01657382

Component

The paper develops a simulation-based eco-routing framework that comprehensively considers microscopic characteristics and is able to differentiate vehicle types and route vehicles dynamically based on real time information. The system models both conventional gasoline/diesel and plug-in electric vehicles, and is developed in the INTEGRATION framework. Testing efforts involve evaluating network-wide impacts of eco-routing strategies at different congestion levels. The network-level measures of effectiveness (MOEs, i.e. energy consumption, travel time and distance) are compared between the proposed system and traditional eco-routing and travel time routing algorithms. The results demonstrate that the proposed eco-routing achieves energy savings relative to the other two routing methods at all tested congestion levels. It is also found that the conventional fuel savings decrease with the increasing traffic demand relative to travel time routing, while electric power savings do not monotonically vary with congestion level. Energy savings relative to traditional eco-routing are also not monotonically related to network congestion level. Finally, network configuration is demonstrated to significantly affect eco-routing benefits. The simulation-based framework provides valuable insights for real-world applications such as on-board navigation using connected vehicle technology.

This paper was sponsored by TRB committee ADC20 Standing Committee on Transportation and Air Quality.

18-01053

English

0000-0002-5845-2929

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; References; Tables

Advanced traveler information systems; Advanced traveler information systems; Connected vehicles; Ecodriving; Energy consumption; Greenhouse gases; Intelligent transportation systems; Navigation; Simulation

Energy; Highways; Operations and Traffic Management; Vehicles and Equipment

Transportation Research Board Annual Meeting 2018 Paper #18-01053

TRIS, TRB, ATRI

Jan 8 2018 10:16AM