Since ride-hailing has become an important travel alternative in many cities worldwide, a fervent debate is underway on whether it competes with or complements public transport services. We use Uber trip data six the United States and Europe to identify most attractive for each ride. then address following questions: (i) How does time cost compare fastest alternative? (ii) What proportion of trips that do not have viable (iii) change overall service accessibility? (iv) relation between...

Overcrowding is a major phenomenon affecting travel experience in urban public transport, whose negative impacts can be potentially mitigated with real-time crowding information (RTCI) on transport vehicle departures. In this study, we investigate the willingness to wait (WTW) instantaneous RTCI avoid in-vehicle (over)crowding passenger faces, focusing specifically context (i.e. bus and tram systems). We conduct stated-preference survey Krakow (Poland), where examine choice probability...

This paper proposes a new method to estimate the macroscopic volume delay function (VDF) from point speed-flow measures. Contrary typical VDF estimation methods it allows estimating speeds also for hypercritical traffic conditions, when both and flow drop due congestion (high density of flow). We employ well-known hydrodynamic relation fundamental diagram derive so-called quasi-density measured time-mean flows. formulating problem with speed being monotonically decreasing shape resembling...

The premise of ride-sharing is that service providers can offer a discount, so 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 crucially needed. We propose an exact, replicable demand-, rather than supply-driven algorithm matching trips into shared rides. leverage on delimiting our search attractive...

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 two next vehicle departures can stimulate to wait for less-crowded departure, thus alleviate bunching effect. To end, leverage on results from own stated-preference survey develop choice model. The model accounts...

Urban spatial structure, transport mode and space-time constraints are known to affect accessibility activities for a city's residents. However, most studies measure from home only report in terms of the travel time or number activities. Such neglect mobility budget on people's accessibility. Furthermore, modal disparity have not considered inequality between modes during afternoon commute. We examine non-work by automobile public using spatiotemporal measures that determine minutes people...

Public transport (PT) overcrowding is a notorious problem in urban networks. Its negative effects upon travel experience can be potentially addressed by disseminating real-time crowding information (RTCI) to passengers. However, impacts of RTCI provision PT networks remain largely unknown. This study aims contribute developing an extended dynamic simulation model that enables thorough analysis instantaneous consequences. In the model, generated and disseminated across network, then utilised...

With the increasing availability of big, transport-related datasets, detailed data-driven mobility analysis is becoming possible. Trips with their origins, destinations, and travel times are now collected in publicly available databases, allowing for demand forecasting methods exploiting big accurate data. In this paper, we predict pattern New York City bikes a low-dimensional approach utilizing three-level data clustering. We use historical along temperature precipitation to first aggregate...

Two-sided mobility platforms, such as Uber and Lyft, widely emerged in the urban landscape. Distributed supply of individual drivers, matched with travellers via intermediate platform yields a new class phenomena not present before. Such disruptive changes to transportation systems call for simulation framework where researchers from various across disciplines may introduce models aimed at representing complex dynamics platform-driven mobility. In this work, we MaaSSim, lightweight...

Contrary to traditional transit services, supply in ridesourcing systems emerges from individual labour decisions of gig workers. The effect decentralisation on the evolution on-demand services is largely unknown. To this end, we propose a dynamic model comprising subsequent supply-side processes: (i) initial exposure information about platform, (ii) long-term registration decision, and (iii) daily participation decisions, subject day-to-day learning based within-day matching outcomes. We...

Abstract Before the pandemic, ride-pooling was a promising mode of urban mobility, marked by increasing service providers and traveller adoption, critical to its efficiency sustainability. However, COVID-19 pandemic caused significant disruption, with services suspended, business models altered, reduced confidence. In post-pandemic era, understanding future is crucial. This article reviews market through literature, pooling availability, behaviour studies. We find that core elements model...

Sharing rides in on-demand systems allow passengers to reduce their fares and service providers increase revenue, though at the cost of adding uncertainty system. Notably, ride-pooling stems not only from travel times but also unique features sharing, such as dependency on other passengers' arrival time pick up points. In this work, we theoretically experimentally analyse how late arrivals locations impact shared rides' performance. We find that total delay is equally distributed among...

Emerging on-demand sharing alternatives, in which one resource is utilised simultaneously by a circumstantial group of users, entail several challenges regarding how to coordinate such users. A very relevant case refers form groups mobility system that offers shared rides, and split the costs within travellers group. These are non-trivial tasks, as two objectives conflict: 1) minimising total system, 2) finding an equilibrium where each user content with her assignment. Aligning both...

We demonstrate how digital traces of city-bike trips may become useful to identify urban space attractiveness. exploit their unique feature – stopovers: short, non-traffic-related stops made by cyclists during trips. As we with the case study Kraków (Poland), when applied a big dataset, meaningful patterns appear, hotspots (places long and frequent stopovers) identified at both top tourist leisure attractions as well emerging new places. propose generic method, applicable any spatiotemporal...

The objective of this paper is to understand the consequences providing real-time information on crowding levels (RTI-CL) in public transport networks. We propose extend mesoscopic, simulation-based assignment model with passengers' knowledge instantaneous onboard vehicles. illustrate results a sample transit network, where we investigate arising changes network performance and journey experience as result RTI-CL provision. demonstrate that effects en-route path choices strongly related...

The size of the solution space associated with trip-matching problem has made search for high-order ride-pooling prohibitive. We introduce hyper-pooled rides along a method to identify them within urban demand patterns. Travellers walk common pick-up points, travel shared vehicle sequence stops and are dropped off at from which they their destinations. While closely resembling classical mass transit, purely demand-driven, itineraries (stop locations, sequences, timings) optimised all...

In this study, we set out to explore how various spatial patterns of travel demand drive the effectiveness ride-pooling services. To do so, generate a broad range synthetic, yet plausible patterns. We experiment with number attraction centres, dispersion destinations around these and trip length distribution. apply strategic algorithm across generated identify shareability potential using series metrics related ridepooling. Our findings indicate that, under fixed level, vehicle-hour...

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, not only appealing for platforms and their travellers, but also promoting the sustainability of urban systems. Yet, potential ride-pooling rides serve as safe effective given personal public health risks considerations associated with COVID-19 hitherto unknown. To answer this, we combine epidemiological behavioural...