1R625H) in 19.8% of prolactinomas. These patients with mutant prolactinomas display higher prolactin (PRL) levels (p = 0.02) and shorter progression-free survival (PFS) (p = 0.02) compared to patients without the mutation. Moreover, we identify that the SF3B1R625H mutation causes aberrant splicing of estrogen related receptor gamma (ESRRG), which results in stronger binding of pituitary-specific positive transcription factor 1 (Pit-1), leading to excessive PRL secretion. Thus our study validates an important mutation and elucidates a potential mechanism underlying the pathogenesis of prolactinomas that may lead to the development of targeted therapeutics

Modelling demand for high speed rail in Sweden. : Business trips

Recently conducted revealed preference and stated choice surveys in Sweden have extended data availability for travel demand modelling. Refined models with destination and mode choice are herein developed mainly for the long-distance business-trip market in Sweden. With focus on the nonlinearity of crucial variables and the underlying pattern of unobserved correlation, general Box-Cox transformations as well as nested logit formulation together with other data techniques are employed. Finally, the model with best goodness of fit is recommended for the high-speed train (HST) prediction. The main findings implicate multiple impressive impacts of HST on the business trip market, as well as instructive and practical hints on the blueprint of business trip market in the long term

Modelling demand for high speed rail in Sweden. : Business trips

Recently conducted revealed preference and stated choice surveys in Sweden have extended data availability for travel demand modelling. Refined models with destination and mode choice are herein developed mainly for the long-distance business-trip market in Sweden. With focus on the nonlinearity of crucial variables and the underlying pattern of unobserved correlation, general Box-Cox transformations as well as nested logit formulation together with other data techniques are employed. Finally, the model with best goodness of fit is recommended for the high-speed train (HST) prediction. The main findings implicate multiple impressive impacts of HST on the business trip market, as well as instructive and practical hints on the blueprint of business trip market in the long term

Hastighetsövervakning med sensorer från mätfordonet

Rapporten är framtagen med ekonomiska bidrag från Trafikverket, Skyltfonden. Ståndpunkter och slutsatser i rapporten reflekterar författaren och överensstämmer inte med nödvändighet med Trafikverkets ståndpunkter och slutsatser inom rapportens ämnesområden.I detta pilotprojekt har WSP utvecklat ett system för att mäta och informera om realtidshastigheter som vi kallar ”Speed Tracker”. Systemet består av modern sensorteknik som även används i stödsystem och autonom styrning inom fordonsindustrin. Systemet mäter kontinuerligt relativ hastighet mellan närliggande objekt/fordon och absolut hastighet för mätfordonet. På det sättet kan absolut hastighet för alla närliggande fordon beräknas direkt vid mätning. Om hastigheten för närmast bakomvarande fordon är högre än skyltad hastighet så får föraren en upplysning om detta via en LED-skärm som är monterad på mätbilens tak. Hela rörelseförloppet registreras med både positioner och hastighet så att man efteråt kan avgöra om upplysningen via LED-skärmen påverkar fordonsförarens beteende. Prototypen ”Speed Tracker”, inklusive dess hårdvaror och mjukvara fungerar som förväntat under testkörningar på motorväg i stadsmiljö. Systemet kan ses som en mobil mätningsstation eller ett mobilt hastighetsmätningssystem som kan anpassas för olika tillämpningar och dynamiskt bevakningsbehov, t.ex. uppföljning av hastighetsdämpningseffekter av trafiksäkerhetsåtgärder. Vid två testkörningar på E20/E4 i Stockholm, där en personbil utrustats med det nya hastighetsmätningssystemet, kunde en signifikant hastighetsreduktion påvisas. Detta genom att medtrafikanternas realtidshastighet visades på LEDskärmen när efterföljande bil överträdde hastighetsgränsen. Hastighetreduktionseffekten har varierat i förhållande till olika hastighetsbegränsningar mellan trafikplats Södertälje och Norrtull. I genomsnitt minskade hastigheten med 1 % för bilar som körde för fort och låg i samma körfält som mätfordonet. Minskningseffekter förväntas blir större vid högre hastighetsbegränsning och i körfältet längst till vänster, samt om systemet används på offentligt ägda fordon t.ex. polisbilar. När medelhastigheten sänks med 1 % (ca 0,7–1 kilometer i timmen) märks det knappt för den enskilde trafikanten, men det kan motsvara uppemot 15 räddade liv per år i hela landet. Resultatet av testkörningar visar att ”social nudging” av medtrafikanterna har en signifikant effekt även utan incitament mot eller straff för hastighetsöverträdelser. Det tar ca 15 minuter att montera prototypen på en mätbil och koppla ihop den med datorn, efter en utbildning på ca 15 minuter om personen inte sedan tidigare har någon erfarenhet av systemet. Systemet skulle kunna enkelt monteras på t.ex. en polisbil, som framförs på en väg även i andra ärenden än trafikövervakning

Investigating machine learning for simulating urban transport patterns: A comparison with traditional macro-models

Predicting passenger flow within a city is crucial for intelligent transportation management systems, especially in the context of urban development, post-pandemic policy changes, and infrastructure improvements. Traditional macro models have limitations in accurately capturing the complex structure of real traffic flows, and recent advancements in machine learning offer promising approaches for improving transportation simulations. This research aims to compare the effectiveness of traditional simulation models with a selective machine learning (ML) model for traffic flow prediction in Oslo, Norway. Sensitivity and scenario analyses are conducted to examine the models’ parameters and derive the city’s characteristics. Results substantiate that the traditional Spatial Interaction model (SIM), although interpretable and requiring fewer parameters, has limitations in accurately capturing real flow structures and exhibits greater variability compared to the ML model. Statistical analyses support these findings and raise questions about the validity of the ML model’s results over the SIM. The research highlights the potential of ML models to identify trends in passenger flows and simulate traffic flows in different scenarios related to city development. Overall, the research presents a decision support system for planners and policymakers to predict traffic flow accurately and efficiently. It highlights the benefits and drawbacks of both the traditional SIM and ML models, contributing to the ongoing discussion of the role of machine learning in transportation modeling