1In this paper we present the development of an integrated microscopic mobility simulator, 2 SimMobility Short-Term (ST). "Integrated" as its models, inputs and outputs, simulated components and 3 code-base are integrated within a multi-scale agent-and activity-based simulation platform capable of 4 simulating different spatial-temporal resolutions and account for different levels of travelers' decision 5 making. "Microscopic" as both the demand -agents and its trips -and the supply -trip realization and 6 movements on the network -are microscopic, i.e. modeled individually. Finally, "Mobility", as it copes 7with the multimodal nature of urban networks and the need for the flexible simulation of innovative 8 transportation services such as on-demand and smart mobility solutions. This paper follows previous 9 publications that describe SimMobility's overall framework and models. SimMobility is a multi-scale 10 platform that considers land-use, transportation, and mobility-sensitive behavioral models. SimMobility ST 11 aims at simulating the high-resolution movement of agents (traffic, transit, pedestrians and goods) and the 12 operation of different mobility services and control and information systems.
Capacity drop, which is defined as discharge flow drop after bottleneck activation, has been frequently observed on urban highways, especially in merging sections. Maintaining high capacity on roadways is a main concern for traffic operators, theorists, and transportation modelers. Accordingly, many researchers have investigated capacity drop, yet highway capacity and discharge flow measurement methods vary, and results are not comparable. A systematic methodology is introduced for finding capacity drops by using detector data to estimate roadway capacity and discharge flow. The impact of the number of lanes on capacity drops at merging sections on highways is investigated. Results show that capacity drop is negatively related to the number of lanes. Detailed information is analyzed for individual lanes and off-ramp effect on capacity drop. Individual lane analysis supports the negative relationship between the amount of capacity drop and the number of lanes. A decrease in capacity drop is observed when the flow ratio of the off-ramp increases.
Recent advancements in automated vehicle technology and the concurrent emergence of ride-hailing services have focused increasing attention on Automated Mobility-on-Demand (AMOD; a system of shared driverless taxis) as a potential solution for sustainable future urban mobility. However, the impacts of an unrestricted deployment of AMOD are as yet uncertain and likely to be contextspecific; evidence with existing on-demand services suggests that they may lead to the cannibalization of mass-transit and increased traffic congestion. In this context, automated demand-responsive transit (also termed microtransit), which provides similar on-demand services (stop-to-stop or curbside) through higher capacity vehicles, may prove to be a promising substitute and/or complement. In this study, we evaluate the performance of such an automated demand response transit system (hereafter AMOD minibus) through agent-based simulations of the Singapore network. Towards this end, we extend SimMobility (an agentand activity-based microsimulation laboratory) with the capability of modeling an AMOD minibus service including demand, supply and their interactions. On the demand side, we use an activity-based model system that draws on data from a stated-preferences survey conducted in Singapore. On the supply side, an insertion heuristic is applied to dynamically perform both the assignment of requests to vehicles and vehicle routing. Scenario simulations on the Singapore network (with an area-wide deployment of the AMOD services) indicate the potential benefits of an automated demand responsive transit service for local circulation, which can result in a reduction of Vehicle Kilometres Traveled of up to 50% (compared to the AMOD shared taxis) whilst satisfying the same demand, with a modest increase in average travel times. INDEX TERMS Agent-based simulation, automated mobility-on-demand (AMOD), high-capacity ridesharing, shareability.
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