arXiv subjects

Farnoud Ghasemi

Publications and source records attributed to Farnoud Ghasemi.

8 recordsLinked to original sources

arXiv2026

Demand-agnostic assessment of on-demand pooled transit services

This study proposes a method to assess the potential of pooled on-demand transit feeder services in urban areas where demand is not yet known. We introduce the fraction of demand, reflecting the probability that a resident will use the service. Demand is generated on the distribution of residents address points at varying demand fraction levels. Through simulations, we match travellers into pooled rides and evaluate the service potential using three performance indicators (KPIs). We observe how these KPIs change with varying demand fractions and identify the most promising hub for each area. By setting KPI thresholds, we select the optimal combination of area and hub that meets these thresholds at the lowest demand fraction. This approach provides municipalities with a structured tool for pre-deployment evaluation, helping them choose the most suitable areas for launching new services despite the absence of exact demand data. We illustrate its application through a case study in Krakow, ranking 12 pre-selected areas for feeder service deployment.

physics.soc-ph↗

arXiv2025

Regulating Ride-Sourcing Markets: Can Minimum Wage Regulation Protect Drivers Without Disrupting the Market?

Ride-sourcing platforms such as Uber and Lyft are prime examples of the gig economy, recruiting drivers as independent contractors, thereby avoiding legal and fiscal obligations. Although platforms offer flexibility in choosing work shifts and areas, many drivers experience low income and poor working conditions, leading to widespread strikes and protests. Minimum wage regulation is adopted to improve drivers welfare. However, the impacts of this regulation on drivers as well as on travelers and platforms, remain largely unknown. While ride-sourcing platforms do not disclose the relevant data, state-of-the-art models fail to explain the effects of minimum wage regulation on market dynamics. In this study, we assess the effectiveness and implications of minimum wage regulation in ride-sourcing markets while simulating the detailed dynamics of ride-sourcing markets under varying regulation intensities, both with and without the so-called platform lockout strategy. Our findings reveal that minimum wage regulation impacts substantially drivers income, and may lead to higher fares for travelers and threaten platforms survival. When platforms adopt a lockout strategy, their profitability significantly improves and drivers earn more, although many others lose their jobs, and service level for travelers consequently declines.

cs.ET↗

arXiv2025

SimFLEX: a methodology for comparative analysis of urban areas for implementing new on-demand feeder bus services

On-demand feeder bus services present an innovative solution to urban mobility challenges, yet their success depends on thorough assessment and strategic planning. Despite their potential, a comprehensive framework for evaluating feasibility and identifying suitable service areas remains underdeveloped. Simulation Framework for Feeder Location Evaluation (SimFLEX) uses spatial, demographic, and transport-specific data to run microsimulations and compute key performance indicators (KPIs), including service attractiveness, waiting time reduction, and added value. SimFLEX employs multiple replications to estimate demand and mode choices and integrates OpenTripPlanner (OTP) for public transport routing and ExMAS for calculating shared trip attributes and KPIs. For each demand scenario, we model the traveler learning process using the method of successive averages (MSA), stabilizing the system. After stabilization, we calculate KPIs for comparative and sensitivity analyzes. We applied SimFLEX to compare two remote urban areas in Krakow, Poland - Bronowice and Skotniki - the candidates for service launch. Our analysis revealed notable differences between analyzed areas: Skotniki exhibited higher service attractiveness (up to 30%) and added value (up to 7%), while Bronowice showed greater potential for reducing waiting times (by nearly 77%). To assess the reliability of our model output, we conducted a sensitivity analysis across a range of alternative-specific constants (ASC). The results consistently confirmed Skotniki as the superior candidate for service implementation. SimFLEX can be instrumental for policymakers to estimate new service performance in the considered area, publicly available and applicable to various use cases. It can integrate alternative models and approaches, making it a versatile tool for policymakers and urban planners to enhance urban mobility.

physics.soc-ph↗

arXiv2024

Optimizing Ride-Pooling Revenue: Pricing Strategies and Driver-Traveller Dynamics

Ride-pooling, to gain momentum, needs to be attractive for all the parties involved. This includes also drivers, who are naturally reluctant to serve pooled rides. This can be controlled by the platform's pricing strategy, which can stimulate drivers to serve pooled rides. Here, we propose an agent-based framework, where drivers serve rides that maximise their utility. We simulate a series of scenarios in Delft and compare three strategies. Our results show that drivers, when they maximize their profits, earn more than in both the solo-rides and only-pooled rides scenarios. This shows that serving pooled rides can be beneficial as well for drivers, yet typically not all pooled rides are attractive for drivers. The proposed framework may be further applied to propose discriminative pricing in which the full potential of ride-pooling is exploited, with benefits for the platform, travellers, and (which is novel here) to the drivers.

cs.MA↗

arXiv2023

Spatiotemporal variability of ride-pooling potential -- half a year New York City experiment

Ride-pooling systems, despite being an appealing urban mobility mode, still struggle to gain momentum. While we know the significance of critical mass in reaching system sustainability, less is known about the spatiotemporal patterns of system performance. Here, we use 1.5 million NYC taxi trips (sampled over a six-month period) and experiment to understand how well they could be served with pooled services. We use a utility-driven ride-pooling algorithm and observe the pooling potential with six performance indicators: mileage reductions, travellers' utility gains, share of pooled rides, occupancy, detours, and potential fleet reduction. We report distributions and temporal profiles of about 35 thousand experiments covering weekdays, weekends, evenings, mornings, and nights. We report complex spatial patterns, with gains concentrated in the core of the network and costs concentrated on the peripheries. The greatest potential shifts from the North in the morning to the Central and South in the afternoon. Offering pooled rides at the fare 32% lower than private ride-hailing seems to be sufficient to attract pooling yet dynamically adjusting it to the demand level and spatial pattern may be efficient. The patterns observed in NYC were replicated on smaller datasets in Chicago and Washington, DC, the occupancy grows with the demand with similar trends.

physics.soc-ph↗

arXiv2023

Dynamics of the Ride-Sourcing Market: A Coevolutionary Model of Competition between Two-Sided Mobility Platforms

There is a fierce competition between two-sided mobility platforms (e.g., Uber and Lyft) fueled by massive subsidies, yet the underlying dynamics and interactions between the competing plat-forms are largely unknown. These platforms rely on the cross-side network effects to grow, they need to attract agents from both sides to kick-off: travellers are needed for drivers and drivers are needed for travellers. We use our coevolutionary model featured by the S-shaped learning curves to simulate the day-to-day dynamics of the ride-sourcing market at the microscopic level. We run three scenarios to illustrate the possible equilibria in the market. Our results underline how the correlation inside the ride-sourcing nest of the agents choice set significantly affects the plat-forms' market shares. While late entry to the market decreases the chance of platform success and possibly results in "winner-takes-all", heavy subsidies can keep the new platform in competition giving rise to "market sharing" regime.

cs.MA↗

arXiv2023

Ride Acceptance Behaviour Investigation of Ride-sourcing Drivers Through Agent-based Simulation

Ride-sourcing platforms such as Uber and Lyft offer drivers (i.e., platform suppliers) considerable freedom of choice in multiple aspects. At the operational level, drivers can freely accept or decline trip requests that can significantly impact system performance in terms of travellers' waiting time, drivers' idle time and income. Despite the extensive research into the supply-side operations, the behavioural aspects, particularly drivers' ride acceptance behaviour remains so far largely unknown. To this end, we reproduce the dynamics of a two-sided mobility platform on the road network of Delft using an agent-based simulator. Then, we implement a ride acceptance decision model enabling drivers to apply their acceptance strategies. Our findings reveal that drivers who follow the decision model, on average, earn higher income compared to drivers who randomly accept trip requests. The overall income equality between drivers with the acceptance decision is higher and travellers experience lower waiting time in this setting.

cs.MA↗

arXiv2022

Modelling the Rise and Fall of Two-Sided Mobility Markets with Microsimulation

In this paper, we propose a novel modelling framework to reproduce the market entry strategies for two-sided mobility platforms. In the MaaSSim agent-based simulator, we develop a co-evolutionary model to represent day-to-day dynamics of the two-sided mobility market with agents making rational decisions to maximize their perceived utility. Participation probability of agents depends on utility, composed of: experience, word of mouth and marketing components adjusted by agents every day with the novel S-shaped formulas - better suited (in our opinion) to reproduce market entry dynamics than previous approaches. With such a rich representation, we can realistically model a variety of market entry strategies and create significant network effects to reproduce the rise and fall of two-side mobility platforms. To illustrate model capabilities, we simulate a 400-day evolution of 200 drivers and 2000 travelers on a road-network of Amsterdam. We design a six-stage market entry strategy with consecutive: kick-off, discount, launch, growth, maturity and greed stages. After 25 days the platform offers discounts, yet it starts gaining market share only when the marketing campaign launches at day 50. Campaign finishes after 50 days, which does not stop the growth, now fueled mainly with a positive word of mouth effect and experiences. The platform ends discounts after 200 days and reaches the steady maturity period, after which its greedy strategy leads to collapse of its market share and profit. All above simulated with a single behavioral model, which well reproduces how agents of both sides adapts to platform actions.

cs.MA↗