{'fraction_non_alphanumeric': 0.023255813953488372, 'fraction_numerical': 0.0, 'mean_word_length': 5.18562874251497, '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}}
Dynamic Speed Limits and On-Ramp Metering for IVHS using Model Predictive Control

We consider traffic management and control approaches for intelligent vehicle highway systems (IVHS), which consist of interacting intelligent vehicles and intelligent roadside controllers. The vehicles are organized in platoons with short intraplatoon distances, and larger distances between platoons. All vehicles are assumed to be fully automated, i.e., throttle, braking, and steering commands are determined by an automated on-board controller. We consider both dynamic speed limit control for the platoons in the IVHS and access control at the on-ramps using ramp metering. We propose a model-based predictive control (MPC) approach to determine appropriate speed limits and release times at the on-ramps for the platoons. The proposed approach is also applied to a simple simulation example in which the aim is to minimize the total time all vehicles spend in the network by optimally assigning dynamic speed limits and on-ramp release times.