{'fraction_non_alphanumeric': 0.015829318651066758, 'fraction_numerical': 0.0, 'mean_word_length': 5.058333333333334, '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}}
An Analytical Model for On-Demand Ride Sharing to Evaluate the Impact of Reservation, Detour and Maximum Waiting Time

Ride sharing services have the potential to improve the traffic situation in urban areas. However, a successful implementation of such a service depends on the customers’ willingness to share their trip with somebody else, which among other factors depends on service quality factors. A ride sharing service is more attractive to the customers when it is associated with short detour and waiting time. Hence, from an operator perspective these factors constrain the chances to find shareable trips. A reservation-based system might be beneficial to increase these chances. The aim of this paper is to examine the influences of service quality factors on the percentage of trips that could be shared, a quantity named shareability. An analytical model considering the impacts of detour time, maximum waiting time to be picked up and reservation time is developed and validated using simulations. The influence of the reservation time compared to an online service, in which passengers want to be served as soon as possible, is also investigated. A good match of the analytical model with the simulated data is observed for all the factors considered. Introducing a reservation time improves shareability compared to the online service, especially for low trip density and restrictive systems, where waiting time or detour time are low.