Search Results (2)

The adoption rate of battery electric vehicles (EVs) is rapidly increasing. Electric vehicles differ significantly from conventional internal combustion engine vehicles and vary widely across different manufacturers. Emergency responders (ERs) and recovery personnel may have less experience with EVs and lack timely access to critical information such as the extent of the stranded energy present, high-voltage safety hazards, and post-crash handling procedures in a user-friendly manner. This paper presents a software/hardware interactive tool named Electric Vehicle Information for Incident Response Solutions (EVIRS) to aid in the quick access to emergency response and recovery information. The current prototype of EVIRS identifies EVs using the VIN or Make, Model, and Year, and offers several useful features for ERs and recovery personnel. These features include integration and easy access to emergency response procedures tailored to an identified EV, vehicle structural schematics, the quick identification of battery pack specifications, and more. For EVs that are not severely damaged, EVIRS can perform calculations to estimate stranded energy in the EV’s battery and discharge time for various power loads using either EV dashboard information or operational data accessed through the CAN interface. Knowledge of this information may be helpful in the post-crash handling, management, and storage of an EV. The functionality and accuracy of EVIRS were demonstrated through laboratory tests using a 2021 Ford Mach-E and associated data acquisition system. The results indicated that when the remaining driving range was used as an input, EVIRS was able to estimate the pack voltage with an error of less than 3 V. Conversely, when pack voltage was used as an input, the estimated state of charge (SOC) error was less than 5% within the range of 30–90% SOC. Additionally, other features, such as retrieving emergency response guides for identified EVs and accessing lessons learned from archived incidents, have been successfully demonstrated through EVIRS for quick access. EVIRS can be a valuable tool for emergency responders and recovery personnel, both in action and during offline training, by providing crucial information related to assessing EV/battery safety risks, appropriate handling, de-energizing, transport, and storage in an integrated and user-friendly manner. Full article

Object occlusion is a common challenge in roadside LiDAR-based vehicle tracking. This issue can cause variances in vehicle location and speed calculations. This paper proposes a vehicle tracking post-processing method designed to handle full occlusion and limited datapoint conditions. The first part of the method focuses on linking the disconnected trajectories of the same vehicle caused by full occlusion. The second part refines the vehicle representative point to enhance tracking accuracy. Performance evaluation demonstrates that the proposed method can detect and reconnect the trajectories of the same vehicle, even under prolonged full occlusion. Moreover, the refined vehicle representative point provides more stable speed estimates, even with sparse datapoints. This significantly increases the effective detection range of roadside LiDAR. This approach lays a strong foundation for the application of roadside LiDAR in emission analysis and near-crash studies. Full article