Under no-notice evacuation scenarios with limited time horizons, the effectiveness of evacuation can be negatively impacted by intermediate trips that are made by family members and the identification of vulnerable populations. The emergence of shared-mobility companies, such as Uber and DiDi, can be considered as a potential means to address above-mentioned concerns. The proposed study explores the utility of shared-mobility services under emergency-evacuation scenarios and makes recommendations to relevant bodies that are based on the obtained and they are discussed herein. The study investigates attitudes of the public, experts, and drivers towards the use of shared-mobility resources during emergency evacuations based on a stated preference survey. Results of questionnaires, driver interviews, and face-to-face expert interviews have been analyzed to validate the feasibility and identify potential problems of leveraging shared-mobility services during evacuation response, especially in metropolitan areas wherein such services are already ubiquitous. Numerical simulations have been performed to quantify potential improvements in the total trip distance and number of evacuees after incorporating the use of shared mobility into emergency-response operations. However, despite the observed improvement in emergency efficiency, certain realistic roadblocks must be overcome. Realization of the proposed objective heavily depends on actionable policy recommendations, provided herein as a reference for the government, emergency management agencies, and shared-mobility companies.

Braess paradox is a well-known paradox in transportation researches. In urban cities, there are many different kinds of complex road networks. Unavoidably, some of them fall into the Braess paradox and it is hardly realized. In this paper, two proposed approaches are applied to find and avoid the Braess paradox in urban road networks. With the first approach, the links that cause the Braess paradox in the urban road networks with the current origination-destination (OD) matrix can be tested. The other approach is to calculate the range of the OD flows that makes these links fall into the Braess paradox. Unlike other approaches proposed in literature, this proposed approach can figure out the range of traffic demands in the networks with multiple OD pairs. Moreover, by applying these two approaches, the authors design a traffic management called link restriction which can easily figure out which link should be closed down temporarily and when to resume operation to reduce the total travel times of networks with flexible managements.

This paper presents a definition of boundedly rational confidence level (BRCL) which is the probability that a trip arrives within the shortest travel time budget plus the acceptable travel time difference (i.e. boundedly rational threshold). Using the method of data fitting, boundedly rational threshold is estimated. Then, a reliability-based boundedly rational user equilibrium (R-BRUE) model that explicitly considers both travel time reliability and travelers’ bounded rationality in the route choice decision process is proposed. This new model hypothesizes that for each origin–destination (O–D) pair no traveler can improve his/her BRCL by unilaterally changing routes. A route-based quasi-method of a successive average algorithm is developed to solve the R-BRUE model. Numerical examples illustrate the essential ideas of the proposed model and the applicability of the proposed solution algorithm.

Carbon emissions, produced by automobile fuel consumption, are termed as the key reason leading to global warming. The highway circular curve constitutes a major factor impacting vehicle carbon emissions. It is deemed quite essential to investigate the association existing between circular curve and carbon emissions. On the basis of the IPCC carbon emission conversion methodology, the current research work put forward a carbon emission conversion methodology suitable for China’s diesel status. There are 99 groups’ test data of diesel trucks during the trip, which were attained on 23 circular curves in northwestern China. The test road type was key arterial roads having a design speed greater than or equal to 60 km/h, besides having no roundabouts and crossings. Carbon emission data were generated with the use of carbon emission conversion methodologies and fuel consumption data from field tests. As the results suggested, carbon emissions decline with the increase in the radius of circular curve. A carbon emission quantitative model was established with the radius and length of circular curve, coupled with the initial velocity as the key impacting factors. In comparison with carbon emissions under circular curve section and flat section scenarios, the minimum curve radius impacting carbon emissions is 500 m. This research work provided herein a tool for the quantification of carbon emissions and a reference for a low-carbon highway design.