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• Investigate the experienced users of a paid and publicly accessible autonomous taxi service. • Examine travel characteristics and the determinants of continuous use intention. • Autonomous taxis are expected to become a new mode of transport. • ATT, PEU, PU, SS, PO, and CES influence continuous use intention. • Frequent takeovers influence the preference and perception of autonomous taxis. The interaction with autonomous driving technology has increased in the past few years. Although a few studies have investigated the opinion of people who have physically experienced AVs, the understanding regarding how the experienced users can integrate AV-based services into real life is limited. To address this gap, the present study examines the travel characteristics of autonomous taxi trips and the determinants of continuous use intention. The data used in this study were collected in Guangzhou, China where paid autonomous taxi service have been publicly accessible and operated for one year. The analysis of the autonomous taxi trips revealed that this novel mobility choice has been accepted and extensively used by experienced users. In addition, five market segments were identified according to the supplement and alternative travel mode to autonomous taxi trips. Results indicate a possible mode shift from public transport to autonomous taxis. The role of a safety steward on board was also identified. Findings suggest that takeover action influences the acceptable time for fully autonomous driving and the preference for autonomous taxis. Certain factors—service satisfaction, psychological ownership, and concern for the equality of safety—for autonomous taxi use are considered in this study. On this basis, an extended technology acceptance model is proposed to explain the continuous use intention of autonomous taxis. The maintenance of a positive attitude toward use, which underlines the simplicity and usefulness of autonomous taxis and the improvement of service quality, is essential for experienced users. Furthermore, the approaches that establish psychological ownership and alleviate the concern for the equality of safety can also enhance the continuous use intention. Interestingly, the effect of concern for the equality of safety on continuous use intention is larger when experienced users do not or seldom encounter takeovers. The research contributes to the ongoing research related to the real-life application of AVs, with implications for urban transportation managers, mobility providers, and automobile industry players. [ABSTRACT FROM AUTHOR]

• An integrated framework for real-time signal and routing optimization is proposed. • A two-stage rolling horizon framework is developed to predict network dynamics. • Optimizing individual vehicle routes and signal states with computational feasibility. • Improved network capacity and reduced travel time at relatively low rerouting costs. This paper presents an integrated framework for optimizing signal control and vehicle routing. An important feature of the proposed framework is the ability to simultaneously determine signal states and individual vehicle routes in real time. The general objective is to minimize the network travel time, which can be represented as a trade-off between the total route length of all vehicles and traffic conditions at signalized intersections. A two-stage rolling horizon framework is proposed to explicitly describe the relationship between individual vehicle routes and predicted traffic flow dynamics at signalized intersections. The first stage involves a signal optimization problem, while the second stage optimizes a joint signal control and vehicle routing problem. Both stages are formulated as mixed integer linear programming problems. The optimization procedure is decentralized, and the effects of vehicle routing on control performance is considered by incorporating the route length cost into the objective function. Simulation experiments validate the advantages of the proposed framework over advanced signal control strategies and dynamic user-optimal routing strategies in various scenarios. The effectiveness in improving network capacity, alleviating spillback, and decreasing congestion dissipation time under over-saturation conditions is discussed. The results of vehicle routing suggest that the total travel time can be reduced at a low rerouting cost. Sensitivity analyses demonstrate the network control performance under different compliance rates and model coefficients. Moreover, the computational feasibility of the framework is verified. [ABSTRACT FROM AUTHOR]