scholarly journals Evaluation Method for Estimating Change in Life Cycle Carbon Dioxide Due to Improvement of Transport Systems Using Microscopic Traffic Flow Simulation

2013 ◽  
Vol 69 (5) ◽  
pp. I_97-I_105
Author(s):  
Ryoko MORIMOTO ◽  
Shingo MANO ◽  
Nozomi KUDO ◽  
Naoki SHIBAHARA ◽  
Hirokazu KATO ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Life Cycle ◽  
Traffic Flow ◽  
Evaluation Method ◽  
Flow Simulation ◽  
Transport Systems ◽  
Traffic Flow Simulation

scholarly journals Method of estimating the change in life cycle CO2 due to transport system development incorporating micro-traffic flow simulation

2020 ◽  
Vol 48 ◽  
pp. 2074-2082
Author(s):  
Naoki Shibahara ◽  
Ryoko Morimoto ◽  
Nozomi Kudo ◽  
Hirokazu Kato ◽  
Shingo Mano ◽  
...  
Keyword(s):  
Life Cycle ◽  
Traffic Flow ◽  
Transport System ◽  
System Development ◽  
Flow Simulation ◽  
Traffic Flow Simulation

Report on design of modules for the stochastic traffic simulation

2021 ◽  
Author(s):  
Christian Siebke ◽  
◽  
Maximilian Bäumler ◽  
Madlen Ringhand ◽  
Marcus Mai ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Main Part ◽  
Traffic Simulation ◽  
Cognitive Structure ◽  
Flow Simulation ◽  
Road User ◽  
The Road ◽  
Traffic Flow Simulation ◽  
Cognitive Behaviour ◽  
Traffic Simulations

As part of the AutoDrive project, OpenPASS is used to develop a cognitive-stochastic traffic flow simulation for urban intersection scenarios described in deliverable D1.14. The deliverable D4.20 is about the design of the modules for the stochastic traffic simulation. This initially includes an examination of the existing traffic simulations described in chapter 2. Subsequently, the underlying tasks of the driver when crossing an intersection are explained. The main part contains the design of the cognitive structure of the road user (chapter 4.2) and the development of the cognitive behaviour modules (chapter 4.3).

scholarly journals Effectiveness of Information from Vehicles beyond Nearest Vehicle Ahead for Traffic Flow

2011 ◽  
Vol 2011 ◽  
pp. 1-7
Author(s):  
Hikaru Shimizu ◽  
Sho Nishiyama ◽  
Yukiko Wakita ◽  
Eisuke Kita
Keyword(s):  
Stability Analysis ◽  
Traffic Flow ◽  
Flow Simulation ◽  
The Other ◽  
Stable Region ◽  
Model Parameters ◽  
Model Stability ◽  
Acceleration Rate ◽  
Traffic Flow Simulation ◽  
Vehicle Acceleration

A driver usually controls the vehicle according to only the information from the nearest leader vehicle. If the information from the other leader vehicles is also available, the driver can control the vehicle more adequately. The aim of this study is to discuss the effectiveness of the information from the other leader vehicles than the nearest one for the traffic flow. For this purpose, the traffic flow is modeled by using the Chandler-type multi-vehicle-following model. This model changes the vehicle acceleration rate according to the velocity differences between the vehicle and its multileader vehicles. After the model stability analysis, the traffic flow simulation is performed. The results reveal that the stable region of the model parameters expands according to the increase of the number of the leader vehicles.

Sign in / Sign up

Export Citation Format

Share Document