Overview

1. Methodology Evaluation Overview Conclusion Objectives • Developing a Traffic Network Based on Wireless Communication to Reduce Vehicle Energy Consumption and Emission • Mohamad Abdul-Hak1, Malok Alamir Tamer1, Nizar Al-Holou1, Ph.D., Youssef Bazzi2, Ph.D. 1: Department of Electrical and Computer Engineering, University of Detroit Mercy 2: Lebanese University, Beirut, Lebanon The optimal solution is path connecting source to destination with maximum number of emission tokens arrived with at destination provided travel time tokens are not depleted. The re-optimization of subnet uj is executed on the condition that higher arc weights are received indicating worsen traffic condition. The objective function for re-optimization remains the same given re-optimization begins at current marking. Vehicle traffic adopts navigation rules established by vehicle navigation systems, such as shortest distance, shortest time or Eco-friendly. Each navigation system calculates path using criteria selected by the driver, and creates destination pathways used to direct driver to the next road segment. Existing approaches plan a path based on historical traffic information and then modify the route as the vehicle receives current traffic conditions thus sacrificing optimality. In this poster, we propose a novel genetic algorithm modeled as a Petri Net (PN) for optimizing travel time and vehicle emission in a connected roadway network with minimal total traffic capacity, to route vehicle in a dynamically changing traffic environment, utilizing a predictive optimization approach. The novel unfolded PN model presented in this poster incorporates the essential features in Dynamic Programming (DP) to solve the stochastic traffic routing problem. The effectiveness of the proposed methodology is validated by comparing the performance with conventional routing methodologies. • Identify an Eco Friendly Navigation algorithm, with a focus on: • Moving vehicle from a source to a destination avoiding traffic congestion thus optimizing emissions and travel time • Dynamic re-routing to accommodate traffic condition changes • Implement algorithm utilizing microscopic traffic and emission models to evaluate performance. Figure 5. Total Waiting/Travel Time Transform Roadway network into a mathematical model using Petri Net (PN) as illustrated in Figure 1. Figure 6. Fuel Consumption and Emission • The results in Figure 5 and Figure 6 demonstrate the benefits of the proposed dynamic routing algorithm in both emission as well as travel time reduction. This was achieved through dynamic re-routing however maintaining travel time optimality. Figure 3. Emission Incidence Matrix • The Eco-friendly routing methodology has been presented based on Petri Nets modeling for optimizing travel routes based on vehicle emission and travel time. • The proposed dynamic calculation approach offers enhanced performance than conventional static methodology as it allows for adapting to sudden changes in traffic conditions. Figure 4. Travel Time Incidence Matrix Figure 2. Unfolded Petri Net Model • Determine reachability based on cost objectives: • emission (δui) • Total travel time (φui) A computer-based open source simulation tool iTETRIS is selected to integrate, evaluate and compare the proposed Eco-route methodology to the conventional static routing approach. Figure 1. Roadway Network This work has been partially supported by the U.S. Department of Transportation and MDOT through the University Transportation Center (UTC) program, MIOH, at the University of Detroit Mercy