Traffic Simulation with SUMO – Simulation of Urban Mobility

Krajzewicz, Daniel

doi:10.1007/978-1-4419-6142-6_7

Cited by 373 publications

(298 citation statements)

References 5 publications

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“…26 Barrios and Godier (16), for example, evaluated three different rebalancing strategies (zero, pe-27 riodic and continuous redistribution) for MOD systems. This evaluation was performed for both 28 station-based (i.e. vehicles can be picked-up and dropped-off only at predefined stations) and free-29 floating (i.e.…”

Section: Introductionmentioning

confidence: 99%

Microsimulation of Demand and Supply of Autonomous Mobility On Demand

Azevedo

Marczuk

Raveau

et al. 2016

Transportation Research Record: Journal of the Transportation R

106

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Agent-based models have gained wide acceptance in transportation planning because with increasing computational power, large-scale people-centric mobility simulations are possible. Several modeling efforts have been reported in the literature on the demand side (with sophisticated activity-based models that focus on an individual’s day activity patterns) and on the supply side (with detailed representation of network dynamics through simulation-based dynamic traffic assignment models). This paper proposes an extension to a state-of-the-art integrated agent-based demand and supply model—SimMobility—for the design and evaluation of autonomous vehicle systems. SimMobility integrates various mobility-sensitive behavioral models in a multiple time-scale structure comprising three simulation levels: ( a) a long-term level that captures land use and economic activity, with special emphasis on accessibility; ( b) a midterm level that handles agents’ activities and travel patterns; and ( c) a short-term level that simulates movement of agents, operational systems, and decisions at a microscopic granularity. In that context, this paper proposes several extensions at the short-term and midterm levels to model and simulate autonomous vehicle systems and their effects on travel behavior. To showcase these features, the first-cut results of a hypothetical on-demand service with autonomous vehicles in a car-restricted zone of Singapore are presented. SimMobility was successfully used in an integrated manner to test and assess the performance of different autonomous vehicle fleet sizes and parking station configurations and to uncover changes in individual mobility patterns, specifically in regard to modal shares, routes, and destinations.

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Section: Introductionmentioning

confidence: 99%

Microsimulation of Demand and Supply of Autonomous Mobility On Demand

Azevedo

Marczuk

Raveau

et al. 2016

Transportation Research Record: Journal of the Transportation R

106

View full text Add to dashboard Cite

show abstract

“…SUMO is an open source, microscopic, continuous-space, discrete-time road traffic simulator developed by Institute of Transportation Systems at the German Aerospace Center [34] and adopted as our traffic simulator. OMNET++ [35] is an open-source, componentbased simulation package and captures the wireless communication simulation in VENTOS.…”

Section: Simulation Studymentioning

confidence: 99%

Platoon management with cooperative adaptive cruise control enabled by VANET

Amoozadeh

Deng

Chuah

et al. 2015

Vehicular Communications

289

147

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TitlePlatoon management with cooperative adaptive cruise control enabled by VANET AbstractPrevious studies have shown the ability of vehicle platooning to improve highway safety and throughput. With Vehicular Ad-hoc Network (VANET) and Cooperative Adaptive Cruise Control (CACC) system, vehicle platooning with small headway becomes feasible. In this paper, we developed a platoon management protocol for CACC vehicles based on wireless communication through VANET. This protocol includes three basic platooning maneuvers and a set of micro-commands to accomplish these maneuvers. Various platooning operations such as vehicle entry and vehicle (including platoon leader) leaving can be captured by these basic platoon maneuvers. The protocol operation is described in detail using various Finite State Machines (FSM), and can be applied in collaborative driving and intelligent highway systems. This protocol is implemented in an integrated simulation platform, VENTOS, which is developed based on SUMO and OMNET++. The validity and effectiveness of our approach is shown by means of simulations, and different platooning setting are calibrated.

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“…Default simulation step length is 1 s. Internally, the vehicle's position is recorded by lane number and distance from the beginning of the current lane. SUMO uses a car following model [31] by default and also supports a lane-change model [32]. Simulations can be run from command line application or can be visualized with a graphical application using openGL.…”

Section: Simulation Of Urban Mobilitymentioning

confidence: 99%

Comparison of clustering techniques for traffic accident detection

Dogru¹,

Subaşı²

2015

Turk J Elec Eng & Comp Sci

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Transportation infrastructure in intelligent transportation systems (ITSs) is complemented with information and communication technologies to achieve better passenger safety and reduced transportation time, fuel consumption, and vehicle wear and tear. This paper shows how data mining techniques are used in ITSs for accident detection and prevention on motorways. In traffic, vehicles show similar behavior to that of vehicles in closed neighborhoods. Vehicles that show different behaviors than neighbor vehicles in cases like accidents, inappropriate lane changes, and speeding can be considered as anomalies and detected. In this paper, a traffic accident is simulated and the effectiveness of different clustering techniques is examined for detecting traffic accident. We show that if velocity and position values of each vehicle are given, vehicles' behavior can be analyzed and accidents can be detected easily. The success of the proposed algorithms is demonstrated in a highway scenario by means of simulations. Simulations showed that data mining tools successfully detected accidents with an average accident detection rate of 100% and a false alarm rate of 0% using DBSCAN and hierarchical clustering.

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Traffic Simulation with SUMO – Simulation of Urban Mobility

Cited by 373 publications

References 5 publications

Microsimulation of Demand and Supply of Autonomous Mobility On Demand

Microsimulation of Demand and Supply of Autonomous Mobility On Demand

Platoon management with cooperative adaptive cruise control enabled by VANET

Comparison of clustering techniques for traffic accident detection

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