Shared Mobility

An Approximate Analytic Model of Many-to-Many Demand Responsive Transportation Systems

Daganzo, Carlos F.
1978

This paper presents an analytic model to predict average waiting and ridingtimes in urban transportation systems (such as dial-a-bus and taxicabs), which provide non-transfer door-to-door transportation with a dynamically dispatched fleet of vehicles. Three different dispatching algorithms are analyzed with a simple deterministic model, which is then generalized to capture the most relevant stochastic phenomena. The formulae obtained have been successfully compared with simulated data and are simple enough for hand calculation. They are, thus, tools which enable analysts to avoid...

Checkpoint Dial-a-Ride Systems

Daganzo, Carlos F.
1984

This paper presents a preliminary study of the feasibility of checkpoint dial-a-ride systems. Their cost-effectiveness is compared to that of fixed route systems with no transfers and door-to-door dial-a-ride systems. The results are derived for a simple routing strategy, and involve some simplifications which facilitate the comparisons. For high demand levels, the total cost per passenger for fixed route and checkpoint systems is very close. In fact, their optimal configurations are so alike, and the occurrence of route deviations is so rare, that fixed route systems should be preferred,...

A General Model of Ridesharing Services

Ouyang, Yanfeng
Daganzo, Carlos F.
2018

The paper presents a general analytic framework to model transit systems that provide door-to-door service. The model includes as special cases non-shared taxi and demand responsive transportation (DRT). In the latter we include both, paratransit services such as dial-a-ride (DAR), and the form of ridesharing (shared taxi) currently being used by crowd-sourced taxi companies like Lyft and Uber. The framework yields somewhat optimistic results because, among other things, it is deterministic and does not track vehicles across space. By virtue of its simplicity however, the framework yields...

A General Model of Demand-Responsive Transportation Services: From Taxi to Ridesharing to Dial-A-Ride

Daganzo, Carlos F.
Ouyang, Yanfeng
2019

The paper presents a general analytic framework to model transit systems that provide door-to-door service. The model includes as special cases non-shared taxi and demand responsive transportation (DRT). In the latter we include both, paratransit services such as dial-a-ride (DAR), and the form of ridesharing (shared taxi) currently being used by crowd-sourced taxi companies like Lyft and Uber. The framework yields somewhat optimistic results because, among other things, it is deterministic and does not track vehicles across space. By virtue of its simplicity, however, the framework yields...

Analysis of ride-sharing with service time and detour guarantees

Daganzo, Carlos F.
Ouyang, Yanfeng
Yang, Haolin
2020

This paper explores whether upper bound guarantees to detour distances can be introduced in ride sharing services. By ride sharing we mean taxi ride aggregation services such as Uber-Pool. The paper develops an analytical model that for a given demand relates the guarantee levels to (i) the percent of rides that can be matched, (ii) the expected vehicle distance traveled; (iii) the expected passenger distance traveled; (iv) the fleet size required, and (v) the average passenger trip time including waiting and riding. The formulas developed reveal that for the full range of feasible fleet...

Performance of Reservation-based Carpooling Services Under Detour and Waiting Time Restrictions

Ouyang, Yanfeng
Yang, Haolin
Daganzo, Carlos F.
2021

This paper examines many-to-many carpooling services with advance reservations, and constraints on waits and detours. An analytic model yields approximate formulas for the percent of requests matched, the expected vehicle-distance driven, and the passenger-distance traveled in some idealized scenarios. Simulations of these scenarios validate the formulas. In the most favorable cases carpooling reduces the vehicle-kilometers driven by all users by a few percent. The paper also shows how the formulas can be used by service providers to optimize offerings, and by city governments to design...

Spatio-temporal Road Charge: A Potential Remedy for Increasing Local Streets Congestion

Bayen, Alexandre M.
Forscher, Teddy
2017

US population. Additionally, the emergence of large ridesourcing or transportation network companies (TNCs) totaling up to tens of thousands of registered drivers in single cities (all using the same routing app), there is further consolidation. Across the US, this has led to new or increased congestion patterns that are progressively asphyxiating local streets due to so-called “cut-through traffic.” As neighborhoods have started to realize this, private citizens have begun to resist, by trying to sabotage or trick the apps, or shaming the through traffic through opinion articles, and news...

Privacy-Preserving MaaS Fleet Management

Belletti, Francois
Bayen, Alexandre M.
2017

On-demand traffic fleet optimization requires operating Mobility as a Service (MaaS) companies such as Uber, Lyft to locally match the offer of available vehicles with their expected number of requests referred to as demand (as well as to take into account other constraints such as driver’s schedules and preferences). In the present article, we show that this problem can be encoded into a Constrained Integer Quadratic Program (CIQP) with block independent constraints that can then be relaxed in the form of a convex optimization program. We leverage this particular structure to yield a...

Resiliency of Mobility-as-a-Service Systems to Denial-of-Service Attacks

Thai, Jérôme
Yuan, Chenyang
Bayen, Alexandre M.
2018

Mobility-as-a-Service (MaaS) systems, such as ride-sharing services, have expanded very quickly over the past years. However, the popularity of MaaS systems make them increasingly vulnerable to denial-of-service (DOS) attacks, in which attackers attempt to disrupt the system to make it unavailable to the customers. Expanding on an established queuing-theoretical model for MaaS systems, attacks are modeled as a malicious control of a fraction of vehicles in the network. We then formulate a stochastic control problem that maximizes the passenger loss in the network in steady state, and solve...

Privacy-preserving MaaS fleet management

Belletti, Francois
Bayen, Alexandre M.
2018

On-demand traffic fleet optimization requires operating Mobility as a Service (MaaS) companies such as Uber, Lyft to locally match the offer of available vehicles with their expected number of requests referred to as demand (as well as to take into account other constraints such as driver’s schedules and preferences). In the present article, we show that this problem can be encoded into a Constrained Integer Quadratic Program (CIQP) with block independent constraints that can then be relaxed in the form of a convex optimization program. We leverage this particular structure to yield a...