#09: "Autonomous Vehicles Modelling and its Network Evaluations" (Mar. 1, 2018)

In this seminar, we invited Prof. Schlomo Bekhor, who is a specialist in travel behavior modeling.

We had the discussion about "Autonomous Vehicles". It consists of the presentations by four researchers related to network assignment, optimization, and simulation.

Research Presentation #1:
"Connected Car and New Mobility Service Implication"

Kayoko Hara (Nissan Motor Co.)

Ms. Hara introduced "Easy Ride" which is the autonomous drive vehicles service developed by Nissan & DeNA. This autonomous drive vehicles are set very accurate digital map and detect signals and obstacles. It enables users to move to where they want to go with the application. Before the field test at Minatomirai area in Yokohama city where there are many kinds of people (residents, tourist, and worker), she checked the market volume in this area using Person Trip data and the SP survey they conducted. She pointed out that this result is static and what they want to know is the demand changing dynamically. Then, how to manage and how to calculate the demand dynamically are very big issues. And social understanding is also a big issue.

Research Presentation #2:
"Driving behavior modeling and simulation for autonomous vehicles"

 Tomer Toledo(Israel Technion)

Professor Tomer introduced micro-simulation for developing Autonomous Vehicles (AVs) to evaluate expected effects on traffic flow, safety, and externalities. In the simulation, driving models need good algorithms for autonomous driving that is longitudinal-lateral movement. Then, there are some challenges that are how to set variants, how to treat sensing and communications, and how to idealize human driving in semi-AVs. They conducted the experiment in which they checked Adaptive Cruise Control(ACC) state and vehicles movement. Applying these data to Mixed logit choice model, they analyzed the relation between ACC transitions and some parameters. After that, they run a simulation to check the harmonic speed changing ACC and C-ACC penetration rates, demand level, and automated minimum leader headway settings.

Research Presentation #3:
"Transportation network equilibrium in presence of autonomous vehicles"

 Schlomo Bekhor (Israel Technion)

Professor Bekhor posed questions that are "How will autonomous vehicles and traditional ones coexist?" and "How will the introduction of autonomous vehicles affect travel habits in general and the mode choice in particular?" These questions include whether AVs will induce people to travel more and whether they will benefit. Each intermediate scenario which is the result of introducing AVs can be seen as a parametrized combination of User Equilibrium (UE) and System Optimum (SO). He proposed the methodology using the dynamic representation of the problem. The initial calculation based on it using MSA (multi-scenario approach) showed the different tendency of moving from UE to SO in each example network.

Research Presentation #4:
"Connected vehicle auction and it's mechanism design"

 Keiichiro HAYAKAWA (Toyota Central R&D Labs., Inc)

Mr. Hayakawa showed the traffic situations with AVs in which there are complicated interactions between the administrator, service operators, and customers. Then, he focussed on the sequential mechanism for a service operator that aims to maximize social welfare. There, the objective is to maximize social welfare which is defined as the summation of the users’ utility based on Activity model under time-space constraints of users and under capacity constraints of the road network. To solve the problem, he used ZDD (Zero-suppressed binary decision diagram) and MSA. In numerical study, he showed that his proposed mechanism can remain high efficiency when increasing the number of agents. Finally, he suggested that his mechanism can be easily extended to an auction-based implementation by which the social optimal states are achieved.

#08: "Behavior Models and Optimization"(Oct. 13-14, 2017)

In this seminar, we invited Prof. Michel Bierlaire, who is a specialist in travel behavior modeling.

In addition, we had "bahavior in Networks Research Workshop", where seven speakers had presentations related to behavior modeling. It consists of three sessions, route choice, optimization, and special research talk by Prof. Michel Bielraire.

Keynote Lecture:
"Behavior Models and Optimization"

 Prof. Michel Bierlaire (Swiss Federal Institute of Technology in Lausanne) [PDF]

Professor Ben-Akiva gave us a keynote lecture regarding mainly to Smart Mobility applying a behavior model and optimization from concept to frameworks to case studies..

He presented a mobile data collection, a personalized correspondence using behavioral models, the improvement of efficiency in supply of mobility applying optimization, and an integrated smart planning composed of them as an important agenda in a new age of Smart Mobility. And concretely, he illustrated FMS that is a smartphone and prompted-recall-based integrated activity-travel survey using a combination of a smartphone app and an online prompted recall survey to collect both demographic and travel data from participants, FMOD that provides a personalized and optimized menu of travel options in real-time consisting of different modes with varying level of service including mini-bus, shared-taxi and taxi, MeMOT that designs, builds and trials a new system to incentivize people to adapt their travel choice to conserve energy using real and simulated personal travel data to reward people to shift their routes, departure times, modes of travel and vehicles based on live information they receive from MeMOT app and so on.

Research Presentation #1:
"Route choice behavior under extreme weather events in densified networks: a case study in Tokyo under torrential downpour"

Samal Sanjeewa Darmarathna (University of Tokyo) [PDF]

Travel behavior is changed under uncertainty. Especially, we focus on extreme weather events and research the route choice behavior during them in β-Scaled recursive logit model framework.Checking the data in Tokyo, we realize that travel time parameter increases indicating difficulty to assess difference of travel time in links during heavy rainy day, that sequential discount rate β decreases indicating tendency towards the myopic decision making behaviour, and so on.

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Behavior and Network Optimization Session 1:
"A strategy-proof mechanism of network pricing focusing on the activity-chain of agents"

 Keiichiro Hayakawa (TOYOTA CENTRAL R&D LABS., INC.) [PDF]

We establish fundamental algorithm to realize MaaS(Mobility as a Service) which allocate traffic resources optimally to users, considering heterogeneous users and slow traffic using auction-based approach. We have some problems to express this, but we introduce activity-state network which is an extended time-space network and time-constraint, and formalize activity-chain auction based on VCG mechanism. Moreover, We propose an algorithm, which is based on graph theory, to mitigate the computational complexity. Simulating based on this model, it can be said that by considering slow traffic, especially for cruising agents, the total social welfare can be increased.

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Behavior and Network Optimization Session 2:
"Reservoir-based Surrogate Modeling of Dynamic User Equilibrium Assignment "

 Qian Ge (Tokyo Institute of Technology) [PDF]

In Dynamic Traffic Assignment (DTA), we have to deal with Dynamic User Equilibrium(DUE), which is the assumption that the travel time of travels on all used paths is equal at user equilibrium in order to evaluate path cost. Firstly, variational inequalities formulation is adopted for DUE. However, this approach imposes high computation burden. Therefore, surrogate modeling is adopted to develop a DTA solver considering macroscopic traffic dynamics. It describes the mapping from path flow to path cost and can be viewed as a local approximation of mapping for the solution point. It performs better when the distance between sampled data and the solution are small. By iteratively solving the DUE problem, the accuracy of surrogate model will be improved accordingly.

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Behavior and Network Optimization Session 3:
"A macroscopic approach for optimizing road space allocation of bus lanes in multimodal urban networks through simulation analysis"

 Takao Dantsuji (Tokyo Institute of Technology) [PDF]

Transportation demand management (TDM) has problems that we cannot solve easily; congestion. Dedicated bus lane is regarded as one of the most promising solutions. In this study, road space allocation of the dedicated bus lanes is optimized quantitatively by using 3D-MFD (Macroscopic fundamental diagram). This approach adopts both static optimization model and simulation analysis model. In the Geneva case, around 15% of the space to the bus lanes is the most efficient. In the future study, it is useful to investigate the universality of this approach further with the Tokyo case, by improving the aggregate logit model or calibrating by the detectors data.

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Special Research Talk:
"A macroscopic approach for optimizing road space allocation of bus lanes in multimodal urban networks through simulation analysis"

 Prof. Michel Bierlaire (Swiss Federal Institute of Technology in Lausanne) [PDF]

In this session, Prof. Michel introduced various ongoing research projects in EPFL such as the analysis of traffic system of Ghana, the analysis of behavior of pedestrian in EU, the technology for detecting pedestrian in autonomous driving, the optimization of a timetable of Swiss Federal Railways and so on. He finished it with an big project which aims at "World without Car" by installing the moving walkway throughout the city.

At last, he gave an advice to young researchers that they pay attention to both updating technology and idea and problems in the world and match them.

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Early Bird Session 3:
"Structural Estimation for a route choice model with uncertain measurement"

 Yuki Oyama (The University of Tokyo)[PDF]

Mr. Oyama had a presentation about the route choice model estimated simultaneously with the route measurement model by GPS data. This approach is to resolve the 'loop' that the route choice data for estimating parameters of the route choice model is made by using parameters of route choice model and the assumption that error variance is constant among all links. Since estimating the proposed model corresponds to solving a fixed point problem, structural estimation method is applied. The effectiveness of proposed model and the estimation method is validated by twins experiments. When estimating parameters by using the real data, the dependency on each link of measurement error variance was shown. Also, the improvement of the estimation result was shown. As an example, travel time seemed to be significant from the result of one-way model while the arcade dummy variable was most likely to be significant and travel time was not significant from the result of structural estimation.

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#07: "Dynamics in Behavior Modeling with Advanced Observation"(Sep. 24-25, 2016)

In this seminar, we invited Prof. Moshe Ben-Akiva, who is a specialist in travel behavior modeling and currently engaged in projects regarding smart mobility.

In addition, three young speakers had presentations related to behavior modeling. The first presentator Mr. Seo introduced a new method for conducting travel survey which enables long-term and extensive investigation. Next, Mr. Urata discussed a methodology of modeling tsunami evacuation behavior accounting for dynamics of heterogeneity in ecpected utility. Lastly, Mr. Oyama proposed a new link-based route choice model under uncertain measurement with structural estimation method.

Keynote Lecture:
"Smart mobility: Optimization and Behavioral Modeling"

 Prof. Moshe Ben-Akiva (MIT) [PDF]

Professor Ben-Akiva gave us a keynote lecture regarding mainly to Smart Mobility applying a behavior model and optimization from concept to frameworks to case studies..

He presented a mobile data collection, a personalized correspondence using behavioral models, the improvement of efficiency in supply of mobility applying optimization, and an integrated smart planning composed of them as an important agenda in a new age of Smart Mobility. And concretely, he illustrated FMS that is a smartphone and prompted-recall-based integrated activity-travel survey using a combination of a smartphone app and an online prompted recall survey to collect both demographic and travel data from participants, FMOD that provides a personalized and optimized menu of travel options in real-time consisting of different modes with varying level of service including mini-bus, shared-taxi and taxi, MeMOT that designs, builds and trials a new system to incentivize people to adapt their travel choice to conserve energy using real and simulated personal travel data to reward people to shift their routes, departure times, modes of travel and vehicles based on live information they receive from MeMOT app and so on.

Early Bird Session 1:
"Automated and Adaptive Activity-Travel Survey using Online Interaction with Travelers"

Toru SEO (Tokyo Institute of Technology) [PDF]

Mr. Seo had proposed a new survey method for collecting travel data which is suitable for a long-term and extensive investigation. The proposed method estimates the type of the detectated activity, and questions to the traveler when the estimation confidence is lower than a particular rate.

The most likely type of the activity and the estimation confindence are calculated from the historical data based on Naive Bayes assumption.

The answer by the traveler or the estimated type of the activity is used as the traveler-specific historical data to the learning process of the model for estimation of the activity type. The proposed method is validated by using existing travel survey data. The error rate of the estimation stayed 5%, which is given by admin, and the frecuency of questions was almost halved after 12 days. The proposed method would be the survey method which reduces the burdan of travelers and keeps the quality of data high.

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Early Bird Session 2:
"Modelling of Tsunami Evacuation Behavior accounting for Dynamics of Heterogeneity in Expected Utility"

 Junji URATA (Kobe University) [PDF]

When we model the evacuation behavior, it would be important to acount for heterogeneity in expected utility and choices of the evacuation start time. Mr. Urata had formulated the sequential choice model in which a decision maker chooses to evacuate or to stay there at every term. The utility of staying at time t includes the expected utility when choosing to stay at time t (EV). In the evacuation situation the recognized expected utility would not be the same as the expected utility satisfying the Bellman equation, and may have some variance. Therefore, the new constraint Ω, the range of vairiance, is introduced. This model is validated by evacuation data in Rikuzentakata. The algorithm to estimate the model is constructed based on SQP method. The finel likelihood of the proposed model is higher than that of static model or dynamic model with no heterogeneity. Also, distribution of recognized expected utility in time and space was shown.

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Early Bird Session 3:
"Structural Estimation for a route choice model with uncertain measurement"

 Yuki Oyama (The University of Tokyo)[PDF]

Mr. Oyama had a presentation about the route choice model estimated simultaneously with the route measurement model by GPS data. This approach is to resolve the 'loop' that the route choice data for estimating parameters of the route choice model is made by using parameters of route choice model and the assumption that error variance is constant among all links. Since estimating the proposed model corresponds to solving a fixed point problem, structural estimation method is applied. The effectiveness of proposed model and the estimation method is validated by twins experiments. When estimating parameters by using the real data, the dependency on each link of measurement error variance was shown. Also, the improvement of the estimation result was shown. As an example, travel time seemed to be significant from the result of one-way model while the arcade dummy variable was most likely to be significant and travel time was not significant from the result of structural estimation.

  (read more...)

#06: "Modeling for capturing the diversity and changes in knowledge information society"(Sep. 25-27, 2015)

In recent years, the Information Communication Technology (ICT) and transport technology have been revolutionarily developed, and the way of communication and travel behavior are dynamic changing. In this seminar, we invited Prof. Fujita, who is a specialist in economic field and currently doing research on diversity and creativity in Brain Power Society.

Keynote Lecture: Diversity and Cultured in Knowledge Creation
-The Story of the Tower of Babel Revisited-

 Masahisa Fujita (Konan Univ./ Kyoto Univ./ RIETI) [PDF]

Professor Fujita gave us the lecture as a keynote lecture regarding mainly to the relationship between Knowledge productivity(K-productivity) and share of differential person's knowledge that quote from "The Story of the Tower of Babel Revisited".

He mentioned recent revolutionary development in ICT and Transport Technology. From the view point of this dynamic development, he pointed out the antinomy between in the short run, synergy might be growth though close communication, on the other hand, in the long run, common knowledge will be growth, even though diversity and synergy might be decrease. In terms of this antinomy, his research question is"Does ICT really enhance the K-productivity?" and also, "Does perfect automatic translation-machine(AI) really enhance the communication capacity and K-productivity? E

From this background, he formulated "the Endogenous Growth Model with Dynamic of Knowledge Diversity" considering the dynamics of knowledge heterogeneity due to the ICT development. And also, "the Multi-region Model of Knowledge Dynamics" considering the intra and inter regional interactions. And he show us the condition for achieving the most efficient K-production though the equilibrium dynamics.

At the tentative conclusion about the story of the tower of babel, regarding the question "expulsion from the paradise of effortless communication that mean multilingual / multi-cultural world, was it punishment, or blessing in disguise?" he answered "It could have been a blessing in disguise."

Early Bird Session 1:
“Firms ELocation Choice based on Trading and Financing Relationship"

 Ryo Fukuda (The University of Tokyo) [PDF]

Mr. Fukuda had a presentation about firms Erelocation behavior based on trading and financing relationship. Historically, transportation costs have been decreasing and population have been concentrating to a few larger cities. However, now firm’s relocation is mainly moving locally to not only larger cities. To clarify the mechanism of relocations, he focused on continuous relationship of firms including trading and financing transactions.

Using the database of Teikoku Databank, which is the largest credit research company in Japan, he analyzed firms Erelocation behavior, trading and financing network at first. Then, he applied nested logit model to explain location (municipality) selection and estimated parameters. As a result, the proposed model was more effective to relocation to medium-sized cities and of small & medium enterprises.

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Early Bird Session 2:
"Activity Opportunities and Changing Travel Patterns: A case of Developing Nations"

 Varun Varghese (IIT Mumbai) [PDF]

Mr. Varghese focused on activity opportunities and changing travel patterns, and presented the case study in India as a Developing Nation. The first part is about public transport crowding. In this part, he explained about the crowding of Ahmedabad city’s bus systems, and how to measure and calculate it. And in the second part, he focused on activity travel pattern in Mumbai. As the ICT technology has progressed, activity travel behavior of people who use mobile internet information can be changed. He proposed the framework to combine socioeconomic and spatial factors with ICT use in behavior modelings. And as the future work, he aims to develop an inter-regional destination choice model. It might be significant to better understand effects of policies related to long distance travel, such as infrastructure provisioning and facilities allocation, to activity opportunities.

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Early Bird Session 3:
"Context-Dependent Scheduling Model Considering Measurement Errors in Pedestrian Network"

 Yuki Oyama (The University of Tokyo)[PDF]

In pedestrian networks, activities can be generated context-dependently such as spatial attributes, social and activity interactions. To capture sequential decision making of pedestrians, Mr. Oyama modeled dynamic scheduling behavior based on the concept as energy, which is a personal resource for engaging activities and used as discrimination function of activity generation model. Using GPS data collected from Probe Person (PP) surveys in Matsuyama city, he stochastically inferred sequences of activities in pedestrian network considering measurement errors. In his model, walking links is assumed as an activity as well as staying at nodes, and these activities were connected with certain spaces through the bayesian approach. As a estimation result, it was clarified that the energy consumption and gain processes depend on some behavioral and spatial context variables.

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#05: "Modeling for evaluation of new urban transit and recent innovation in data-service technologies"(August 11, 2015)

The 5th International BinN research seminar, "Modeling for evaluation of new urban transit and recent innovation in data-service technologies" was took placed on Aug 11th, 2015. In this seminar, we mainly discussed the modeling for public transportation considering recent innovation in data-service technologies.

As keynote speakers, we invited Dr. Oded Cats from TU Delft and Dr.Jan-Dirk Schmöcker from Kyoto University. Dr. Cats is currently doing research on agent-based dynamic public transit modeling. And the keynote lectures focused on developed dynamic model and its application to real network. In addition, we discussed new approaches to new urban mobility modeling considering recent innovation of technologies.

Keynote Lecture 1: An agent-based approach to modelling public transport dynamics

 Oded Cats (TU Delft) [PDF]

The traditional PT assignment principle is frequency-based or schedule-based. This methods Eemerging developments are multi-agent simulation models, dynamic loading process, and so on.

Research question is how the system performs under various dynamic conditions. This study propose an agent-based approach to PTA. Agent-based TAM represents individual vehicles and travellers, agents Einteraction, en-route decisions and day-to-day learning. Implementation is BusMezzo. Using transit vehicle trajectory and traveller trajectory, transit modes and dwelling times are specified. The travel demand is represented by poisson arrival process. This simulation model includes non-compensatory rule-based choice-set generation process. En-route decisions are based on assessment of the attributes of each available path, and calculation of the joint utility.This model is applied for incleased capacity situation. For example, crowding factor is 3% at static model, but 60% in dynamic model. Based on Real-time information, the weakest path can be detected.

Keynote Lecture 2: Smart transit systems for even smarter travellers

 Jan-Dirk Schmöcker (Kyoto Univ.) [PDF]

Prof. Jan-Dirk Schmöcker provided a keynote lecture regarding smart transit with real time information considering bus bunching.

Firstly he revealed why bus bunching arises when passengers have real time information (RTI). Because boarding rate is influenced by travelers given RTI, even without exogenous delays bus bunching arises.

Secondly, he transformed classic route choice problem with hyperpaths formulated by Spiess and Florian into multiple local demon game assuming risk-averse users and demons aiming to maximise delay. And then based on it, a smart transit with RTI in bus services can be transformed into single local demon game. Not only with formulations but also with actual effects, it was shown that the travelers behave in different ways at each departure point depending on how much well informed in advance they are.

In conclusion, in smart transit which gives “good Einformation to travelers, they can benefit from it. However, there is also a risk that the system can be outsmarted by the travelers. Therefore, even more information and management of network may be required.

Research Presentation 1:
"Innovative ITS Approaches for Control of Large-Scale Urban Networks"

 Mehdi Keyvan-Ekbatani (TU Delft) [PDF]

Dr. Keyvan-Ekbatani focused on gating control, which is a practical tool for mitigating congestion in urban networks, and evaluated its efficiency using network or macroscopic fundamental diagram (NFD or MFD). When gating is located upstream of protected network (PN) to keep the network under-saturated, time-delay to approach PN is induced.

To deal with time-delay, Dr. Keyvan-Ekbatani proposed the developed feedback regulators, and tested gating performances using this concept. In experiment in urban network of Chania (Greece) and San-Francisco, the results showed that gating strategy acted efficiently and leads to significant improvements in mean speed and delay at the overall network level.

Research Presentation 2:
"Demand control management for one-way car sharing system focus on the imbalance between demand and supply"

 Nodoka Kasahara (Tokyo Univ.) [PDF]

Ms.Kasahara’s research focused on the Demand control management for One –way Car sharing service named “Choi-mobi Eby applying price optimization. By using Probe Person data that is activity diary and trajectory data by GPS, and use result data, she formulated the profit maximization problem by changing the price of this service. In this formulation dynamic programming method was applied. As a result of the numerical example, it was confirmed that price control have effect for the demand control. Furthermore micro simulation was calculated considering the availability of service in the real network in Yokohama, Japan and evaluate the pricing strategy.

#04: "Dynamic modeling based on bounded rationality to understand diversifying travel behavior"(June 13, 2015)

Although much progress has been made over the years, the basis of current transport models is still the rational-agent model. This traditional view is regarded to lead to numerous biases in the description of human behavior. In this seminar, new approaches to travel behavior modeling based on bounded rationality are discussed, particularly focusing on how to accurately represent the decision making context and process. In addition, this seminar aims at discussing about methods for integrating new data and technologies into models.

In this seminar, as keynote speakers, we will invite Dr. Theo Arentze from Eindhoven University of Technology and Prof. Morikawa from Nagoya University. Dr. Arentze is currently doing research on dynamic activity-based modeling involving human cognition and learning. The keynote lectures will focus on bounded rationality in individual decision making, and its implications for policy making. In addition, two invited researchers will discuss new approaches to disaggregate behavioral modeling.

Keynote Lecture 1: The role of bounded rationality in travel choice behavior and implications for transport modeling

 Theo Arentze (Eindhoven University of Technology) [PDF]

In travel demand models, micro simulation models based on the activity-based approach have been developed from early 19 century. These are developed from static to dynamic and including social networks and interactions based on new survey methods and data sources, for example GPS data. He incorporates bounded rartionality in travel demand models. The model with bounded rationality are composed of 3 steps of cycle, learning & judgment, search & information acquisition, and evaluation & decision. In these 3 steps, biases are well-documented, such as memory biases, limited search, and emotional weighting.

He proposed new modeling approach using habitual behavior and spatial search. From a dataset of an agent’s set of scripts, He defined utility of a script. This is composed of activity component and travel component. An agent choose the script that maximizes utility. If agents are dissatisfied with current set of scripts, then the agent starts exploration. The probability that a location is specified as logit model using conditional probability used ρE ρErepresents lack of information. Effect of memory and emotion is represented by a model of memory encoding and retrieval processes. This model explains primary and secondary biases.

Keynote Lecture 2: Bounded rationality in travel behavior modeling

 Takayuki Morikawa (Nagoya University) [PDF]

Professor Morikawa’s lecture focused on the bounded rationality in travel behavior modeling and decision making strategies. First, he gave an overview of the three types of rationality and 6 type of decision-making strategies. Then, he showed the framework for the bounded rationality with latent classes. Furthermore, two case studies were introduced. First one was about the mode choice between car and dynamic P&R using a semi-ordered lexicographic rule including both compensatory and non-compensatory decision making rules. Second one, more psychological approach, was by applying mental accounting theory, he aimed to analyze the effect of Ride Point Program in the context of discrete choice travel behavior.

Research Presentation 1:
"Modeling shopping behavior in a neighborhood with endogenous representation of retail attractiveness"

 Makoto Chikaraishi (Hiroshima University) [PDF]

Dr. Chikaraishi developed a model of shopping behaviour in a neighbourhood with social interactions. It shows retail attractiveness as endogenous. The important point of this model is to deal with market/non-market interactions not through “average Ebehaviour but through “aggregate Ebehaviour. This model is estimated by NFXP algorithm. By using this model, an empirical analysis was performed using 10 networks in Hiroshima city. It confirmed significant endogenous effect but it did not give multiple equilibrium.

Main point in the discussion part is whether new elements can be applied to that model or not, such as history/strategy of supply side (i.e. supermarket), interactions on floor space and average/personal income information. Since the available data is limited and developing the estimation method is difficult, it is challenging but possible to fulfil some of the requirements.

Research Presentation 2:
"Choice set generation of pedestrian route choice using data distribution of walking behavior in urban space"

 Sachiyo Fukuyama (National Institute for Land and Infrastructure Management) [PDF]

Dr. Fukuyama proposed a data-oriented approach for choice set generation of pedestrian route choice behavior. In this research, she applied Branch and Bound (Prato and Bekhor, 2006) and sampling method using data distribution from the probe person surveys. Branching rules in her study consist of destination directivity, keep-direction rate and detour rate. She concluded this approach is able to be applied for individual choice set generation which reflects the characteristics of individual behavior when they have enough amount of trajectory data.

#03: "Network configuration and multi-scale behavior analysis"(March 4, 2015)

The optimal spatial scale of analysis of travel behavior differs given the target behavior of interest. As a result, modelling travel behavior in micro, meso and macro scale is necessary to adequately analyze and evaluate transportation networks. In addition, scale aggregation is sometimes necessary not only to match the scale at which spatial recognition is conducted by individuals, but also to reduce calculation costs. This seminar aims at deepen the discussion regarding the relationship between spatial configuration and travel behavior in a multi-scale framework.

In this seminar, we invited Dr. Richard Connors from the Institute for Transport Studies (University of Leeds). Dr. Connors is currently doing research on network equilibrium and topological configuration of transportation networks.

Keynote Lecture: Ensemble Analysis of Transport Networks

 Richard Connors (University of Leeds) [PDF]

Dr. Connors focused on the relation between network performance and topology, and sought to answer the question: How does network topology structure affects network performance (e.g. efficiency, vulnerability)? To investigate this relation, among a set of possible indicator variables, he applied the concept of “Meshedness Eas a single variable summarizing network topology, and “Price of Anarchy EPoA) as a performance indicator. PoA is defined as the ratio of the Total Travel Cost (TTC) under User Equilibrium (UE) routing to the TTC under Stochastic Optimal (SO) routing.

Connors examined network performance across a wide “spectrum Eof networks in order to understand the relation between PoA and network size, density, and connectivity. In addition, he tried to undesrtand how PoA depends on demand, and concluded that the variation of PoA with travel demand is due to activation of routes at different levels of demand under UE and SO (route activations is defined as increase in the number of links which are used caused by demand increase).

Research Presentation 1:
"An experimental study of driving behavior of Personal Mobility Vehicles"

 Miho Iryo-Asano (The University of Tokyo) [PDF]

Personal Mobility Vehicles (PMVs) have high potential as an intermediate mode between walking and cars. However in most cases PMVs are of limited use, such as in the airports, shopping malls, golf courses etc. This preliminary study analyzed conflicts between pedestrian and PMVs, In particular, how did PMVs users avoid pedestrians.

In this experiment, a Robstep M1 vehicle was used (Max speed is 15km/h, Min Speed is 9km/h). Position data was gathered through video monitoring, while an android app was used to measure wheel speed. 30 monitors conducted 24 tries each. It was hypothesized that the PMV will travel along the shortest path (timewise) and adapt his behavior to avoid the coming pedestrian in two ways: by changing its direction angle, or adjusting speed. Preliminary findings suggest that all else equal, rear avoidance is preferred to front avoidance.

Research Presentation 2:
"A joint estimation model of destination choice and evacuation timing: Case study of Kesennuma City"

 Giancarlos TRONCOSO (The University of Tokyo) [PDF]

The analysis of travel behavior under disaster situations consists mainly of three main stages 1) evacuation participation and departure time choice 2) Destination choice and 3) route choice. Although there is enough evidence to suggest that these phases are interdependent, due to model complexities most studies model these phases independently. This presentation focused on this gap in the literature by proposing a discrete-continuous model of Tsunami evacuation destination choice and evacuation timing. Data from the Great East Japan Earthquake is used to estimate the model. Travel behavior data from the day of the earthquake was gathered by the Ministry of Land, Infrastructure, Transport and Tourism (MLIT) of Japan via a travel diary. In terms of the methodology used, based on the premise that both outcomes might in fact be jointly determined, a discrete-continuous model is formulated. Destination choice is formulated as a multinomial logit model, where the choice set is generated as a function of location altitude in order to account for tsunami risk. Evacuation timing is estimated as an accelerated failure time survival model. Results validate the use of a discrete continuous approach as several error correlation parameters were statistically significant. Among factors found to affect destination choice were OD distance, OD altitude difference, which is estimated as a quadratic function, average slope of destination and total number of buildings in destination. Regarding evacuation timing, significant variables include the use of car for evacuation, altitude at origin knowledge of refuge locations, and age.

#02: "Advanced activity model for capturing dynamic changes"(Sept 27-28, 2014)

In this decade, activity-based models based on a succesive choices have become progressively popular. Activity-based models are able to illustrate and evaluate personal activities and their traffic environment. The models have been implemented for various policy applications. In this seminar, we invited Prof. Shlomo Bekhor, from the Israel Institute of Technology, who specializes on behavioral models, transportation planning and network optimization.

Keynote Lecture: Stability analysis of Activity-Based models
-Case study of the Tel Aviv Transportation Model-

 Shlomo Bekhor (Israel Institute of Technology) [PDF]

Professor Bekhor’s lecture focused on the issues regarding practical implementation of Activity-Based Models (ABM). The lecture was divided into two parts. The first part departs from the advantages of implementing Activity-Based Models over the traditional 4-Step approach. The first part of the lecture introduced the model implemented in Tel-Aviv City, in Israel, which is based on the hierarchical model proposed by Bowman and Ben-Akiva (2001).

The second part of the presentation focused on the stability of ABMs, which is a critical issue on these type of models due to its probabilistic nature (As opposed to the deterministic nature of the 4-Step model). Professor Bekhor pointed out to three main sources of error that might compromise the stability of the ABMs, namely, assignment accuracy, the random component in the tour generation models, and the population sampling.

Regarding, assignment error, as in previous studies, assignment errors can be eliminated using path-based assignment algorithms. Regarding tour-generation randomness, averaging results of model runs might be successful in mitigating error. Finally, regarding, population sampling, instead of sampling from the population, Professor Bekhor recommended using the full population, as sampling does not bring any significant savings in the number of iterations (as more iterations are required to converge), and might compromise the accuracy of ABMs.

To conclude, one of the most important limitations in ABMs might come from the uncertainty in the synthetic population generation, which is created from a limited set of aggregated control variables.

Early Bird Session 1:
"Transportation system monitoring method by using probe vehicles that observe other vehicles"

 Toru SEO (Tokyo Institute of Technology) [PDF]

Mr. Seo’s presentation is aim to acquire volume-related info over a wide range, and proposes a new method for estimating traffic states using probe vehicles with spacing measurement equipment. Then validates the method under an actual condition in Tokyo. Mr. Seo reports that high resolution information can be acquired where enough number of probe vehicle exist. And mentions a system model of microscopic travel behaviors and pedestrian space as future works.

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Early Bird Session 2:
"The built environment-travel behavior connection: A propensity score approach under a continuous treatment regime"

 Giancarlos TRONCOSO (The University of Tokyo) [PDF]

In recent years, the concept of urban development is changing into which promote the population concentration to cities center, like a compact city, from a viewpoint of the breakaway from the society of automatic automobile dependency. However, it is not clarified about the causal relationship which built environment gives to traval behavior of individuals and households. This is because the right causal effect cannot be explained in cross-sectional data since selection bias occurs by the background covariates of a specimen.

To overcome these limitations, Dr. Troncoso had an eye to the "propensity score" approach (Rosenbaum and Rubin, 1984). This score is the conditional probability of treatment given observed covariates and can explain the causal effect which eliminated the selection bias. This approach is originally used under binary treatment regimes, but can be generalized under continuous treatment regimes (Imai and Van Dyk, 2004).

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Early Bird Session 3:
"Accommodating spatial correlation in local-interaction formation model under a heavy rain disaster"

 Junji Urata (The University of Tokyo)[PDF]

This study focus on making interactions under a disaster in a settlement. An interaction between two people is influenced not only by two but also by others in group. The process of making interactions are modeled as a group decision-making. This model capture a spatial correlation of interactions. The correlations arise from spatial risks and travel costs. The correlations are formulated by spatial divisions. The model structure is a network-GEV model (Daly & Bierlaire(2006)). In this study, a case study is shown. The utility of making interactions are set by a altruistic utility which is a difference of risk.

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#01: "Dynamic Travel Behavior Modelling for Evacuation"(July 12, 2014)

In Japan, many local government prepare for infrastructure of disaster reduction and many people study on disaster reduction after the Great East Japan Earth quake(2011). In the world, the evacuation behavior studies attracts attention after Sumatra-Andaman arthquake(2004) and Hurricane Katrina(2005). We need the citizens' evacuation behavior analysis, the evacuation traffic management by information technology and the road network design for evacuation.

In this seminar, we invited Dr. Pel, who is a young researcher and study on evacuation behavior and talked about dynamic travel behavior modelling for evacuation. Dynamic management and forecasting are needed for optimal evacuation because travel time are limited under disaster situation. We discussed about the direction of thesis of evacuation behaviors and managements.

Keynote Lecture: Route choice Behavior and Optimal traffic management in Evacuation

 Adam Pel (TU Delft) [PDF]

Dr. Pel's lecture gave an overview about the research efforts at TU Delft focusing on improving route choice behavior and traffic management during evacuation situations. Dr. Pel explained that in terms of evacuation research, the key challenge is the development of theory and models to predict evacuation behaviors, incorporating factors such as how people react to disaster information and evacuation instructions, and taking into consideration uncertainty in parameter estimation. Certainly uncertainty is a crucial aspect when discussing evacuations, as travelers are not familiar with emergency situations, they might behavior changes due to stress and emotions, and infrastructure may be affected by disaster.

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Research presentation 1: "Direction of evacuation traffic"

 Takamasa Iryo (Kobe University)

Dr. Iryo's presentation discussed the issue of traffic evacuation directions using the Great East Japan Earthquake as a case study. The presentation challenged the assumption of a unique destination used in Dynamic Traffic Assignment (DTA) for evacuation analysis. Dr. Iryo argued that in the case of disasters trip purposes can in fact be heterogeneous, because the only purpose is not evacuation. This paper was tested using evacuation data from some cities in Tohoku during 3.11. Findings in fact suggested that the direction of evacuation trips was quite clear (homogeneous), but also showed the existence of other trips such as picking up family members, that are rather heterogeneous.

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Research presentation 2: "A Dynamic Discrete Choice Model of Collective Behaviors incorporated in Spatial Reference Group under Disaster Situation"

 Junji Urata (The University of Tokyo)[PDF]

Mr. Urata’s presentation focused on understanding collective behavior during disaster situations. And explain how to use a dynamic discrete choice modelling framework to understand the process of collective behavior formation. Mr. Urata further argues that collective behavior predictions can be helpful in developing an efficient local evacuation management plan and an adequate information propagation system.

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