Rafał Kucharski

List of main publications and preprints

1. Tmertica:A

   Hyper-pool: pooling private trips into high-occupancy transit-like attractive shared rides

   Kucharski, Rafal, and Cats, Oded

   arXiv preprint arXiv:2206.05940 2022

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   We propose Hyper-pool, an analytical, offline, utility-driven ride-pooling algorithm to aggregate individual trip requests into attractive shared rides of high-occupancy. We depart from our ride-pooling ExMAS algorithm where single rides are pooled into attractive door-to-door rides and propose two novel demand-side algorithms for further aggregating individual demand towards more compact pooling. First, we generate stop-to-stop rides, with a single pick up and drop off points optimal for all the travellers. Second, we bundle such rides again, resulting with hyper-pooled rides compact enough to resemble public transport operations. We propose a bottom-up framework where the pooling degree of identified rides is gradually increased, thereby ensuring attractiveness at subsequent aggregation levels. Our Hyper-pool method outputs the set of attractive pooled rides per service variant for a given travel demand. The algorithms are publicly available and reproducible. It is applicable for real-size demand datasets and opens new opportunities for exploiting the limits of ride-pooling potential. In our Amsterdam case-study we managed to pool over 220 travellers into 40 hyper-pooled rides of average occupancy 5.8 pax/veh.

2. PLOS

   Simulating two-sided mobility platforms with MaaSSim

   Kucharski, Rafał, and Cats, Oded

   PLoS ONE 2022

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   Two-sided mobility platforms, such as Uber and Lyft, widely emerged in the urban mobility landscape. Distributed supply of individual drivers, matched with travellers via intermediate platform yields a new class of phenomena not present in urban mobility before. Such disruptive changes to transportation systems call for a simulation framework where researchers from various and across disciplines may introduce models aimed at representing the complex dynamics of platform-driven urban mobility. In this work, we present MaaSSim, a lightweight agent-based simulator reproducing the transport system used by two kinds of agents: (i) travellers, requesting to travel from their origin to destination at a given time, and (ii) drivers supplying their travel needs by offering them rides. An intermediate agent, the platform, matches demand with supply. Agents are individual decision-makers. Specifically, travellers may decide which mode they use or reject an incoming offer; drivers may opt-out from the system or reject incoming requests. All of the above behaviours are modelled through user-defined modules, allowing to represent agents’ taste variations (heterogeneity), their previous experiences (learning) and available information (system control). MaaSSim is a flexible open-source python library capable of realistically reproducing complex interactions between agents of a two-sided mobility platform. MaaSSim is available from a public repository, along with a set of tutorials and reproducible use-case scenarios, as demonstrated with a series of illustrative examples and a comprehensive case study.

3. SciRep

   Modelling virus spreading in ride-pooling networks

   Kucharski, Rafał, Cats, Oded, and Sienkiewicz, Julian

   Scientific Reports 2021

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   Urban mobility needs alternative sustainable travel modes to keep our pandemic cities in motion. Ride-pooling, where a single vehicle is shared by more than one traveller, is not only appealing for mobility platforms and their travellers, but also for promoting the sustainability of urban mobility systems. Yet, the potential of ride-pooling rides to serve as a safe and effective alternative given the personal and public health risks considerations associated with the COVID-19 pandemic is hitherto unknown. To answer this, we combine epidemiological and behavioural shareability models to examine spreading among ride-pooling travellers, with an application for Amsterdam. Findings are at first sight devastating, with only few initially infected travellers needed to spread the virus to hundreds of ride-pooling users. Without intervention, ride-pooling system may substantially contribute to virus spreading. Notwithstanding, we identify an effective control measure allowing to halt the spreading before the outbreaks (at 50 instead of 800 infections) without sacrificing the efficiency achieved by pooling. Fixed matches among co-travellers disconnect the otherwise dense contact network, encapsulating the virus in small communities and preventing the outbreaks.

4. TR:B

   Exact matching of attractive shared rides (ExMAS) for system-wide strategic evaluations

   Kucharski, Rafał, and Cats, Oded

   Transportation Research Part B: Methodological 2020

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   The premise of ride-sharing is that service providers can offer a discount, so that travellers are compensated for prolonged travel times and induced discomfort, while still increasing their revenues. While recently proposed real-time solutions support online operations, algorithms to perform strategic system-wide evaluations are crucially needed. We propose an exact, replicable and demand-, rather than supply-driven algorithm for matching trips into shared rides. We leverage on delimiting our search for attractive shared rides only, which, coupled with a directed shareability multi-graph representation and efficient graph searches with predetermined node sequence, narrows the (otherwise exploding) search-space effectively enough to derive an exact solution. The proposed utility-based formulation paves the way for model integration in travel demand models, allowing for a cross-scenario sensitivity analysis, including pricing strategies and regulation policies. We apply the proposed algorithm in a series of experiments for the case of Amsterdam, where we perform a system-wide analysis of the ride-sharing performance in terms of both algorithm computations of shareability under alternative demand, network and service settings as well as behavioural parameters. In the case of Amsterdam, 3000 travellers offered a 30% discount form 1900 rides achieving an average occupancy of 1.67 and yielding a 30% vehicle-hours reduction at the cost of halving service provider revenues and a 17% increase in passenger-hours. Benchmarking against time-window constrained approaches reveals that our algorithm reduces the search-space more effectively, while yielding solutions that are substantially more attractive for travellers.

5. Tmetrica:A

   If you are late, everyone is late: late passenger arrival and ride-pooling systems’ performance

   Kucharski, Rafał, Fielbaum, Andres, Alonso-Mora, Javier, and Cats, Oded

   Transportmetrica A: Transport Science 2021

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   Sharing rides in on-demand systems allow passengers to reduce their fares and service providers to increase revenue, though at the cost of adding uncertainty to the system. Notably, the uncertainty of ride-pooling systems stems not only from travel times but also from unique features of sharing, such as the dependency on other passengers’ arrival time at their pick up points. In this work, we theoretically and experimentally analyse how late arrivals at pick up locations impact shared rides’ performance. We find that the total delay is equally distributed among sharing passengers. However, delay composition gradually shifts from on-board delay only for the first passenger to waiting delay at the origin for the last passenger. Sadly, trips with more passengers are more adversely impacted. Strategic behaviour analysis reveals Nash equilibria that might emerge. We analyse the system-wide effects and find that when lateness increases passengers refrain from sharing and eventually opt-out.

6. TR:B

   Simulation of rerouting phenomena in Dynamic Traffic Assignment with the Information Comply Model

   Kucharski, Rafał, and Gentile, Guido

   Transportation Research Part B: Methodological 2019

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   We present the Information Comply Model (ICM) which extends the framework for macroscopic within-day DTA proposed by Gentile (2016) to represent the rerouting of drivers wrt a single traffic event. Rerouting is reproduced as a two-stage process: first, drivers become aware about the event and its consequences on traffic; second, drivers may decide to change path. At each arc, unaware drivers have a probability of being informed by multiple ATIS sources (radio, VMS, mobile apps), which depends not only on devise penetration rates, but also on users space and time coordinates wrt the position and interval of the event. At each node, aware drivers, who are somehow reluctant to change, may finally modify their path based on a random rerouting utility, which is composed of expected gains and avoided losses. ICM is thus capable of representing the evolution of rerouting phenomena in time and space when the information about a traffic event and its consequences on congestion spread among drivers and onto the network. This way, ICM extends the concept of dynamic user equilibrium to a case of imperfect information related to availability and awareness rather than to individual perception, as well as to a case of bounded rationality with prudent drivers. Besides the model architecture and specification, this paper provides a workable methodology which can be applied both off-line for transport planning and in real-time for traffic management on large size networks.

7. JAT

   Lewis-Mogridge Points: A Nonarbitrary Method to Include Induced Traffic in Cost-Benefit Analyses

   Kucharski, Arkadiusz, Paszkowski, Jan, and Szarata, Andrzej

   Journal of Advanced Transportation 2020

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   We propose a new method to estimate benefits of road network improvements, which allows to include the induced demand without arbitrary assumptions. Instead of estimating induced demand (which is nontrivial and hardly possible in practice), we search for demand induction where initial benefits are mitigated to zero. Such approach allows to formulate a dual measure of benefit, covering both the potential benefits and the likelihood of consuming them by the induced traffic. We first estimate benefits of road network improvement assuming that traffic demand is fixed. Consequently, we find demand model configurations at which the benefits of the new investment become null, i.e., all the initial benefits are consumed by the traffic demand growth. We call such states of induced demand the Lewis–Mogridge points of the analysed improvement. We select the most probable of such points and use it to calculate the proposed novel indicator μ, for which the initial benefits (obtained under a fixed-demand assumption) are multiplied with a demand increase rate needed to consume them. We believe that such measure allows to include the critical phenomena of induced traffic and, at the same time, to overcome problems associated with reliable estimation of induced demand. As we illustrate with the case of two alternative road improvement schemes in Kraków, Poland, the proposed method allows to estimate maximal threshold of induced traffic and to select scenario more resilient to induced traffic.

8. EJTIR

   Multichannel queueing behaviour in urban bicycle traffic

   Kucharski, Rafał, Drabicki, Arkadiusz, Żyłka, Klaudia, and Szarata, Andrzej

   European Journal of Transport and Infrastructure Research 2019

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   The objective of this paper is to propose a method to analyse and describe cyclists’ behaviour at signalized intersections with specific focus on the multichannel (multi-lane) queue phenomenon. As we observed, cyclists form queues without a fixed-lane and FIFO discipline, for which the classical, car-oriented analytical approach becomes insufficient. Cyclists’ multichannel queueing behaviour is common and characterized by substantial degree of variability, especially in case of shorter queues which emerge regularly at cycle crossings. Although cyclist behaviour has been widely studied by transportation research community, their queueing behaviour picture is still incomplete. Namely, there is no method addressed to analyse the full scope of these phenomena and to quantify their impact on the cyclist queue performance. To bridge this gap, we introduce the technique to observe multichannel queues and report relevant observations, which we then complement with a methodological framework to analyse obtained results and provide a complete multichannel queue description. We video-record cyclists as they enqueue to one of multiple channels, form the queue and smoothly merge into a single lane again as the queue discharges. We apply the method to analyse results from a pilot study of 160 cyclists forming 50 queues in the city of Krakow, Poland. The proposed method allows us to analyse and quantify the observed queue performance and its characteristics: the number of channels, their emergence process, channel and queue lengths, discharge process with FIFO violations, starting and discharging times. Findings from pilot study reveal that both queue length and discharge times strongly depend on queue formation process. The contribution of this paper is the method to describe multichannel cyclist queueing behaviour, enriching current picture of bicycle flow and cyclists’ behaviour. Since the method has been developed on relatively short queues (up to 10 cyclists), findings included in this paper primarily refer to such queue sizes. Nonetheless, the method is formulated in a generic way, applicable also for longer bicycle queues. Possible practical implications are new estimates for queue lengths and discharge times - useful for bicycle infrastructure design and traffic engineering purposes.

9. JAT

   Estimating Macroscopic Volume Delay Functions with the Traffic Density Derived from Measured Speeds and Flows

   Kucharski, Arkadiusz

   Journal of Advanced Transportation 2017

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   This paper proposes a new method to estimate the macroscopic volume delay function (VDF) from the point speed-flow measures. Contrary to typical VDF estimation methods it allows estimating speeds also for hypercritical traffic conditions, when both speeds and flow drop due to congestion (high density of traffic flow). We employ the well-known hydrodynamic relation of fundamental diagram to derive the so-called quasi-density from measured time-mean speeds and flows. This allows formulating the VDF estimation problem with a speed being monotonically decreasing function of quasi-density with a shape resembling the typical VDF like BPR. This way we can use the actually observed speeds and propose the macroscopic VDF realistically reproducing actual speeds also for hypercritical conditions. The proposed method is illustrated with half-year measurements from the induction loop system in city of Warsaw, which measured traffic flows and instantaneous speeds of over 5 million vehicles. Although the proposed method does not overcome the fundamental limitations of static macroscopic traffic models, which cannot represent dynamic traffic phenomena like queue, spillback, wave propagation, capacity drop, and so forth, we managed to improve the VDF goodness-of-fit from of 27% to 72% most importantly also for hypercritical conditions. Thanks to this traffic congestion in macroscopic traffic models can be reproduced more realistically in line with empirical observations.

10. Modeling information spread processes in dynamic traffic networks

    Kucharski, R., and Gentile, G.

    Communications in Computer and Information Science 2016
11. Observing rerouting phenomena in dynamic traffic networks

    Kucharski, R., and Gentile, G.

    2015
12. Indirect observation of rerouting phenomena in traffic networks - Case study of warsaw bridges

    Kucharski, R., and Gentile, G.

    Archives of Transport 2014
13. Direct observation of rerouting phenomena in traffic networks

    Kucharski, R., and Gentile, G.

    Archives of Transport 2014
14. Method to decompose regional travel demand model -case study of Krakow region

    Kucharski, R., Kulpa, T., Mielczarek, J., and Drabicki, A.

    Lecture Notes in Networks and Systems 2019
15. Real-time traffic forecasting with recent DTA methods

    Kucharski, R., Kostic, B., and Gentile, G.

    2017
16. Modelowanie oporu skrzyżowań w modelach makroskopowych

    Kucharski, Rafał, Drabicki, Arkadiusz, and Szarata, Andrzej

    Transport Miejski i Regionalny 2016
17. Model wyboru środka transportu w dojazdach do i z pracy w Warszawie

    Kucharski, Rafał, Kulpa, Tomasz, and Szarata, Andrzej

    Transport Miejski i Regionalny 2016
18. Gromadzenie danych do budowy modeli ruchu-przegląd możliwości

    Kucharski, R

    Transport Miejski i Regionalny 2013
19. Optymalizacja kształtu monocentrycznej sieci komunikacyjnej z zastosowaniem optymalizacji wielokryterialnej

    Kucharski, Rafał

    Przegląd Komunikacyjny 2011
20. Trip volume seasonal variations at regional level – case study of Małopolska GSM OD matrices

    Kucharski, R., Szarata, A., Mielczarek, J., and Drabicki, A.

    Archives of Transport System Telematics 2018
21. Metoda aktualizacji modelu podróży z wykorzystaniem macierzy przemieszczeń telefonów komórkowych

    Kucharski, Rafał, Mielczarek, Justyna, Drabicki, Arkadiusz, and Szarata, Andrzej

    Transport Miejski i Regionalny 2018
22. Information Comply Model–new model to represent rerouting phenomena in Dynamic Traffic Assignment

    Kucharski, Rafał, Gentile, G, and Meschini, L

    In 5th International Symposium on Dynamic Traffic Assignment 2014
23. Metoda detekcji cellular floating data—możliwości i perspektywy

    Kucharski, Rafał

    In Zeszyty Naukowe Politechniki Krakowskiej, zeszyt 2009
24. Multichannel Cyclist Queuing Behaviour at Signalised Cycle Crossings

    Kucharski, Rafał, Drabicki, Arkadiusz, Kulpa, Tomasz, and Szarata, Andrzej

    In hEART 2016 - 5th Symposium of the European Association for Research in Transportation
25. Makroskopowy model przepływu ruchu w sieci drugiego rzędu–alternatywny opis stanu sieci

    Kucharski, Rafał

    In Wydajność systemów transportowych, Materiały IX Konferencji naukowo-technicznej 2013
26. Tło teoretyczne dla adaptacyjnego, dynamicznego modelu wyboru ścieżki w modelu ruchu

    Kucharski, Rafał

    In Zeszyty Naukowo-Techniczne Stowarzyszenia Inżynierów i Techników Komunikacji w Krakowie. Seria: Materiały Konferencyjne 2012
27. Otwieranie oprogramowania–skrypty i programy w programie Visum

    Kucharski, Rafał

    In Ogólnopolska Konferencja Naukowo-Techniczna „Modelowanie podróży i prognozowanie ruchu”, Kraków 2010
28. Modelowanie wyboru środka transportu–porównanie regresji logistycznej i logitowego modelu wyboru dyskretnego

    Kucharski, Rafał, Szarata, A, Bauer, M, and Kulpa, T

    In X Poznańska Konferencja Naukowo-Techniczna, Poznań-Rosnówko 2015
29. Modelowanie zjawiska zmiany trasy przejazdu w dynamicznym rozkładzie ruchu w sieci drogowej

    Kucharski, Rafał, and Gentile, Guido

    In Zeszyty Naukowo-Techniczne Stowarzyszenia Inżynierów i Techników Komunikacji w Krakowie. Seria: Materiały Konferencyjne 2014
30. Makroskopowy Model Przeplywu Ruchu W Sieci Drugiego Rzedu – Alternatywny Opis

    Kucharski, Rafał

    In PROBLEMY KOMUNIKACYJNE MIAST W WARUNKACH ZATLOCZENIA MOTORYZACYJNEGO IX Konferencja Naukowo-Techniczna 2013
31. Lewis-Mogridge Points - A Non-Arbitrary Method of Including Induced Traffic in Cost-Benefit Analyses

    Kucharski, Rafał, Drabicki, Arkadiusz, Paszkowski, Jan, and Szarata, Andrzej

    In TRB Conference 2018
32. MoMaS: Two-sided Mobility Market Simulation Framework for Modeling Platform Growth Trajectories

    Kucharski, Rafal, and Ghasemi, Farnoud

    2024

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    Mobility platforms such as Uber and DiDi have been introduced in cities worldwide, each demonstrating varying degrees of success, employing diverse strategies, and exerting distinct impacts on urban mobility. We have observed various growth trajectories in two-sided mobility markets and understood the underlying mechanisms. However, to date, a realistic microscopic model of these markets including phenomena such as network effects has been missing. State-of-the-art methods well estimate the macroscopic equilibrium conditions in the market, but struggle to reproduce the individual human behaviour behind and complex growth patterns sensitive to platform strategy and policies. To bridge this gap, we introduce the MoMaS (two-sided Mobility Market Simulation) framework to represent growth mechanism in two-sided mobility markets based on the realistic behavior adjustment of drivers and travelers reactive to platform strategy. In the proposed framework, traveler and driver agents learn the platform utility from multiple channels: their own experience, peers’ word-of-mouth, and the platform’s marketing, all-together constituting the agent’s perceived utility of the platform. Each of these channels is modeled and updated by our S-shaped learning model day-to-day which stabilizes, and at the same time, remains sensitive to the system changes.The platform can simulate any strategy on five levers: trip fare, commission rate, discount rate, incentive rate, and marketing. MoMaS allows to reproduce a variety of market phenomena, including reluctancy, neutrality, and loyalty at the individual level, as well as critical mass, bandwagon effect, positive and negative cross-side network effects at the aggregated level, which are crucial to reproduce realistic growth trajectories.We illustrate the capabilities of MoMaS through an extensive set of real-world experiments. Our results demonstrate that once the platform acquires critical mass, it triggers a significant positive cross-side network effect, accelerating growth. However, this can be reversed if a negative cross-side network effect is triggered, leading to the collapse of the platform. MoMaS is applicable for real-sized problems and available on public repository along with reproducible experiments.