Leveraging Connected Vehicle Data to Assess Interstate Exit Utilization and Identify Charging Infrastructure Investment Allocation Opportunities
With an influx of public and private sector investment in the electric vehicle (EV) domain, public agencies and stakeholders need objective, equitable and systematic processes for identifying candidate sites for siting charging stations. This paper reports on a case study examining the Indiana Inter...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-09-01
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| Series: | World Electric Vehicle Journal |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2032-6653/13/9/167 |
| _version_ | 1797481162069770240 |
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| author | Jairaj Desai Jijo K. Mathew Howell Li Darcy M. Bullock |
| author_facet | Jairaj Desai Jijo K. Mathew Howell Li Darcy M. Bullock |
| author_sort | Jairaj Desai |
| collection | DOAJ |
| description | With an influx of public and private sector investment in the electric vehicle (EV) domain, public agencies and stakeholders need objective, equitable and systematic processes for identifying candidate sites for siting charging stations. This paper reports on a case study examining the Indiana Interstate network using connected vehicle data (CV). The Indiana Interstate network analyzed by this study is composed of 1247 centerline miles along nine routes. Each month, approximately 13 billion CV records representing more than 44 million unique trips are generated along all roads in Indiana. For this study 3.02 billion records comprising 4.78 million trips on and around Indiana Interstates and Exits were analyzed for usage patterns. The CV data was predominantly from internal combustion engine vehicle (ICEV) passenger cars, but provides insight into exit utilization and dwell times at 544 exits on 9 interstate roadways to evaluate how their current usage would align with building out Indiana’s Alternative Fuel Corridors. A pareto sorted graphic for the top 50 busiest exits in the state shows that all but two are not well served by fast charging infrastructure. The paper suggests this pareto sorted list as a good starting point for further analysis and identified 15 exits on Indiana interstates, if chosen for deploying charging infrastructure, would ensure full compliance. The results provide a systemwide look at present dwell patterns among ICEVs and help identify locations of interest that would most benefit from addition of charging infrastructure as the current fleet of ICEVs gradually transitions to EVs. |
| first_indexed | 2024-03-09T22:10:33Z |
| format | Article |
| id | doaj.art-9bba67e947054c5ca3b4a096f1d25733 |
| institution | Directory Open Access Journal |
| issn | 2032-6653 |
| language | English |
| last_indexed | 2024-03-09T22:10:33Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj.art-9bba67e947054c5ca3b4a096f1d257332023-11-23T19:32:48ZengMDPI AGWorld Electric Vehicle Journal2032-66532022-09-0113916710.3390/wevj13090167Leveraging Connected Vehicle Data to Assess Interstate Exit Utilization and Identify Charging Infrastructure Investment Allocation OpportunitiesJairaj Desai0Jijo K. Mathew1Howell Li2Darcy M. Bullock3Joint Transportation Research Program, Purdue University, West Lafayette, IN 47907, USAJoint Transportation Research Program, Purdue University, West Lafayette, IN 47907, USAJoint Transportation Research Program, Purdue University, West Lafayette, IN 47907, USAJoint Transportation Research Program, Purdue University, West Lafayette, IN 47907, USAWith an influx of public and private sector investment in the electric vehicle (EV) domain, public agencies and stakeholders need objective, equitable and systematic processes for identifying candidate sites for siting charging stations. This paper reports on a case study examining the Indiana Interstate network using connected vehicle data (CV). The Indiana Interstate network analyzed by this study is composed of 1247 centerline miles along nine routes. Each month, approximately 13 billion CV records representing more than 44 million unique trips are generated along all roads in Indiana. For this study 3.02 billion records comprising 4.78 million trips on and around Indiana Interstates and Exits were analyzed for usage patterns. The CV data was predominantly from internal combustion engine vehicle (ICEV) passenger cars, but provides insight into exit utilization and dwell times at 544 exits on 9 interstate roadways to evaluate how their current usage would align with building out Indiana’s Alternative Fuel Corridors. A pareto sorted graphic for the top 50 busiest exits in the state shows that all but two are not well served by fast charging infrastructure. The paper suggests this pareto sorted list as a good starting point for further analysis and identified 15 exits on Indiana interstates, if chosen for deploying charging infrastructure, would ensure full compliance. The results provide a systemwide look at present dwell patterns among ICEVs and help identify locations of interest that would most benefit from addition of charging infrastructure as the current fleet of ICEVs gradually transitions to EVs.https://www.mdpi.com/2032-6653/13/9/167electric vehiclesconnected vehicle datacharge station sitingexit utilization |
| spellingShingle | Jairaj Desai Jijo K. Mathew Howell Li Darcy M. Bullock Leveraging Connected Vehicle Data to Assess Interstate Exit Utilization and Identify Charging Infrastructure Investment Allocation Opportunities World Electric Vehicle Journal electric vehicles connected vehicle data charge station siting exit utilization |
| title | Leveraging Connected Vehicle Data to Assess Interstate Exit Utilization and Identify Charging Infrastructure Investment Allocation Opportunities |
| title_full | Leveraging Connected Vehicle Data to Assess Interstate Exit Utilization and Identify Charging Infrastructure Investment Allocation Opportunities |
| title_fullStr | Leveraging Connected Vehicle Data to Assess Interstate Exit Utilization and Identify Charging Infrastructure Investment Allocation Opportunities |
| title_full_unstemmed | Leveraging Connected Vehicle Data to Assess Interstate Exit Utilization and Identify Charging Infrastructure Investment Allocation Opportunities |
| title_short | Leveraging Connected Vehicle Data to Assess Interstate Exit Utilization and Identify Charging Infrastructure Investment Allocation Opportunities |
| title_sort | leveraging connected vehicle data to assess interstate exit utilization and identify charging infrastructure investment allocation opportunities |
| topic | electric vehicles connected vehicle data charge station siting exit utilization |
| url | https://www.mdpi.com/2032-6653/13/9/167 |
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