Resilience Modeling of Surface Transportation System in Mixed Traffic Environment

Large-scale natural disasters challenge the resilience of surface transportation system. The objective of this research was to develop a resilience model of surface transportation system in mixed-traffic environment considering varying Connected and Automated Vehicle (CAV) penetration scenarios. As deployment of CAVs are expected to improve traffic operations, a resilience model was developed in this research to evaluate the resilience performance of a transportation system with several CAV penetration levels (0%, 25%, 50%, 75% and 100%) for a given budget and recovery time. The proposed resilience quantification model was applied on a roadway network considering several disaster scenarios. The network capacity in terms of trips at any phase of disaster was compared to the pre-disaster trips to determine the system resilience. The capacity variation and the travel time variation was also estimated. The analysis showed that the resilience phenomenon of the transportation system improved with CAVs in respect of travel time and capacity improvement. The rate of improvement in link travel time for varied CAV penetration was almost identical for different disaster scenarios. For each disaster scenario, the individual link travel time reduced significantly with increased CAV penetration. However, higher penetration of CAVs (i.e., 50% or more), increased the recovery budget requirement. For example, the recovery budget needed for medium and large-scale disasters were 50% and 90% higher respectively compared to the recovery budget needed for a small-scale disaster. These higher costs were primarily needed for repair and replacement of intelligent infrastructure required for CAV

Determinants of continuance intention of user on smartphone-based traveller information systems in the greater Klang Valley

In these modern-days, the use of mobile traveller information service is pivotal in the efficient and effective running of the transportation system for an urban area. The role of urban facilities managers in urban transportation planning is to develop a plan to provide drivers with real-time traveller information services to enable regional economic growth and transition. Existing research in the mobile information traveller information services area has not deeply investigated the determinants of continuance intention to use smartphone-based traveller information systems (STIS). The purpose of this study is to attempt to do so by investigating STIS users’ continuance intention at the post-adoption phase. This study developed and validated an extended framework based on the expectation-confirmation model (ECM). The 280 STIS users from the Klang Valley highways and major streets participated in the study. The extended ECM results revealed that STIS users’ continuance intention is determined by perceived enjoyment and perceived usefulness of continued STIS use, followed by satisfaction with STIS use. In this study, satisfaction and perceived usefulness are determined primarily by confirmation of expectation from participants’ previous use, except for the perceived enjoyment. The findings of this study have implications for the transportation sectors in planning their strategies to increase users’ continuance intention to use STIS services. Most of the current literature in mobile information services studies focused only on pre-adoption and have paid little attention to user’s continuance intention, especially in the context of smartphone apps or electronic information in the transportation system services. This study fills the theoretical and practical gaps by focusing on the post-adoption phase and developed an extended framework based on the ECM to explain the STIS continuance intention context. In addition, the topic is timely, as mobile information services have been flourishing in the current worldwide transportation sector services

Development of an Optimisation Model for Scheduling of Street Works Schemes

The coordination of street works activities in urban networks has been highlighted by the Government as one of the most important aspects of street works practice, benefiting street authorities, undertakers and road users alike (Department for Transport, 2012c). The present research aims to develop an optimisation model for minimising the overall costs and disruptions incurred by all stakeholders as a result of implementing a number of street works schemes in an urban traffic network. The output of the optimisation model consists of optimum values for the underlying decision variables of the model such as start time of each street works scheme, type of traffic management strategy for each link, sequence of link closures and the level of resources allocated to undertake each scheme. The following two distinct objective functions, which are subject to minimisation by the optimisation model, have been developed: A primary objective function which captures the monetised effects of street works schemes such as cost of delays to road users, and cost of undertaking street works schemes. A secondary objective function (developed as a fuzzy inference system) to capture the non-monetised disruptive effects of street works schemes. The fuzzy variables of this inference system correspond to the level of ‘accessibility degradation’ of the network links, ‘connectivity degradation’ of the origin-destinations of the network, and ‘time sensitivity’ of the disruptive events (i.e. street works schemes). Next the street works optimisation problem was mathematically formulated as a bi-level optimisation programming problem, where the higher level problem is associated with minimising the aforementioned objective functions, and the lower level problem deals with predicting traffic flows, and thus the amount of delays incurred by the road users. Subsequently this study developed a genetic algorithm solution method to solve the resulting non-convex and NP-hard optimisation problem with integer or mixed type variables. Finally the performance of the optimisation algorithm was verified by a number of experimental tests on a small hypothetical network for three street works schemes