- By:
- Xu, Guanhao ; Zhou, Anye ; Saroj, Abhilasha J; Wang, Chieh ; Sujan, Vivek A; Rodgers, Michael O; Chen, Jianfei ; Calderón, Oriana; Wang, Zejiang
- Page Number:
- 1023-1034
- Book Title:
- Proceedings of the 2025 Winter Simulation Conference (WSC)
- Publication Date:
- March 12, 2026
- Publisher Location:
- IEEE, United States of America
- Conference Name:
- 2025 Winter Simulation Conference (WSC 2025)
- Conference Location:
- Seattle, Washington, United States of America
- Conference Sponsor:
- ACM/SIGSIM, ASA (Technical Co-Sponsor), ASIM (Technical Co-Sponsor), IEEE/SMC (Technical Co-Sponsor), IISE, INFORMS-SIM, NIST (Technical Co-Sponsor), SCS, and ORS (Technical Sponsor).
- View DOI Listing:
- https://doi.org/10.1109/WSC68292.2025.11339042
Abstract
Traffic-vehicle co-simulation couples microscopic traffic simulation with full-body vehicle dynamics to assess system-level impacts on mobility, energy, and safety with greater realism. Incorporating elevation is critical for accurately modeling vehicle behavior and energy use, especially for gradient-sensitive vehicles such as electric and heavy-duty trucks. However, raw elevation data often contain noise, discontinuities, and inconsistencies. While such issues may be negligible in traditional traffic simulations, they significantly affect traffic-vehicle co-simulations where vehicle dynamics are sensitive to road grade variations. This paper investigates the impact of unprocessed elevation data on vehicle behavior and energy consumption using a 42-mile simulation along Interstate 81. We propose an elevation processing workflow that can mitigate the effects stem from elevation data issues, improving the realism and stability of traffic-vehicle co-simulation. Results show that the method effectively removes noise and abrupt elevation transitions while preserving roadway geometry.
