Model Contrast of Autonomous Vehicle Impacts on Traffic
The adoption of connected and autonomous vehicles (CAVs) is in its infancy. Therefore, very little is known about their potential impacts on traffic. Meanwhile, researchers and market analysts predict a wide range of possibilities about their potential benefits and the timing of their deployments. P...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2020/8935692 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832553261056393216 |
|---|---|
| author | Derek Hungness Raj Bridgelall |
| author_facet | Derek Hungness Raj Bridgelall |
| author_sort | Derek Hungness |
| collection | DOAJ |
| description | The adoption of connected and autonomous vehicles (CAVs) is in its infancy. Therefore, very little is known about their potential impacts on traffic. Meanwhile, researchers and market analysts predict a wide range of possibilities about their potential benefits and the timing of their deployments. Planners traditionally use various types of travel demand models to forecast future traffic conditions. However, such models do not yet integrate any expected impacts from CAV deployments. Consequently, many long-range transportation plans do not yet account for their eventual deployment. To address some of these uncertainties, this work modified an existing model for Madison, Wisconsin. To compare outcomes, the authors used identical parameter changes and simulation scenarios for a model of Gainesville, Florida. Both models show that with increasing levels of CAV deployment, both the vehicle miles traveled and the average congestion speed will increase. However, there are some important exceptions due to differences in the road network layout, geospatial features, sociodemographic factors, land-use, and access to transit. |
| format | Article |
| id | doaj-art-63be304d726f4c1b8fcc23313f4f5808 |
| institution | Kabale University |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-63be304d726f4c1b8fcc23313f4f58082025-02-03T05:54:25ZengWileyJournal of Advanced Transportation0197-67292042-31952020-01-01202010.1155/2020/89356928935692Model Contrast of Autonomous Vehicle Impacts on TrafficDerek Hungness0Raj Bridgelall1SRF Consulting Group, 6720 Frank Lloyd Wright Avenue, Suite 100, Middleton, WI 53562, USADepartment of Transportation, Logistics and Finance, North Dakota State University, P.O. Box 6050, Fargo, ND 58108, USAThe adoption of connected and autonomous vehicles (CAVs) is in its infancy. Therefore, very little is known about their potential impacts on traffic. Meanwhile, researchers and market analysts predict a wide range of possibilities about their potential benefits and the timing of their deployments. Planners traditionally use various types of travel demand models to forecast future traffic conditions. However, such models do not yet integrate any expected impacts from CAV deployments. Consequently, many long-range transportation plans do not yet account for their eventual deployment. To address some of these uncertainties, this work modified an existing model for Madison, Wisconsin. To compare outcomes, the authors used identical parameter changes and simulation scenarios for a model of Gainesville, Florida. Both models show that with increasing levels of CAV deployment, both the vehicle miles traveled and the average congestion speed will increase. However, there are some important exceptions due to differences in the road network layout, geospatial features, sociodemographic factors, land-use, and access to transit.http://dx.doi.org/10.1155/2020/8935692 |
| spellingShingle | Derek Hungness Raj Bridgelall Model Contrast of Autonomous Vehicle Impacts on Traffic Journal of Advanced Transportation |
| title | Model Contrast of Autonomous Vehicle Impacts on Traffic |
| title_full | Model Contrast of Autonomous Vehicle Impacts on Traffic |
| title_fullStr | Model Contrast of Autonomous Vehicle Impacts on Traffic |
| title_full_unstemmed | Model Contrast of Autonomous Vehicle Impacts on Traffic |
| title_short | Model Contrast of Autonomous Vehicle Impacts on Traffic |
| title_sort | model contrast of autonomous vehicle impacts on traffic |
| url | http://dx.doi.org/10.1155/2020/8935692 |
| work_keys_str_mv | AT derekhungness modelcontrastofautonomousvehicleimpactsontraffic AT rajbridgelall modelcontrastofautonomousvehicleimpactsontraffic |