scholarly journals Exploring the correlations between spatiotemporal daily activity-travel patterns and stated interest and perception of risk with self-driving cars

2020 ◽  
Vol 1 ◽  
pp. 1-15
Author(s):  
Jingyi Xiao ◽  
Rongxiang Su ◽  
Elizabeth C. McBride ◽  
Konstadinos G. Goulias
Keyword(s):  
Public Transportation ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Daily Activity ◽  
Puget Sound ◽  
Travel Patterns ◽  
Multinomial Regression ◽  
Multinomial Regression Model ◽  
People’S Attitudes ◽  
Self Driving Cars

Abstract. The key to Autonomous Vehicles (AVs) successful penetration of markets lies in identifying specific needs that AVs satisfy for daily activity-travel participation of individuals. In this paper we explore whether and to what extent people’s exhibited spatiotemporal activity-travel patterns correlate with their stated perceptions about self-driving cars. We investigate the travel diaries of 3,411 survey respondents who live in the Puget Sound region of the U.S. in 2017 using sequence analysis. In parallel, we apply hierarchical clustering to identify people’s attitudes based on their stated interest and perception of risks about AVs. A multinomial regression model is built to examine the correlations between AV attitude clusters and daily activity-travel patterns. Statistically significant correlations are then identified. The model results suggest that people exhibiting different activity-travel behavior patterns also express distinct attitudes towards the uses of AVs. The model shows that people who travel to work during the day are more likely to be positive to AVs. In particular, the group traveling to work later than the regular 8-to-5 schedule shows stronger interest and less concerns to AVs, which can be partially explained by the diverse activities they do throughout the day, the variety of travel modes they use and presumably more schedule flexibility they need than the public transportation system offers.

Pedestrians, Autonomous Vehicles, and Cities

2016 ◽  
Vol 38 (1) ◽  
pp. 6-12 ◽  
Author(s):  
Adam Millard-Ball
Keyword(s):  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Urban Neighborhoods ◽  
Urban Traffic ◽  
Risk Averse ◽  
Strategic Interactions ◽  
Road Users ◽  
Self Driving Cars ◽  
Time Autonomous

Autonomous vehicles, popularly known as self-driving cars, have the potential to transform travel behavior. However, existing analyses have ignored strategic interactions with other road users. In this article, I use game theory to analyze the interactions between pedestrians and autonomous vehicles, with a focus on yielding at crosswalks. Because autonomous vehicles will be risk-averse, the model suggests that pedestrians will be able to behave with impunity, and autonomous vehicles may facilitate a shift toward pedestrian-oriented urban neighborhoods. At the same time, autonomous vehicle adoption may be hampered by their strategic disadvantage that slows them down in urban traffic.

scholarly journals Simulation of the Daily Activity Plans of Travelers Using the Park-and-Ride System and Autonomous Vehicles: Work and Shopping Trip Purposes

2020 ◽  
Vol 10 (8) ◽  
pp. 2912 ◽  
Author(s):  
Jairo Ortega ◽  
Jamil Hamadneh ◽  
Domokos Esztergár-Kiss ◽  
János Tóth
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Daily Activity ◽  
Transport Mode ◽  
Park And Ride ◽  
Activity Chain ◽  
Private Car ◽  
Transport Modes ◽  
The Impact

The preferences of travelers determines the utility of daily activity plans. Decision-makers can affect the preference of travelers when they force private car users to use park-and-ride (P&R) facilities as a way of decreasing traffic in city centers. The P&R system has been shown to be effective in reducing uninterrupted increases in traffic congestion, especially in city centers. Therefore, the impacts of P&R on travel behavior and the daily activity plans of both worker and shopper travelers were studied in this paper. Moreover, autonomous vehicles (AVs) are a promising technology for the coming decade. A simulation of the AV as part of a multimodal system, when the P&R system was integrated in the daily activity plans, was carried out to determine the required AV fleet size needed to fulfill a certain demand and to study the impacts of AVs on the behavior of travelers (trip time and distance). Specifically, a group of travelers, who use private cars as their transport mode, was studied, and certain modifications to their daily activity plans, including P&R facilities and changing their transport mode, were introduced. Using the MATSim open-source tool, four scenarios were simulated based on the mentioned modifications. The four scenarios included (1) a simulation of the existing transport modes of the travelers, (2) a simulation of their daily activity plans when their transport modes were changed to AVs, (3) a simulation of the travelers, when P&R facilities were included in their activity chain plans, and (4) a simulation of their daily activity plans, when both P&R and AVs were included in their activity chain plans. The result showed that using the P&R system increased overall travel time, compared with using a private car. The results also demonstrated that using AVs as a replacement for conventional cars reduced travel time. In conclusion, the impact of P&R and AVs on the travel behavior of certain travelers was evaluated in this paper.

scholarly journals Autonomous vehicles and smart cities: future directions of ownership vs shared mobility

2020 ◽  
Author(s):  
Nacer-Eddine Bezai ◽  
◽  
Benachir Medjdoub ◽  
Fodil Fadli ◽  
Moulay Larby Chalal ◽  
...  
Keyword(s):  
Public Transportation ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Smart Cities ◽  
Autonomous Vehicle ◽  
Travel Speed ◽  
On Demand ◽  
Shared Mobility ◽  
The Future ◽  
Self Driving Cars

Over the last decade, there has been increasing discussions about self-driving cars and how most auto-makers are racing to launch these products. However, this discourse is not limited to transportation only, but how such vehicles will affect other industries and specific aspects of our daily lives as future users such as the concept of work while being driven and productivity, entertainment, travel speed, and deliveries. Although these technologies are beneficial, access to these potentials depends on the behaviour of their users. There is a lack of a conceptual model that elucidate the acceptance of people to Self-driving cars. Service on-demand and shared mobility are the most critical factors that will ensure the successful adoption of these cars. This paper presents an analysis of public opinions in Nottingham, UK, through a questionnaire about the future of Autonomous vehicles' ownership and the extent to which they accept the idea of vehicle sharing. Besides, this paper tests two hypotheses. Firstly, (a) people who usually use Public transportation like (taxi, bus, tram, train, carpooling) are likely to share an Autonomous Vehicle in the future. Secondly, (b) people who use Private cars are expected to own an Autonomous Vehicle in the future. To achieve this aim, a combination of statistical methods such as logistic regression has been utilised. Unexpectedly, the study findings suggested that AVs ownership will increase contrary to what is expected, that Autonomous vehicles will reduce ownership. Besides, participants have shown low interest in sharing AVs. Therefore, it is likely that ownership of AVs will increase for several reasons as expressed by the participants such as safety, privacy, personal space, suitability to children and availability. Actions must be taken to promote shared mobility to avoid AVs possession growth. The ownership diminution, in turn, will reduce traffic congestion, energy and transport efficiency, better air quality. That is why analysing the factors that influence the mindset and attitude of people will enable us to understand how to shift from private cars to transport-on-demand, which is a priority rather than promoting the technology.

scholarly journals PERILAKU PERJALANAN PENGGUNA SEPEDA MOTOR UNTUK TUJUAN BEKERJA DI PUSAT KOTA SEMARANG (STUDI KASUS: KORIDOR SEGITIGA EMAS)

2019 ◽  
Vol 21 (1) ◽  
pp. 23
Author(s):  
Jonathan Suek ◽  
Okto Risdianto Manullang
Keyword(s):  
Public Transportation ◽  
Travel Behavior ◽  
Structural Equation ◽  
Equation Model ◽  
School Age Children ◽  
School Age ◽  
Travel Patterns ◽  
City Center ◽  
Transport Services ◽  
The City

Working activity is one of the subsistence activities with the highest motivation level to travel. In Semarang City, the workplace is still dominant (75.04%) located in the city center, so the city center has a great attraction. It makes the provision of public transportation, such as Trans Semarang has a high service area in the city center. Currently, the Segitiga Emas Corridor has been serviced by 5 bus lines, but workers are still using motorcycles. In city scale, the dependency of motorcycle use reached 79.58% in Semarang City. On the other hand, the value of Trans Semarang loading factor is only 54%. This phenomenon is suspected to occur because of public transport services that have not been in accordance with the user’s travel behavior. Travel behavior can be measured through travel patterns that are formed by scheduling daily activities. Decisions in determining travel patterns are inseparable from the socio-demographic, economic and residential aspects. This study aims to understand the relationship between the travel patterns of workers with these aspects, as well as analyzing predictor variables on understanding the provision of urban mass transportation. The research method used is quantitative approach by using descriptive statistics and multivariate analysis through structural equation model (SEM). The results showed that unmarried workers and workers who do not have children or already do not have children at school age are potential workers who can switch modes to Trans Semarang (49,5%). Therefore, married workers with dual-earners in households, have 1-2 school-age children and small households tend to travel complex and difficult to facilitate by Trans Semarang service. Thus, transport services should be tailored to the characteristics and needs of workers, at least for potential demand to attract new users

Modeling Individual Preferences for Ownership and Sharing of Autonomous Vehicle Technologies

2017 ◽  
Vol 2665 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Patrícia S. Lavieri ◽  
Venu M. Garikapati ◽  
Chandra R. Bhat ◽  
Ram M. Pendyala ◽  
Sebastian Astroza ◽  
...  
Keyword(s):  
Travel Behavior ◽  
Autonomous Vehicles ◽  
Network Performance ◽  
Transportation Network ◽  
Autonomous Vehicle ◽  
Puget Sound ◽  
Heterogeneous Data ◽  
Model System ◽  
Vehicle Technologies ◽  
The One

Considerable interest exists in modeling and forecasting the effects of autonomous vehicles on travel behavior and transportation network performance. In an autonomous vehicle (AV) future, individuals may privately own such vehicles, use mobility-on-demand services provided by transportation network companies that operate shared AV fleets, or adopt a combination of those two options. This paper presents a comprehensive model system of AV adoption and use. A generalized, heterogeneous data model system was estimated with data collected as part of the Puget Sound, Washington, Regional Travel Study. The results showed that lifestyle factors play an important role in shaping AV usage. Younger, urban residents who are more educated and technologically savvy are more likely to be early adopters of AV technologies than are older, suburban and rural individuals, a fact that favors a sharing-based service model over private ownership. Models such as the one presented in this paper can be used to predict the adoption of AV technologies, and such predictions will, in turn, help forecast the effects of AVs under alternative future scenarios.

Analysis of Lifestyle Choices: Neighborhood Type, Travel Patterns, and Activity Participation

2002 ◽  
Vol 1807 (1) ◽  
pp. 119-128 ◽  
Author(s):  
Kevin J. Krizek ◽  
Paul Waddell
Keyword(s):  
Travel Behavior ◽  
Puget Sound ◽  
Residential Location ◽  
Three Dimensions ◽  
Activity Participation ◽  
Travel Patterns ◽  
Vehicle Ownership ◽  
Lifestyle Choices ◽  
Household Travel ◽  
Neighborhood Type

Activity-based travel modeling has begun to make significant progress toward a more behavioral framework for simulating household travel behavior. A significant challenge remains in the need to address the interaction of daily activity and travel patterns with longer-term household choices of vehicle ownership, residential location, and employment location. The choices often depend on one another and jointly define the lifestyle of the household. These choices are likely to evolve over the course of the life cycle as households are formed; as children are born, raised, and ultimately depart to form their own households; and as retirement and old age change patterns of residence, work, and travel. A framework is developed for analyzing household choices relating to three dimensions of lifestyle: travel patterns (including vehicle ownership), activity participation, and residential location (neighborhood type). With cluster analysis on data from the Puget Sound Transportation Panel, nine classifications of lifestyle are uncovered. These clusters demonstrate empirically how decisions of residential location reinforce and affect daily decisions related to travel patterns and activity participation. The applicability of these lifestyle clusters for land use transportation planning is discussed.

scholarly journals Travel Behavior of Car Travelers with the Presence of Park-and-Ride Facilities and Autonomous Vehicles

2021 ◽  
Author(s):  
Jamil Hamadneh ◽  
Domokos Esztergár-Kiss
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Daily Activity ◽  
Policy Makers ◽  
Park And Ride ◽  
People Search ◽  
Parking Pricing ◽  
The Impact

Travelers' behavior is predicted based on their individual preferences. People search for alternatives to maximize their benefit from doing activities, such as increasing the activity time by minimizing the travel time. Traffic congestion and the scarcity of parking spaces in the city center motivate the decision-makers to encourage travelers to use the park-and-ride (P&R) system. An evaluation concerning the impact of using the P&R system on the travel behavior of car users is conducted. Some of the existing P&R facilities are incorporated into the daily activity plans of car travelers to produce new daily activity plans (i.e., P&R facility is considered an activity). By using the Multi-Agent Transport Simulation (MATSim) open-source tool, simulations of the daily activity plans including the P&R system and autonomous vehicles (AVs) are conducted. The study examines three scenarios: (1) a simulation of the existing condition, (2) a simulation of the daily activity plans of the travelers with the P&R system, and (3) a simulation of the daily activity plans of the travelers with the P&R system and AVs. The results show that using the P&R system increases the overall travel time compared with the existing conditions, and the use of AVs as a transport mode impacts the existing modal share as follows: 64 % of the car users switch to AVs, while 15 % of the car users switch to public transport. The output of this study might be used by policy-makers in parking pricing and the location of the P&R facilities.

scholarly journals The impacts of mediating the work environment on the mode choice in work trips

2021 ◽  
Vol 11 (1) ◽  
pp. 592-605
Author(s):  
Melchior Bria ◽  
Ludfi Djakfar ◽  
Achmad Wicaksono
Keyword(s):  
Work Environment ◽  
Public Transportation ◽  
Travel Behavior ◽  
Structural Equation ◽  
Mode Choice ◽  
Equation Modeling ◽  
Rapid Transit ◽  
Long Time ◽  
Socio Economic Variables ◽  
The Relationship

Abstract The impacts of work characteristics on travel mode choice behavior has been studied for a long time, focusing on the work type, income, duration, and working time. However, there are no comprehensive studies on the influence of travel behavior. Therefore, this study examines the influence of work environment as a mediator of socio-economic variables, trip characteristics, transportation infrastructure and services, the environment and choice of transportation mode on work trips. The mode of transportation consists of three variables, including public transportation (bus rapid transit and mass rapid transit), private vehicles (cars and motorbikes), and online transportation (online taxis and motorbike taxis online). Multivariate analysis using the partial least squares-structural equation modeling method was used to explain the relationship between variables in the model. According to the results, the mediating impact of work environment is significant on transportation choices only for environmental variables. The mediating mode choice effect is negative for public transportation and complimentary for private vehicles and online transportation. Other variables directly affect mode choice, including the influence of work environment.

scholarly journals The opportunity of shared autonomous vehicles to improve spatial equity in accessibility and socio-economic developments in European urban areas

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Norman Eppenberger ◽  
Maximilian Alexander Richter
Keyword(s):  
Educational Attainment ◽  
Unemployment Rate ◽  
Public Transport ◽  
Public Transportation ◽  
Autonomous Vehicles ◽  
Well Being ◽  
District Level ◽  
Positive Effects ◽  
Spatial Equity ◽  
Economic Well Being

Abstract Background This paper provides insight into the opportunity offered by shared autonomous vehicles (SAVs) to improve urban populations’ spatial equity in accessibility. It provides a concrete implementation model for SAVs set to improve equity in accessibility and highlights the need of regulation in order for SAVs to help overcome identified spatial mismatches. Methodology Through the formulation of linear regression models, the relationship between land-use and transportation accessibility (by car and public transport) and socio-economic well-being indicators is tested on district-level in four European cities: Paris, Berlin, London and Vienna. Accessibility data is used to analyse access to points of interest within given timespans by both car and public transport. To measure equity in socio-economic well-being, three district-level proxies are introduced: yearly income, unemployment rate and educational attainment. Results In the cities of Paris, London and Vienna, as well as partially in Berlin, positive effects of educational attainment on accessibility are evidenced. Further, positive effects on accessibility by yearly income are found in Paris and London. Additionally, negative effects of an increased unemployment rate on accessibility are observed in Paris and Vienna. Through the comparison between accessibility by car and public transportation in the districts of the four cities, the potential for SAVs is evidenced. Lastly, on the basis of the findings a ‘SAV identification matrix’ is created, visualizing the underserved districts in each of the four cities and the need of equity enhancing policy for the introduction of SAVs is emphasized.

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