Car-following is the mostcommontask. lt refers to a process where the followingvehicle (FV) tries to keep a safe distance betweenitself and the lead vehicle (LV) by adjusting itsacceleration in response to the actions of thevehicle ahead. The corresponding car-followingmodels are functions that determine FV's futureaccelerationsbased on current (and historicaldriving situations. Car-following models are thecornerstone for microscopic traffic simulation andintelligent vehicle development. One majormotivation of car-following models is to replicatehuman drivers'longitudinal driving trajectories. Inthis seminar, will first talk about how to calibrate
classical
evaluate,andcross-comparecar-following models using large-scale real-worldnaturalistic driving data. To model the long-termdependency of future actions on historical drivingsituations, will also introduce a long-sequencecar-following trajectory prediction model based onthe attention-based Transformer model.

Rail is safe, efficient, and environmentally friendly formoving large volumes of passengers and freight overlong distances. Safety is the top priority for global railsystems. In the age of Industry 4.0 empowered by theuse of the Internet of Things (loT), advancedcommunications technologies, artificial intelligence(Al),andautomation technologies, the railtransportation system is stepping onto a new phase ofrapidproactive,digital,developmenttowardintelligent safety and risk management. Thispresentation will introduce several cross-disciplinary.rail-centric A and data analytics-related studiesconducted at the Rail and Transit Program at RutgersUniversity, in close collaboration with the U.S. railindustry. Particular examples include predictivemodeling of rail infrastructure degradation, as well asreducing fatalities and injuries on railways through theuse of Al and communications-based advanced traincontrol technologies.

The COVID-19 outbreak exposed the vulnerability ofthe global supply chain to a wide audience. Fromtransport and logistics perspective, port congestionshave seriously disrupted the cargo flows in the globalsupply chains. This talk will focus on containershipping industry. Firstly, l will present a few studiesthat we conducted to enhance operation efficiency atport yard and landside that help reduce portcongestion and emissions. This includes optimizingoperations at seaport rail terminals, optimizingcontainer retrieval and reshuffling, and smart stackingat container yard. Secondly, taking the supply chainviewpoint, I will explain the challenging issues incontainer shipping supply chain (CSSC) by focusing ondigitalization and decarbonization. Possible pathwaytoward digitalization andpathwaytowardsdecarbonization in CSSC will be discussed includingfuture research opportunities.

介绍轨道交通、道路交通、水运交通以及航空交通等行业的科技发展现状、成就和短板，对国内外交通科技的需求态势和发展趋势进行分析，在总结目前创新发展的基础上，提出交通科技未来发展的目标和总体思路以及各种交通方式的科技发展需求;探讨十四五期间我国交通领域科技创新的主要任务。

Many cities worldwide are embracing electric vehicle(EV) sharing as a flexible and sustainable means ofurban transit. However, it remains challenging forthe operators to charge the fleet because of limitedor costly access to charging facilities. We focus onanswering the core question-how to charge the fleetto make EV sharing viable and profitable. Our work ismotivated by the setback that struck San DiegoCalifornia, where car rental company car2go ceasedits EV-sharing operations. We integrate charginginfrastructure planning and vehicle repositioningoperations that were often considered separatelyMore interestingly, our modeling emphasizes theoperator-controlledchargingoperationsandcustomers' EV-picking behavior. With advancedoperations research models, we find that the viabilityof EV sharing can be enhanced by concentratinglimited charger resources at selected locations. Boththe high-level planning guidelines and operationalpolicies can be useful for practitioners.

Civil aviation is one of the drivers of global growth. It increasesat around 4.4% per annum and is poised to maintain thisgrowth for the next 20 decades. On the other hand, aviation isresponsible for 5% of total anthropogenic radiative forcing andis expected to increase substantially in the future. In the face ofthe continuing expansion of air traffic, mitigation of aviation'sclimate impact becomes challenging but imperative

Despite the ambitious plans of vehicle manufacturers, vehicletechnologies usually take two to five decades to saturate theirpotential market,and currently, SAE level-2 automation (SAEJ3016 201401) is the state-of-the-art vehicle-automationtechnology. For this level, drivers are still required to monitor theroad and get ready to intervene in a timely manner whennecessary. Thus,visually monitoring the driving environmentand anticipating how a given situation may evolve (anticipatorydriving) may still bring benefits to driving safety. A good designneeds to support drivers' anticipation of both the environmentas well as the automated system that they are interacting withand consider drivers' states when transferring control. Throughdriving simulator experiments, my research aimed to answer thefollowing questions: (1) how automation affects anticipation indriving and (2) what types of feedback can be effective to supportdriver anticipation in automated vehicles. Results show thatdriving experience still matters to driving safety in automatedvehicles, with experienced drivers exhibited more anticipatorydriving behaviors. Distraction engagement may still need to beavoided in vehicles with the current level of driving automation(SAE Level-2), as distraction engagement can impede anticipatorydriving in automated vehicles. Further, this research indicates thatdrivers in automated vehicles should be trained with proper

Rail and urban transit systems often serve a large number of passengerson a daily basis and play an important role in supporting economicactivities. This presentation will discuss how to utilize modeling anddata analysis tools to improve our understanding and performanceof rail or urban transit systems. In particular, this presentation will firstdiscus data mining and modeling techniques for quantifying mobilitypatterns and demand prediction in rail/transit systems. Then, givencertain levels of demand information, pricing and service networkdesign problems in rail/transit systems will be presented. A fewexamples on game-theoretical models and network design models forpassenger-freight integrated transit/rail system will be illustrated. Inaddition, several empirical studies that examine the impacts of raildevelopment on accessibility, economy and equity will be discussedwhere the joint effect of rail development and megalopolis policy willalso be covered. In summary, this presentation illustrates with exampleshow modeling and analysis tools can be applied to rail and urban transitsystems for better policy and decision making.