Efficient Origin-Destination Estimation Using Microscopic Traffic Simulation with Restricted Rerouting

Traffic simulators are utilized to solve a variety of traffic-related problems.For such simulators,origin-destination(OD)traffic volumes as mobility demands are required to input,and we need to estimate them.The authors regard an OD estimation as a bi-level programming problem,and apply a microscopic traffic simulation model to it.However,the simulation trials can be computationally expensive if full dynamic rerouting is allowed,when employing multi-agent-based models in the estimation process.This paper proposes an efficient OD estimation method using a multi-agent-based simulator with restricted dynamic rerouting to reduce the computational load.Even though,in the case of large traffic demand,the restriction on dynamic rerouting can result in heavier congestion.The authors resolve this problem by introducing constraints of the bi-level programming problem depending on link congestion.Test results show that the accuracy of the link traffic volume reproduced with the proposed method is virtually identical to that of existing methods but that the proposed method is more computationally efficient in a wide-range or high-demand context.

Microscopic Fuzzy Urban Traffic Simulation with Variable Demand

Some microscopic traffic simulations on urban road network are developed up to now. However, the effect of urban transport policy in the local city is influenced with the complex interaction of automobile traffic and public transport traffic. Particularly, behaviours of vehicles should be described with the fuzziness of the subjective recognition and operation. On the other hand, the trip makers are influenced by various transport policies in terms of mode choice behaviour. The change in mode choice behaviour and number of public transport mode users would eventually affect traffic flow conditions on road network. Modal spilt and traffic conditions of a network are interrelated. Therefore, the present study mainly aims to integrate mode choice model and microscopic traffic simulation model based on fuzzy logic. In the study, the fuzzy logic based mode choice model is proposed. The proposed mode choice model and the existing microscopic traffic simulation model are combined. The developed model has been applied on real urban network to demonstrate the effectiveness of the installation of LRT system. Finally, it is helpful for evaluation of transport policy that the fuzzy logic based microscopic traffic simulation with modal choice model has been constructed.

Traffic organization during urban road constructions

This research presented a bi-level programming approach to optimize the schedule of ur- ban road construction activities based on a hypothetical transport network, with an objective of mini- mizing the overall traffic delays. A heuristic algorithm was utilized to identify a set of road construction schedules, while PARAMICS was adopted to estimate the total travel time in the network under each road construction scenario. To test the performance of proposed heuristics-simulation methodology, a numerical test was implemented. The overall results suggested that the proposed methodol- ogy could quickly find the optimum solution with good convergence.

Sensitivity Analysis of Key Input Parameters in Microscopic Simulation of Congested and Uncongested Arterial Signals

This study involved investigating the sensitivity of Measures of Effectiveness （MOEs） to different simulation initialization time （7, 10, and 13 minutes）; observing the trend of variation of MOEs with increasing simulation runs; and identifying the major contributors of variation in MOEs using CORSIM and SimTraffic. The results showed that （1） the MOEs of a simulated intersection approaches were indeed sensitive to initialization times; （2） the variation within MOEs reached a steady state with increased number of simulation runs, while CORSIM required at least 50 simulation runs, SimTraffic required even higher number of runs for congested approaches; （3） lane changing and gap acceptance parameters play a major role as a source of variation of MOEs （delay/vehicle） in CORSIM and SimTraffic respectively.

Study on the Signal Control System of Urban Traffic with a Genetic Algorithm

In the paper the aim and meaning of traffic microscopic simulation is discussed first, and then three sub-models of the system are established, e. i. the model for random generation of the vehicles, the model for car-following and lane change influenced by an adjacent vehicle, and the model for control and optimization of intersection with signal. Optimization of the traffic signal timing with a genetic algorithm and a microscopic simulation is carried out. It represents a novel approach to solving optimal signal timing.

Investigating the impacts of urban speed limit reduction through microscopic traffic simulation

Road traffic congestion has become an everyday phenomenon in today's cities all around the world.The reason is clear:at peak hours,the road network operates at full capacity.In this way,growing traffic demand cannot be satisfied,not even with traffic-responsive signal plans.The external impacts of traffic congestion come with a serious socio-economic cost:air pollution,increased travel times and fuel consumption,stress,as well as higher risk of accidents.To tackle these problems,a number of European cities have implemented reduced speed limit measures.Similarly,a general urban speed limit measure is in preparatory phase in Budapest,Hungary.In this context,a complex preliminary impact assessment is needed using a simulated environment.Two typical network parts of Budapest were analyzed with microscopic traffic simulations.The results revealed that speed limits can affect traffic differently in diverse network types indicating that thorough examination and preparation works are needed prior to the introduction of speed limit reduction.