Comparing Measured Driver Behavior Distributions to Results from Car-Following Models using SUMO and Real-World Vehicle Trajectories from Radar
In this study, the physical principles governing car-following (CF) behavior and their impact on traffic flow at signalized intersections are investigated. High temporal-resolution radar data is used to provide valuable insights into actual CF behavior, including acceleration, deceleration, and tim...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
TIB Open Publishing
2023-06-01
|
| Series: | SUMO Conference Proceedings |
| Subjects: | |
| Online Access: | https://www.tib-op.org/ojs/index.php/scp/article/view/214 |
| _version_ | 1797730893160251392 |
|---|---|
| author | Max Schrader Mahdi Al Abdraboh Joshua Bittle |
| author_facet | Max Schrader Mahdi Al Abdraboh Joshua Bittle |
| author_sort | Max Schrader |
| collection | DOAJ |
| description |
In this study, the physical principles governing car-following (CF) behavior and their impact on traffic flow at signalized intersections are investigated. High temporal-resolution radar data is used to provide valuable insights into actual CF behavior, including acceleration, deceleration, and time headway distribution. Demand-calibrated SUMO simulations are run using empirical CF parameter distributions, and three CF models are evaluated: IDM, EIDM, and Krauss. By emulating radar data in SUMO and processing simulated vehicle traces, discrepancies between empirical and simulated parameter distributions are identified. Further analysis includes comparisons with default SUMO CF model parameters. The findings reveal that measured accelerations differ from CF model parameter accelerations and using the empirical value ($\mu = 0.89m/s^2$) leads to unrealistic simulations that fail volume-based calibration. Default parameters for all three models reasonably approximate the mean and median of measured parameters, but fail to capture the true distribution shape, partly due to homogeneity when using default parameters. The results show that it is more effective to simulate with the default parameters provided by SUMO rather than using measurements of real-world distributions without additional calibration. Future work will investigate closing the loop between the measured real-world and SUMO distributions using traditional calibration tactics, as well as assess the impact of calibrated vs. default CF parameters on simulation outputs like fuel consumption.
|
| first_indexed | 2024-03-12T11:50:47Z |
| format | Article |
| id | doaj.art-a424f68554cc4e889d16f92d96ae129f |
| institution | Directory Open Access Journal |
| issn | 2750-4425 |
| language | English |
| last_indexed | 2024-03-12T11:50:47Z |
| publishDate | 2023-06-01 |
| publisher | TIB Open Publishing |
| record_format | Article |
| series | SUMO Conference Proceedings |
| spelling | doaj.art-a424f68554cc4e889d16f92d96ae129f2023-08-31T08:31:31ZengTIB Open PublishingSUMO Conference Proceedings2750-44252023-06-01410.52825/scp.v4i.214Comparing Measured Driver Behavior Distributions to Results from Car-Following Models using SUMO and Real-World Vehicle Trajectories from RadarMax Schrader0https://orcid.org/0000-0003-3673-7672Mahdi Al Abdraboh1https://orcid.org/0009-0001-4906-297XJoshua Bittle2https://orcid.org/0000-0003-4524-3316University of Alabama University of Alabama University of Alabama In this study, the physical principles governing car-following (CF) behavior and their impact on traffic flow at signalized intersections are investigated. High temporal-resolution radar data is used to provide valuable insights into actual CF behavior, including acceleration, deceleration, and time headway distribution. Demand-calibrated SUMO simulations are run using empirical CF parameter distributions, and three CF models are evaluated: IDM, EIDM, and Krauss. By emulating radar data in SUMO and processing simulated vehicle traces, discrepancies between empirical and simulated parameter distributions are identified. Further analysis includes comparisons with default SUMO CF model parameters. The findings reveal that measured accelerations differ from CF model parameter accelerations and using the empirical value ($\mu = 0.89m/s^2$) leads to unrealistic simulations that fail volume-based calibration. Default parameters for all three models reasonably approximate the mean and median of measured parameters, but fail to capture the true distribution shape, partly due to homogeneity when using default parameters. The results show that it is more effective to simulate with the default parameters provided by SUMO rather than using measurements of real-world distributions without additional calibration. Future work will investigate closing the loop between the measured real-world and SUMO distributions using traditional calibration tactics, as well as assess the impact of calibrated vs. default CF parameters on simulation outputs like fuel consumption. https://www.tib-op.org/ojs/index.php/scp/article/view/214traffic micro-simulationcar-following modelscar-following calibrationintelligent driver modelroadside radar data |
| spellingShingle | Max Schrader Mahdi Al Abdraboh Joshua Bittle Comparing Measured Driver Behavior Distributions to Results from Car-Following Models using SUMO and Real-World Vehicle Trajectories from Radar SUMO Conference Proceedings traffic micro-simulation car-following models car-following calibration intelligent driver model roadside radar data |
| title | Comparing Measured Driver Behavior Distributions to Results from Car-Following Models using SUMO and Real-World Vehicle Trajectories from Radar |
| title_full | Comparing Measured Driver Behavior Distributions to Results from Car-Following Models using SUMO and Real-World Vehicle Trajectories from Radar |
| title_fullStr | Comparing Measured Driver Behavior Distributions to Results from Car-Following Models using SUMO and Real-World Vehicle Trajectories from Radar |
| title_full_unstemmed | Comparing Measured Driver Behavior Distributions to Results from Car-Following Models using SUMO and Real-World Vehicle Trajectories from Radar |
| title_short | Comparing Measured Driver Behavior Distributions to Results from Car-Following Models using SUMO and Real-World Vehicle Trajectories from Radar |
| title_sort | comparing measured driver behavior distributions to results from car following models using sumo and real world vehicle trajectories from radar |
| topic | traffic micro-simulation car-following models car-following calibration intelligent driver model roadside radar data |
| url | https://www.tib-op.org/ojs/index.php/scp/article/view/214 |
| work_keys_str_mv | AT maxschrader comparingmeasureddriverbehaviordistributionstoresultsfromcarfollowingmodelsusingsumoandrealworldvehicletrajectoriesfromradar AT mahdialabdraboh comparingmeasureddriverbehaviordistributionstoresultsfromcarfollowingmodelsusingsumoandrealworldvehicletrajectoriesfromradar AT joshuabittle comparingmeasureddriverbehaviordistributionstoresultsfromcarfollowingmodelsusingsumoandrealworldvehicletrajectoriesfromradar |