DOI: 10.1177/09544070261460135 ISSN: 0954-4070

Energy-efficient round-trip route planning for electric bikes with real-time traffic and charging integration in Bengaluru

Parkavi Sridhar, Parthiban Angamuthu

In busy cities like Bengaluru, electric bikes are rapidly gaining popularity as an environmentally responsible mode of transportation. Planning the most effective routes for these bikes is difficult, though, because of their short battery life, erratic traffic, and variable road conditions. To tackle these issues, we have created a new system for designing round-trip, energy-efficient routes specifically for electric bikes in cities. Our methodology considers real-time traffic information and charging station locations to generate the most energy-efficient routes. This system’s energy graph, which accounts for slope, elevation variations, and distance, determines how much energy is used for each road segment. Instead of only looking for the quickest route, our system uses a sophisticated algorithm to find routes that use less battery to deliver a more environmentally friendly travel experience. To estimate congested regions by examining historical traffic patterns to further enhance route design. To group information from past journeys to identify typical bottlenecks to avoid traffic jams or road closures. Additionally, the system incorporates real-time traffic data to assist users in avoiding congested or sluggish routes for more comfortable travel. Additionally, our technology continuously monitors the rider’s battery condition and suggests nearby charging stations as needed to ensure the entire trip can be completed without running out of power. Compared to traditional route planning methods, our approach showed a significant improvement in energy economy and a decrease in travel time in a real-world test conducted in Bengaluru. Based on these findings, our approach could significantly enhance the experience of urban electric bike commuters by helping them overcome the challenges of low battery life and heavy traffic.

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