[Paper Review] The Impact of Ridesharing in Mobility-on-Demand Systems: Simulation Case Study in Prague

Davide Fiedler, Michal Čertický+2 more|arXiv (Cornell University)|Jul 5, 2018

Transportation and Mobility Innovations2 references4 citations

TL;DR

This study evaluates ridesharing in a mobility-on-demand (MoD) system for Prague using agent-based simulation, showing that with a 10-minute maximum travel delay, ridesharing increases average vehicle occupancy to 2.7 passengers and reduces vehicle miles traveled (VMT) to 35% of MoD without ridesharing and 60% of current private vehicle usage, significantly improving road network efficiency.

ABSTRACT

In densely populated-cities, the use of private cars for personal transportation is unsustainable, due to high parking and road capacity requirements. The mobility-on-demand systems have been proposed as an alternative to a private car. Such systems consist of a fleet of vehicles that the user of the system can hail for one-way point-to-point trips. These systems employ large-scale vehicle sharing, i.e., one vehicle can be used by several people during one day and consequently the fleet size and the parking space requirements can be reduced, but, at the cost of a non-negligible increase in vehicles miles driven in the system. The miles driven in the system can be reduced by ridesharing, where several people traveling in a similar direction are matched and travel in one vehicle. We quantify the potential of ridesharing in a hypothetical mobility-on-demand system designed to serve all trips that are currently realized by private car in the city of Prague. Our results show that by employing a ridesharing strategy that guarantees travel time prolongation of no more than 10 minutes, the average occupancy of a vehicle will increase to 2.7 passengers. Consequently, the number of vehicle miles traveled will decrease to 35% of the amount in the MoD system without ridesharing and to 60% of the amount in the present state.

Motivation & Objective

• To assess the potential of large-scale ridesharing in reducing vehicular traffic and vehicle miles traveled (VMT) in mobility-on-demand (MoD) systems.
• To evaluate how ridesharing affects road network utilization compared to private vehicles and MoD systems without ridesharing.
• To quantify the trade-off between travel delay and vehicle occupancy in a large-scale MoD environment.
• To analyze the impact of ridesharing on congestion levels and fleet efficiency in a real-world urban setting (Prague).

Proposed method

• Agent-based simulation of a hypothetical MoD system replacing all private vehicles in Prague.
• Three scenarios compared: current private vehicle usage, MoD without ridesharing, and MoD with ridesharing.
• Ridesharing strategy limits travel time prolongation to ≤10 minutes to ensure passenger comfort.
• Vehicle assignment uses a dynamic matching algorithm that groups passengers with similar routes.
• Traffic density and congestion levels are measured across the road network using critical density thresholds.
• Performance metrics include total VMT, average vehicle occupancy, and number of congested/loaded road segments.

Experimental results

Research questions

• RQ1 To what extent can ridesharing reduce vehicle miles traveled (VMT) in a large-scale MoD system compared to private vehicles and MoD without ridesharing?
• RQ2 How does a maximum travel delay of 10 minutes affect vehicle occupancy and system efficiency?
• RQ3 What is the impact of ridesharing on road network congestion and traffic density in a real urban environment like Prague?
• RQ4 How does the utilization of road infrastructure compare across the three scenarios in terms of congested and heavily loaded segments?

Key findings

• With a 10-minute maximum travel delay, ridesharing increases average vehicle occupancy to 2.7 passengers per vehicle, up from 0.7 in MoD without ridesharing.
• Total vehicle miles traveled (VMT) in the MoD system with ridesharing is reduced to 35% of the VMT in the MoD system without ridesharing.
• VMT in the ridesharing-enabled MoD system is only 60% of the VMT in the current private vehicle scenario.
• The number of congested road segments (above critical density) drops from 14 (private vehicles) to 4 in the ridesharing MoD scenario.
• The number of heavily loaded segments (above 50% of critical density) decreases from 208 (private vehicles) to 35 in the ridesharing MoD system.
• The average distance traveled per vehicle is reduced to 10.8 km in the ridesharing MoD system, compared to 30.5 km in MoD without ridesharing.