On September 14, 2022, from 7:00 to 9:00 PM Beijing time, the third and fourth lectures of the 2022 Transportation Series were successfully held by the Transportation Research Institute of the University of Leeds and Beijing Jiao Tong University. The two special lectures in this issue were hosted by Professor Li Hongchang from the School of Economics and Management at Beijing Jiaotong University, using ZOOM online conference live streaming format, continuing to build a bridge for academic dialogue between Chinese and foreign transportation scholars. Among them, the third special lecture was presented by Professor Charisma Choudhury, a behavioral modeling expert from the Institute of Transportation at the University of Leeds, UK, with the title of "Utilizing Physical Data for Augmenting Travel Behavior Models". Professor Yu Biying from Beijing Institute of Technology and Professor Wang Yacan from Beijing Jiaotong University were invited to comment; The fourth special lecture was presented by Associate Professor Zia Wadud, an expert in the field of transportation and energy, with the title of "To Own or not to Own? That is the Question!". Professor Chen Xiqun from Zhejiang University and Professor Jiang Rui from Beijing Jiaotong University were invited to comment.

Beijing Jiaotong University - Institute of Transportation, University of Leeds, UK

The third and fourth lectures of the 2022 Transportation Series will open

Professor Charisma Choudhury, the guest speaker of the third special lecture, is a future leading researcher at the UK National Research and Innovation Agency (UKRI) and a full-time professor at the University of Leeds Transportation Research Institute. He is also the head of the University of Leeds Choice Modeling Research Team and the deputy director of the Interdisciplinary Choice Modeling Center. Professor Charisma Choudhury obtained a doctoral degree from the Massachusetts Institute of Technology (MIT). Prior to joining the University of Leeds, she worked at the Bangladesh University of Engineering and Technology, MIT, the European Rand Corporation, and Cambridge Systems Corporation. Her current research focuses on modeling travel behavior using emerging data sources, especially based on scenarios in developing countries. Professor Charisma Choudhury is currently an honorary visiting professor at Beijing Jiaotong University and a Turing researcher at the Alan Turing Institute; She is also the current Vice President of the International Association for Travel Behavior Research (elected as President in 2024).

In the third lecture, Professor Charisma Choudhury first discussed the research prospects and existing challenges of incorporating emerging data sources into the process of traffic behavior modeling. She then proceeded to present three cases of using emerging data sources to study driving behavior, cycling behavior, and accommodation choices. She pointed out that the development of related computing technologies has allowed people to access a wide range of data sources for modeling traffic behavior, especially physiological sensor data such as skin conductivity, heart rate records, eye tracking information, and electroencephalogram, which is expected to become a data source for studying travelers' mental states and decision-making processes in the future. However, existing research faces difficulties in screening useful information, establishing suitable models, and collecting data outside the laboratory. Professor Charisma Choudhury specifically shared three cases of applying physiological sensor data. Case 1 uses data from a combination of driving simulators and physiological sensors to simulate the impact of psychological stress during driving on following gap decision-making. This case applies the University of Leeds Driving Simulator (UoLDS) to simulate driving scenarios, using Empathica E4 to collect physiological sensor data related to skin conductance, heart rate, and blood flow pulse pressure. During the simulation process, a total of 10 different lengths of following gaps were set, and multiple pressure induced events, including congestion, were set up. The results indicate that using skin conduction and heart rate data to explain the following gap acceptance behavior improves the fit, demonstrating the feasibility of successfully incorporating neural data into general mathematical models through a hybrid structure. Case 2 uses structural equation modeling and brain imaging data to model people's risk perception during cycling in a virtual environment. This experiment designed a total of 24 traffic scenarios to record people's behavioral responses, and constructed a 7-level Likert scale to measure people's perceived risk and willingness to ride bicycles; Throughout the experiment, EEG data of the subjects will be collected, as well as information on their personal and social characteristics. The results indicate that at intersections, when the distance from the workshop is short and there is a potential collision risk, cyclists' tendency to slow down increases, and at the same time, alpha wave neural data also increases; In addition, compared to models that do not use neural data, the standard error of variables included in the structural equation after using neural data is smaller. Case three combines eye tracking data with SP data to study people's choice of residence behavior in different contexts. This study obtained a total of 1430 selection data and their eye tracking data from 38 subjects, and constructed two models, one is the MNL model, where eye tracking data will affect the model's performance β Value; The other is the DFT model, where eye tracking data will adjust the model's "attention weight". The results indicate that the DFT model has better fitting performance than the MNL model, and the DFT model with estimated attention weights is superior to the DFT model with estimated scaling coefficients.

Charisma Choudhury, Institute of Transportation at the University of Leeds, shares the latest research findings

Professor Yu Biying from Beijing Institute of Technology and Professor Wang Yacan from Beijing Jiaotong University, as the guest reviewers of the third special lecture, gave in-depth comments on Professor Charisma Choudhury's academic report. Professor Yu Biying mainly discussed three cases with Professor Charisma Choudhury. Professor Yu Biying pointed out that these data reflecting people's physiological aspects may be influenced by driving experience, that is, the factors may be cross mixed. She and Professor Charisma Choudhury discussed with each other what policies or measures the government should propose to improve people's transportation behavior, based on the research conclusions integrated with physiological data. Professor Charisma Choudhury believes that differentiation strategies can be implemented for different populations, and further prospects the application of physiological data measurement in car driving in the future.

Outstanding comments by Professor Yu Biying from Beijing University of Technology

Professor Wang Yacan focused on discussing the advantages, challenges, and opportunities of physiological sensor data with Professor Charisma Choudhury. Professor Wang Yacan pointed out that a major advantage of physiological sensor data is that it can observe the same decision-maker for longer periods of time and can also capture "softer" factors that affect traffic behavior at the individual level; In addition, these data can also be combined with SP data and RP data. Professor Wang Yacan believes that challenges and opportunities coexist, and such data may have noise interference, but relevant methods of experimental economics can be used to control some interference factors; This type of data requires professional equipment and has a high cost, but it can also be conducted through international cooperation in China, which has abundant experimental resources and relatively low costs.

Highlights of Professor Wang Yacan from Beijing Jiaotong University

In the third lecture, Professor Charisma Choudhury centred her talk on the topic of "Utilizing Physiological Data for Augmenting Travel Behavior Models" and examined the impact of emerging data sources, including physiological sensor data, on the field of traffic behavior modelling research. This study focuses on the micro and cutting-edge perspectives, and the intersection and collision of multiple disciplines such as psychology, economics, and neuroscience have broadened the research horizons of participants. Two specially invited reviewers, Professor Yu Biying and Professor Wang Yacan, further explored the feasibility of data acquisition and the accuracy of the data itself, and looked forward to future research challenges and opportunities in this field, providing exciting ideas for attendees. Other guests and attendees also had active questioning and discussions on the Zoom Q&A platform.

Following Professor Charisma Choudhury's excellent presentation, the fourth special lecture was delivered by Associate Professor Zia Wadud, who shared the latest research on the demand ratio of private cars and taxi hailing services in the context of the development of autonomous driving technology, as well as the convenience value of private cars. Associate Professor Zia Wadud is an associate professor at the Institute of Transportation and the School of Chemistry and Engineering at the University of Leeds, and also serves as the graduate research director at the Institute of Transportation. Associate Professor Zia Wadud's research focuses on transportation connectivity and transportation and environmental issues in a multidisciplinary context, with a particular interest in emerging transportation mobility and new energy prospects. He is a member of three different expert committees on energy, climate change, and aviation at the Transportation Research Association of the National Academy of Sciences, Engineering, and Medicine in the United States. He has published over 50 papers in first-class journals, and his recent research on the costs of autonomous driving, sharing, and electric vehicles has attracted international media attention. He currently involved in UKRI's UKARC and UKCREDS research projects and provides advice to the Ministry of Transportation on the impact of autonomous driving. Associate Professor Zia Wadud holds a doctoral degree from Imperial College London and has previously worked at the University of Cambridge and the Massachusetts Institute of Technology.

In his lecture, Associate Professor Zia Wadud cited multiple media comments and reports on "Will everyone give up their cars when the future era of autonomous driving arrives?" and raised two research questions: what is the potential demand ratio for owning cars and using on-demand ride services, considering the distribution of vehicle ownership and usage costs? What is the convenience value of owning a car? Associate Professor Zia Wadud first pointed out that the cost of owning a car includes multiple components such as vehicle depreciation, fuel consumption, and insurance expenses. However, many studies only focus on the average cost of owning a car, and the distribution of usage costs is also worth paying attention to. The economic cost distribution curve of private car annual usage costs obtained from the UK National Transportation Survey data shows that the left end of the curve is relatively flat, indicating that this part of the vehicle usage cost is not high (such as old vehicles), and the right end is steep, indicating high usage costs (such as branded cars). In addition to economic costs, we also need to consider the time costs people spend on the road, which will further increase the growth rate of the cost distribution curve. Compared to traditional cars, automatic cars may increase capital expenditure, but they can reduce fuel, parking, and insurance costs, while also reducing time costs by about 40%. Associate Professor Zia Wadud found through research on the distribution of people's perception of whether autonomous vehicles make time spent on travel more useful, as well as the relationship between this perception and their interest in using autonomous vehicles, that autonomous vehicles are more helpful in reducing time costs compared to traditional manual vehicles. Zia Wadud also pointed out that autonomous vehicles can be divided into two categories: travel services and private vehicles, and that travel service vehicles can be further classified as exclusive or shared. In terms of travel time benefits, the benefits of exclusive autonomous driving travel service vehicles are about half of those of private autonomous driving vehicles, while the benefits of shared vehicles are also half of those of exclusive travel services. He demonstrated the changes in the demand proportion of private manual driving, private autonomous driving, exclusive autonomous driving calling service, and shared autonomous driving calling service among the two major categories of traditional fuel-powered and electric vehicles. Additionally, the multiple logistic regression model also estimates which factors make the four types of vehicles mentioned above the least costly choices in different scenarios. To conclude, Associate Professor Zia Wadud explained in simple terms how to use experimental methods to explore the value of the convenience of owning a vehicle.

Associate Professor Zia Wadud from the Institute of Transportation at the University of Leeds shares the latest research findings

Professor Chen Xiqun from Zhejiang University and Professor Jiang Rui from Beijing Jiaotong University, as guest reviewers for the fourth special lecture, gave excellent comments on Associate Professor Zia Wadud's academic report. Professor Chen Xiqun commented that Associate Professor Zia Wadud's lecture was impressive and that the two research questions possess important theoretical value and practical significance. He pointed out that the important result of the study, which is slightly counterintuitive, is that the majority of respondents tend to own private cars, indicating that we still have a long way to go in encouraging people to reduce their ownership of vehicles. Professor Chen Xiqun also pointed out that the impact of gender on whether to own a private car is very interesting, and this phenomenon may be due to different genders' differing levels of sensitivity to privacy.

Professor Chen Xiqun's Exciting Comments from Zhejiang University

Professor Jiang Rui mainly discussed with Associate Professor Zia Wadud on applying research conclusions and expanding research contexts. He believes that different countries have different lifestyles, so it remains to be discussed whether the research results based on the UK scenario are fully applicable to China. He also pointed out that people may use private cars on weekdays and use car hailing services on weekends, which will affect the conclusion. Associate Professor Zia Wadud provided detailed answers to these questions. 

Professor Jiang Rui from Beijing Jiaotong University's Exciting Comments

In the fourth lecture, Associate Professor Zia Wadud closely focused on the theme of "To Own or not to Own? That is the Question!". In the context of the continuous development of autonomous vehicles, he demonstrated people's recognition and willingness to use autonomous vehicles, and explored the proportion of demand for private cars with manual and autonomous driving, as well as exclusive and shared autonomous driving calling services. At the same time, He also demonstrated how to obtain valuable results about the convenience of private cars through experimental means. This study closely follows the context of the times and provides a deep interpretation of the collision and fusion between the macro background of transportation technology progress and the micro individual rational choice. The conclusion is thought-provoking. The diverse discussions by two invited reviewers, Professor Chen Xiqun and Professor Jiang Rui, on the meaning, inspiration, and applicability of research conclusions have also provided useful insights for subsequent research and policy recommendations.

The third and fourth special lectures of the 2022 transportation series have inherited the academic discussion style and depth of academic dialogue from the first two special lectures, providing exciting ideas, rigorous research paradigms, beneficial research results, and profound insights for Chinese and foreign scholars, researchers, and university teachers and students attending the conference.