Demand Responsive Transit Simulation of Wayne County, Michigan

Kagho, Grace Orowo; Hensle, D.; Balać, Miloš; Freedman, Joel; Twumasi-Boakye, Richard; Broaddus, Andrea; Fishelson, James; Axhausen, Kay W.

doi:10.1177/03611981211031221

Cited by 16 publications

(15 citation statements)

References 29 publications

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“…For instance, the utility of DRT mode ( U DRT ) is calculated based on agents’ income level ( k ) and private car ownership ( l ) using Equation 1, where x denotes choice variables, and ρ and μ are alternative specific constants and marginal utility parameters, respectively. For a detailed description of DMC parameters used in this study, interested readers are referred to Kagho et al ( 18, 32 ).…”

Section: Methodsmentioning

confidence: 99%

Agent-Based Simulation Approach to Determine Safety Impacts of Demand-Responsive Transport (DRT) in Wayne County, Michigan

Feizi

Twumasi-Boakye

Djavadian

et al. 2022

Transportation Research Record: Journal of the Transportation R

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Road safety is one of the major concerns in transportation system management. Safety performance analyses usually assess crash frequencies and the impacts of countermeasures on the number of crashes. However, the advent of new mobility solutions makes safety evaluation more challenging; data tend to be sparse, and the impacts of such services on demand and the performance of the broader network is not completely understood. This paper attempts to fill this gap by creating a novel method to estimate the safety impacts of Demand-Responsive Transport (DRT) services. Using an agent-based mesoscopic model in the Multi-Agent Transport Simulation (MATSim) Toolkit, we simulate DRT as a new mobility solution in Wayne County, Michigan, and obtain spatial and temporal distributions of traffic volume and operating speed to predict the frequency and severity of crashes. We tested for different DRT service designs, such as fleet size, detour tolerance, and initial placement of the fleet. Our findings indicate that introducing a DRT service on its own increases vehicle kilometers traveled (VKT) by 22% and consequently the number of crashes by 17%. However, this impact could be ameliorated by increasing the detour tolerance, which can significantly increase the number of shared rides and decreases the crash frequency (10.8%) and crash severity as a result of a lower VKT (15%). The output of the proposed framework serves as a starting point of a safety performance evaluation using an agent-based simulation approach to achieve a safe and successful implementation of shared mobility services in large-scale urbanized areas.

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Section: Methodsmentioning

confidence: 99%

Agent-Based Simulation Approach to Determine Safety Impacts of Demand-Responsive Transport (DRT) in Wayne County, Michigan

Feizi

Twumasi-Boakye

Djavadian

et al. 2022

Transportation Research Record: Journal of the Transportation R

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“…On the other hand, some scholars argue that ride-pooling services might increase traffic congestion. For example, in their study of Demand Responsive Transit (DRT), Kagho et al [17] found that the introduction of such a service was likely to increase overall VKT slightly in Wayne County, Michigan. Another study conducted in the same area [18] confirmed this finding and concluded that the introduction of DRT can increase the VKT by 22%.…”

Section: Literature Reviewmentioning

confidence: 99%

“…To date, most studies on the impact of ride-pooling services have been conducted in cities/counties larger in population size than Birmingham metro area, which has a population of 0.89 million [29]. For instance, studies have been carried out in: Hangzhou, China [13] (8.24 million population [30]); Haikou City, China [14] (2.02 million population [30]); Berlin, Germany [15] (3.57 million population [30]); Santiago, Chile [16] (6.9 million population [30]); and Wayne County, Michigan [17,18] (1.77 million population [31]). Since the population size affects transportation demand, further research is needed to investigate how ride-pooling services affect the operational efficiency of the transportation system in medium-sized cities (population between 350,000-999,999).…”

Section: Literature Reviewmentioning

confidence: 99%

Operational Impacts of On-Demand Ride-Pooling Service Options in Birmingham, AL

Salman

Sisiopiku

Khalil

et al. 2023

Future Transportation

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Transportation Network Companies (TNCs) use online-enabled apps to provide on-demand transportation services. TNCs facilitate travelers to connect with drivers that can offer them rides for compensation using driver-owned vehicles. The ride requests can be for (a) individual or (b) shared rides. The latter, also known as ride-pooling services, accommodates requests of unrelated parties with origins and destinations along the same route who agree to share the same vehicle, usually at a discounted fare. Uber and Lyft offer ride-pooling services in select markets. Compared to individual ride requests, ride-pooling services hold better promise toward easing urban congestion by reducing the number of automobiles on the road. However, their impact on traffic operations is still not fully understood. Using Birmingham, AL as a case study, this research evaluated the impact that ride-pooling services have on traffic operations using a Multi-Agent Transport Simulation (MATSim) model of the Birmingham metro area. Scenarios were developed to simulate baseline conditions (no TNC service) and ride-pooling availability with two types of ride-pooling services, namely door-to-door (d2d) and stop-based (sB) service and three fleet sizes (200, 400, and 800 vehicles). The results indicate that when TNC vehicles are added to the network, the Vehicle Kilometers Traveled (VKT) decrease by up to 5.78% for the door-to-door (d2d) service, and up to 2.71% for stop-based (sB) services, as compared to the baseline scenario (no TNC service). The findings also suggest that an increase in the size of the ride-pooling fleet results in a rise in total ride-pooling service VKT, network-wide total VKT, and detour distance. However, increasing the size of the ride-pooling fleet also results in a decrease in the ride request rejection rates, thus benefiting the customers and decreasing the vehicle empty ratio which, in turn, benefits the TNC drivers. The results further suggest that a fleet of 200 ride-pooling vehicles can meet the current demand for service in the Birmingham region at all times, thus it is the optimal ride-pooling TNC fleet size for a medium-sized city such as Birmingham.

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“…With the advancement of DRT, the field trial of it is a welcome subject of empirical research (e.g.- [24]), but not so where market approval is still being sought. In view of the ambitious task in a rural setting and abovestated caveats, the lack of a manageable a priori assessment of sustainability still proves to be a weak point.…”

Section: A Case-related Sustainable Development Assessmentmentioning

confidence: 99%

“…3, is considered prototypical in terms of its peripheral location, polycentricity, and medium-to-low population density. The renewed (24) exp…”

Section: Investigation Area and Initial Quantity Structurementioning

confidence: 99%

Sustainable development assessment of incentive-driven shared on-demand mobility systems in rural settings

Heinitz

2022

Eur. Transp. Res. Rev.

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Background In the light of the sustainable development goals, a set of operationalizable criteria quantifying societal benefits versus costs is needed to prepare for the introduction of an incentive-driven, high adoption shared on-demand mobility service in a rural transportation area. Aiming to reduce still-existing uncertainty about the impacts of a market entry and to balance substantial monetary incentives for suppliers of pooled rides with the progress in net GHG emission reduction and accessibility gain, the framework is applicable at the transactional and/or aggregate level. Results The presented set of indicators is decision-oriented, and applicable both at the transactional and macro level. Scenarios and user choice situations for two regulatory options of demand responsive transport—one in line with the current legislation in Germany, avoiding overlap with existing fixed-route scheduled public transport and one not strictly complementary which assumes direct competition—are formalized. By the help of a case study, the outcome of the different organizational models at three levels of incentivization can be systematically compared. The implementation effort of the assessment method is examined in view of the forthcoming sustainability compliance reporting in this sector. Conclusions A system-optimal constrained public private DRT deployment offers the opportunity of a reduction of uneconomic routes and parallel services upon selection of eligible rides. As shown, a crowding out of existing, publicly financed offerings in an unsaturated mobility market should not be the primary concern. At the contrary, resorting to supply-side incentives, a proportion of the high volume of solo car trips could be consolidated while levels of service improve in total. However, this may be associated with considerable expense, as demonstrated by the quantity structure of the provided case study.

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Demand Responsive Transit Simulation of Wayne County, Michigan

Cited by 16 publications

References 29 publications

Agent-Based Simulation Approach to Determine Safety Impacts of Demand-Responsive Transport (DRT) in Wayne County, Michigan

Agent-Based Simulation Approach to Determine Safety Impacts of Demand-Responsive Transport (DRT) in Wayne County, Michigan

Operational Impacts of On-Demand Ride-Pooling Service Options in Birmingham, AL

Sustainable development assessment of incentive-driven shared on-demand mobility systems in rural settings

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