{'fraction_non_alphanumeric': 0.018571428571428572, 'fraction_numerical': 0.0, 'mean_word_length': 5.5162790697674415, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A Cooperative Control Strategy of Connected and Autonomous Vehicles in Ramp Merging Areas with Mixed-Autonomy Traffic

Considering mixed-autonomy traffic with connected and autonomous vehicles (CAVs) and human-driven vehicles (HVs), a CAV cooperative control strategy was proposed to improve the traffic flow efficiency in freeway ramp merging areas. The roadside unit controlled the movements of CAVs both on the ramp and on the mainline before the merging point, according to real-time traffic conditions. Microscopic simulations based on cellular automata were performed to evaluate the influences of the proposed cooperative control strategy on the average vehicle delays of the mainline, the ramp, and the entire merging area. Sensitivity analyses were performed with varying CAV market penetration rates and traffic demand levels. Results show that, compared to no-control case, the proposed cooperative control strategy may effectively reduce the average vehicle delay of the mainline. Though the average vehicle delay of the ramp increases, the average vehicle delay of entire merging area is still improved, because the mainline flow volume is usually much larger than the ramp flow volume. Furthermore, the proposed cooperative control strategy only requires a limited number of control variables, making it feasible to determine the optimal control variables based on sensitivity analysis.