{'fraction_non_alphanumeric': 0.018947368421052633, 'fraction_numerical': 0.0, 'mean_word_length': 5.135483870967742, '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}}
Empirical data on driving behaviour in stop-and-go traffic

In the near future, it is foreseen that car-makers was introduce adaptive cruise control systems extended with a stop-and-go feature, supporting the driver in distance-keeping at low speeds. These intelligent vehicles behave in congested traffic according to driver behaviour rules specified in the controller. Essential part for a correct and efficient functioning of such a congestion assistance system is the specification of the desired time or distance gap to the preceding vehicle. The paper deals with the analysis of empirical gap data, measured during stop-and-go traffic conditions on a Dutch motorway. The data is analyzed and relations between speed and desired gap distance for car and truck drivers have been established. Based on the findings, recommendations are given for the desired gap distance function for intelligent vehicles operating in congested traffic conditions.