Sisi Jian

• PhD
• Professor (Assistant) at Hong Kong University of Science and Technology

With technological advances, mobility has been moving from a product (i.e., traditional modes and vehicles), to a service (i.e., Mobility as a Service, MaaS). However, as observed in other fields (e.g., cloud computing resource management) we argue that mobility will evolve from a service to a resource (i.e., “Mobility as a Resource”, MaaR). Furthe...

Most studies developing car-following controllers for AVs in mixed traffic primarily focus on maximizing the utility of the AVs. However, the utility of the entire mixed traffic flow is largely ignored, which may lead to self-centered AVs. This study aims to develop a leading cruise controller for AVs that can “look behind” the mixed traffic flow....

The development of autonomous driving technology will lead to a transition period during which human-driven vehicles (HVs) will share the road with autonomous vehicles (AVs). Understanding the interactions between AVs and HVs is critical for traffic safety and efficiency. Previous studies have used traffic/numerical simulations and field experiment...

Mobility-as-a-Service (MaaS) is a promising solution for sustainable mobility and has therefore received considerable attention from researchers. People have complicated travel diaries. Larger households, especially with children, with a limited number of cars, are essentially prone to delays or travel cancellations. MaaS options fill this gap for...

Extreme events, such as disasters and severe road accidents, have frequently happened in recent years, threatening thousands of people’s lives. Efficient evacuation after extreme events is of utmost importance, which requires transport authorities to plan for and develop solutions to ensure transport infrastructure resiliency to disasters. In this...

Many regions of the world aim to phase out conventional private gasoline cars within ten years, requiring imminent expansion of the electric vehicle (EV) charging infrastructure. However, because of high installation and maintenance costs, many landowners (LOs), such as shopping malls and commercial building owners, hesitate to install and operate...

With more autonomous vehicles (AVs) being tested or deployed on public roads, human-driven vehicles (HVs) have to share the road with AVs. However, human drivers may not interact AVs the same way as they interact with HVs. Very few studies have investigated drivers' behaviors when sharing the road with AVs. Based on a real-world dataset, our study...

This paper considers a group of shared electric vehicles (SEV) that provide transport and energy services through a ride-sourcing platform. Under the novel business model, the transport and power networks are coupled and the resulting market equilibrium depends on the pricing strategies of the distribution network operator (DNO) and the SEV platfor...

As an emerging urban mobility service, carsharing has become increasingly popular worldwide. To understand customers’ needs and optimize the design of service networks, the usage of carsharing vehicles whose trips are recorded by the operators has been applied in research estimating carsharing demand. However, as a form of spatio-temporal correlate...

As the market penetration rate of automated vehicles (AVs) increases, there will be a transition period when the traffic stream is composed of both AVs and human-driven vehicles (MVs) in the near future. However, the interactions between MVs and AVs, especially whether MVs will behave differently when following AVs compared to following MVs, have n...

Vehicle-to-grid (V2G) technology enables electric vehicles (EVs) to discharge unused power to the power grid, allowing EVs to serve as flexible energy resources. Although this technology promises benefits to power systems, its impact on transport systems is unknown. We investigate the interaction between transport and power systems with V2G during...

This study proposes a two-stage stochastic program approach to jointly optimize the planning and operational decisions for one-way carsharing systems accounting for demand uncertainty. The two-stage stochastic model is constructed in the way that stage-one determines the strategic deployments, including the number of vehicles, personnel and parking...

Drive cycles in vehicle systems are important determinants for energy consumption, emissions, and safety. Estimating the frequency of the drive cycle quickly is important for control applications related to fuel efficiency, emission reduction and improving safety. Quantum computing has established the computational efficiency that can be gained. A...

China is motorizing rapidly as economic growth takes place alongside increasing car ownership. However, little is known about the determinants of household car ownership, and especially about how they are changing as this motorization process takes place. A major reason for this knowledge gap is the very limited available data resources compared to...

Drive cycles in vehicle systems are important determinants for energy consumption, emissions, and safety. Estimating the frequency of the drive cycle quickly is important for control applications related to fuel efficiency, emission reduction and improving safety. Quantum computing has established the computational efficiency that can be gained. A...

This study develops day-to-day models to explore how unreliability of public transit service affects the day-to-day evolution of travel choices. We consider two dynamical processes that incorporate transit service unreliability, i.e., travelers' learning and perception updating process (LPUP) and proportional-switch adjustment process (PSAP). The c...

Existing studies proposed different models to capture day-to-day evolution of travelers’ choices and traffic dynamics. However, explicitly incorporating public transit service unreliability/reliability into day-to-day traffic modeling received very little attention. This study develops day-to-day models to explore how the unreliability of public tr...

To improve the appeal of carsharing, we propose an integrated operation scheme of car-sharing and parking-sharing services, where a carsharing operator rents parking spaces from private owners to provide convenient parking options to carsharing users. We examine how the operator's profit and social welfare differ under the existing carsharing-only...

To improve the appeal of carsharing, we propose an integrated operation scheme of carsharing and parking-sharing services, where a carsharing operator rents parking spaces from private owners to provide convenient parking options to carsharing users. We examine how the operator's profit and social welfare differ under the existing carsharing-only s...

Collecting effective data is a fundamental step in developing transport networks and related research. Social media have become an emerging source of data for traffic analyses. In this paper, we demonstrate that the function of a city influences the utility of social media data in travel demand models by generating models for eight US cities with d...

The dominant challenge in one-way carsharing systems is the vehicle stock imbalance. Previous studies have proposed relocation approaches to handle it using optimization and simulation models. However, these models do not consider the interdependence between supply and demand in carsharing systems. In this paper, we develop an integrated optimizati...

This study investigates the mobility patterns in public transit system with a focus on commuters' departure time choice using large amount of transit smart card data. We use Sydney in our case studies. Unlike conventional methods using stated-preference and simulation techniques, we quantify the correlation between commuters' departure time and tra...

We review Transportation Demand Management strategies through the conceptual lens of Behavioural Economics, focussing on non-pricing (behavioural) interventions often known as nudges. We identify promising precedents, evaluate their impact and stability, and nominate strategies that might be applicable in the Melbourne context.

Facing the growing demand for carsharing services, it is critical for operators to accurately predict users’ preferences on different vehicle types and their vehicle usage. This vehicle choice behavior involves choosing multiple vehicle types simultaneously and allocating continuous amounts of budget to the chosen vehicles. The recent developed mul...

Carsharing, as an alternative to private vehicle ownership, has spread worldwide in recent years due to its potential of reducing congestion, improving auto utilization rate and limiting the environmental impact of emissions release. To determine the most efficient allocation of resources within a carsharing program, it is critical to understand wh...

One-way carsharing, providing users with more flexibility on returning stations, has attracted larger market demand than has the traditional round-trip service. However, the main challenge faced by a one-way carsharing system is the vehicle stock imbalance due to the uneven distribution of user demand. This study attempted to address this problem b...

This article proposes a bi-criteria formulation to find the optimal location of light rapid transit stations in a network where demand is elastic and budget is constrained. Our model is composed of two competing objective functions seeking to maximize the total ridership and minimize the total budget allocated. In this research, demand is formulate...