Rafal Kucharski
Biographic Data
| ID | 1832309 |
|---|---|
| NAME | Rafal Kucharski |
| GIVEN NAMES | Rafal |
| FAMILY NAME | Kucharski |
| SIGNATURE | KUCHARSKI R |
| AFFILIATIONS | Jagiellonian University |
| ORCID | 0000-0002-9767-8883 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 4 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 1 |
Mitigating bus bunching with real-time crowding information
A common problem in public transport systems is bus bunching, characterized by a negative feedback loop between service headways, number of boarding passengers and dwell times. In this study, we examine whether providing real-time crowding information (RTCI) at the stop regarding the two next vehicle departures can stimulate passengers to wait for a less-crowded departure, and thus alleviate the bunching effect. To this end, we leverage on result…
Spatiotemporal variability of ride-pooling potential – Half a year New York City experiment
Network structures of urban ride-pooling problems and their properties
Travellers, when sharing their rides in a so-called ride-pooling system, form complex networks. Despite being the algorithmic backbone to the ride-pooling problems, the shareability graphs have not been explicitly analysed yet. Here, we formalise them, study their properties and analyse relations between topological properties and expected ride-pooling performance. We introduce and formalise two representations at the two crucial stages of poolin…
Using city-bike stopovers to reveal spatial patterns of urban attractiveness
We demonstrate how digital traces of city-bike trips may become useful to identify urban space attractiveness. We exploit their unique feature – stopovers: short, non-traffic-related stops made by cyclists during their trips. As we demonstrate with the case study of Kraków (Poland), when applied to a big dataset, meaningful patterns appear, with hotspots (places with long and frequent stopovers) identified at both the top tourist and leisure attr…
Network structures of urban ride-pooling problems and their properties
Travellers, when sharing their rides in a so-called ride-pooling system, form complex networks. Despite being the algorithmic backbone to the ride-pooling problems, the shareability graphs have not been explicitly analysed yet. Here, we formalise them, study their properties and analyse relations between topological properties and expected ride-pooling performance. We introduce and formalise two representations at the two crucial stages of poolin…
Using city-bike stopovers to reveal spatial patterns of urban attractiveness
We demonstrate how digital traces of city-bike trips may become useful to identify urban space attractiveness. We exploit their unique feature – stopovers: short, non-traffic-related stops made by cyclists during their trips. As we demonstrate with the case study of Kraków (Poland), when applied to a big dataset, meaningful patterns appear, with hotspots (places with long and frequent stopovers) identified at both the top tourist and leisure attr…
Mitigating bus bunching with real-time crowding information
A common problem in public transport systems is bus bunching, characterized by a negative feedback loop between service headways, number of boarding passengers and dwell times. In this study, we examine whether providing real-time crowding information (RTCI) at the stop regarding the two next vehicle departures can stimulate passengers to wait for a less-crowded departure, and thus alleviate the bunching effect. To this end, we leverage on result…
Spatiotemporal variability of ride-pooling potential – Half a year New York City experiment
Network structures of urban ride-pooling problems and their properties
Travellers, when sharing their rides in a so-called ride-pooling system, form complex networks. Despite being the algorithmic backbone to the ride-pooling problems, the shareability graphs have not been explicitly analysed yet. Here, we formalise them, study their properties and analyse relations between topological properties and expected ride-pooling performance. We introduce and formalise two representations at the two crucial stages of poolin…
Computer Science (4 works) · Engineering (3 works) · Transport engineering (3 works) · Transportation and Mobility Innovations (3 works) · Transportation Planning and Optimization (3 works) · Artificial Intelligence (2 works) · Geography (2 works) · Pooling (2 works) · Psychology (2 works) · TRIPS architecture (2 works)