Exploring Factors that Influence Connected Drivers to (Not) Use or Follow Recommended Optimal Routes

Samson, Briane Paul V.; Sumi, Y.

doi:10.1145/3290605.3300601

Cited by 16 publications

(14 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Yet, not everyone might feel comfortable even with these standard AI-based services from the start. For example, Al Mahmud, Mubin and Shahid (2009) state that younger drivers have a more positive user-experience than older ones when using a new navigation system; while Samson and Sumi (2019) emphasise that navigation systems need to be personalised to encourage their use in all situations.…”

Section: Introductionmentioning

confidence: 99%

The effects of personality and locus of control on trust in humans versus artificial intelligence

Sharan

Romano

2020

Heliyon

View full text Add to dashboard Cite

Introduction We are increasingly exposed to applications that embed some sort of artificial intelligence (AI) algorithm, and there is a general belief that people trust any AI-based product or service without question. This study investigated the effect of personality characteristics (Big Five Inventory (BFI) traits and locus of control (LOC)) on trust behaviour, and the extent to which people trust the advice from an AI-based algorithm, more than humans, in a decision-making card game. Method One hundred and seventy-one adult volunteers decided whether the final covered card, in a five-card sequence over ten trials, had a higher/lower number than the second-to-last card. They either received no suggestion (control), recommendations from what they were told were previous participants (humans), or an AI-based algorithm (AI). Trust behaviour was measured as response time and concordance (number of participants' responses that were the same as the suggestion), and trust beliefs were measured as self-reported trust ratings. Results It was found that LOC influences trust concordance and trust ratings, which are correlated. In particular, LOC negatively predicted beyond the BFI dimensions trust concordance. As LOC levels increased, people were less likely to follow suggestions from both humans or AI. Neuroticism negatively predicted trust ratings. Openness predicted reaction time, but only for suggestions from previous participants. However, people chose the AI suggestions more than those from humans, and self-reported that they believed such recommendations more. Conclusions The results indicate that LOC accounts for a significant variance for trust concordance and trust ratings, predicting beyond BFI traits, and affects the way people select whom they trust whether humans or AI. These findings also support the AI-based algorithm appreciation.

show abstract

Section: Introductionmentioning

confidence: 99%

The effects of personality and locus of control on trust in humans versus artificial intelligence

Sharan

Romano

2020

Heliyon

View full text Add to dashboard Cite

show abstract

“…e shortest distance path of any OD is fixed in the road network, but the shortest time path varies with the change in a traffic state. Most existing research uses simulation, weighted solution of historical average speed, or the sum of historical travel time to obtain the shortest time path, [3] Traffic survey of 188 respondents (1997)# Simulation 28% 45 Turin [4] 276 observations of Turin Polytechnic faculty Simulation 30.93% 18.22 Lexington [2] 216 drivers over a week, more than 3000 trips Null * Minneapolis-St. Paul [6] 143 subjects, 25157 trips (2008) Null @ 34 Minneapolis-St. Paul [5] 50 persons, 124 commute trips (2011) 12.26% 24.19 Enschede [8] 317 respondents, 624 trips 54% 41 A European country [9] 526 users over 18 months 47% e Philippines and Japan [7] 17 driver participants Null 21.6…”

Section: Shortest Path Data Extraction From Navigationmentioning

confidence: 99%

“…Even in some cases, no residents use the shortest distance path unless the shortest distance path is consistent with the fastest time path [6]. Most drivers tend to choose the familiar travel path and only choose the most straightforward path recommended by the guidance system in an emergent condition [7]. e proportion of fastest path selection in existing studies worldwide is shown in Table 1.…”

Section: Introductionmentioning

confidence: 99%

Understanding the Shortest Route Selection Behavior for Private Cars Using Trajectory Data and Navigation Information

Wang

Ding

Cheng

2022

Journal of Advanced Transportation

View full text Add to dashboard Cite

Traffic information and driving preference play critical roles in the route selection of drivers and further impact transport management in practice. Some studies have explored the difference between actual and shortest paths for private cars during route selection. However, the quantification of the difference and deviation as well as the impacts of the date on route selection is still seldom investigated. The study proposed a method to quantify the deviation between actual and shortest paths based on big trajectory data and the digital map. Firstly, the rules of private car travel are determined according to the definition of a trip, and the travel trajectory is divided based on these rules to attain many trips. Then, the trip routes and their attributes are generated by geographical information methods. Baidu Map’s path planning collects the shortest routes with the optimal distance and time, and the deviation between actual and recommended paths is compared. Finally, the results of 2860 private car trips of nearly 400 drivers in Chongqing, China, reveal that only about 67% of the actual trips match well with the shortest path, which was significantly higher compared to existing studies. However, the deviation between the actual and shortest paths is limited to 9 minutes or 2 kilometers. There was no significant difference between the weekday and weekend in the proportion. Compared with the weekday, the indicators of the weekend are more deviated. Path selection and the deviation vary in travel modes, OD types, drivers’ preferences, travel time intervals, and distance intervals.

show abstract

“…Commuters tend to rely totally on information provided by navigation systems only for completely unknown destinations. However, in most cases, they tend to choose routes with which they are already familiar ( 5 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Evidence from Highway Drivers in Greece Showing Toll Avoidance and Utility of Alternative Routes

Politis

Kyriakoglou

Georgiadis

et al. 2020

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

Road tolling plays a significant role on highways’ financial sustainability since it consists the major revenue source. This paper aims to examine the factors that affect the drivers’ route choice and urge them to avoid toll roads when an alternative toll-free route is available. The paper presents the results of a case study that is dealing with the issue of toll avoidance at the last non-privatized highway of Greece, the Egnatia Odos (EO) road. Data from a combined revealed and stated preference survey were collected and binary choice models were built for car and truck drivers so as to determine the utility of alternative routes. The results show that travel cost and toll fees are critical route choice criteria for car drivers, while travel time is a key decision factor for truck drivers. The high safety standards for the toll route were appreciated by both categories of drivers. Additional trip and personal characteristics, such as gender, trip frequency, type of transported cargo, and total trip length also affect drivers’ choices. The elasticity of travel time and cost was estimated to shed light on drivers’ sensitiveness to the route attributes and it was found that truck drivers’ choices are greatly influenced by their working time schedules. These findings highlight the key factors that influence the utility of toll roads and therefore could assist highway authorities and concessionaires in developing successful toll pricing policies which will not act as a deterrent to the use of highways.

show abstract

Exploring Factors that Influence Connected Drivers to (Not) Use or Follow Recommended Optimal Routes

Cited by 16 publications

References 30 publications

The effects of personality and locus of control on trust in humans versus artificial intelligence

The effects of personality and locus of control on trust in humans versus artificial intelligence

Understanding the Shortest Route Selection Behavior for Private Cars Using Trajectory Data and Navigation Information

Evidence from Highway Drivers in Greece Showing Toll Avoidance and Utility of Alternative Routes

Contact Info

Product

Resources

About