Nowadays, the rapid development of self-driving technology and its fusion with the current
vehicle electrification process has given rise to electric self-driving taxis (es-taxis) …

Vehicle mobility optimization in urban areas is a long-standing problem in smart city and
spatial data analysis. Given the complex urban scenario and unpredictable social events …

Online ride-hailing platforms can gather travel requests and allocate service vehicles to
balance transportation demands and supplies, which may result in an increase in the …

We present a novel order dispatch algorithm in large-scale on-demand ride-hailing
platforms. While traditional order dispatch approaches usually focus on immediate customer …

Today policymakers face increasingly complex traffic systems. While they need to ensure
smooth traffic flows in the cities, they also have to provide an acceptable level of service in …

The ride-hailing behaviors of customers are often impacted by various factors including time,
geographic distance between locations and weather conditions, causing imbalance …

In this paper, we consider same-day delivery with a heterogeneous fleet of vehicles and
drones. Customers make delivery requests over the course of the day and the dispatcher …

We are witnessing a rapid taxi electrification process due to the ever-increasing concern
about urban air quality and energy security. A key difference between conventional gas taxis …

In this paper, we focus on a taxi dispatch system with the help of auxiliary models that predict
future demand and destination. We build two different neural networks for learning taxi …

Autonomous vehicles (AVs) are expected to operate on mobility-on-demand (MoD)
platforms because AV technology enables flexible self-relocation and system-optimal …