Drivers' Information Requirements when Navigating in an Urban Environment

May, Andrew; Ross, Tracy; Bayer, Steven H.

doi:10.1017/s0373463302002114

Cited by 32 publications

(23 citation statements)

References 11 publications

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“…It has been shown in [23] that drivers are prepared to take suboptimal routes in terms of travel time, if these routes are potentially easier to describe and to follow. Additionally, it is confirmed that successful vehicle navigation systems rely as much on clarity of route instructions as on the length of routes [19].…”

Section: Introductionmentioning

confidence: 81%

Algorithms for Reliable Navigation and Wayfinding

Haque

Kulik

Klippel

2007

Spatial Cognition v Reasoning, Action, Interaction

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Abstract. Wayfinding research has inspired several algorithms that compute the shortest, fastest, or even simplest paths between two locations. Current navigation systems, however, do not take into account the navigational complexity of certain intersections. A short route might involve a number of intersections that are difficult to navigate, because they offer more than one alternative to turn left or right. The navigational complexity of such an intersection may require modified instructions such as veer right. This paper, therefore, presents a reliable path algorithm that minimizes the number of complex intersections with turn ambiguities between two locations along a route. Our algorithm computes the (shortest) most reliable path, i.e., the one with the least turn ambiguities. Furthermore, we develop a variation of this algorithm that balances travel distance and navigational complexity. Simulation results show that traversing a reliable path leads to less navigational errors, which in turn reduces the average travel distance. A further advantage is that reliable paths require simpler instructions.

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Section: Introductionmentioning

confidence: 81%

Algorithms for Reliable Navigation and Wayfinding

Haque

Kulik

Klippel

2007

Spatial Cognition v Reasoning, Action, Interaction

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“…They have been shown empirically to be widely used within drivers' wayfinding strategies (Alm, 1990;May, Ross, & Bayer, 2003), and valued by drivers as information cues (Burns, 1997;Streeter, 1986;Wochinger & Boehm-Davis, 1997). …”

Section: The Practical Benefits Of Landmarks For Driver Navigationmentioning

confidence: 99%

Presence and Quality of Navigational Landmarks: Effect on Driver Performance and Implications for Design

May

Ross

2006

Hum Factors

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Abstract:Current vehicle navigation systems still predominantly use distance-to-turn information to enable a driver to locate a forthcoming manoeuvre. It has been proposed that the design of driver navigation aids can be improved through the incorporation of landmarks as key navigation cues. However, little research has investigated how the quality of the landmark affects driver behaviour. An empirical field trial in a real traffic environment was undertaken with 48 participants (minimum age 21, mean 44; minimum driving experience three years; mean km driven in the last year 19,000) in order to assess the effect that the quality of a landmark had on driver behaviour when navigating an unfamiliar, complex, urban route. The use of good landmarks (as opposed to poor landmarks or distance information) as key verbal navigation cues resulted in significant improvements in navigation performance, driving performance, and driver confidence immediately preceding a turn. The use of distance information to locate a turn resulted in significantly more glances to the in-vehicle display.Actual or potential applications of this research include guiding the design of effective and safe future vehicle navigation systems.

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“…Research by Richter and Klippel [7], into optimal locations for "You-are-here" maps, emphasizes the importance of the overall number of decision points and the number of branches at an intersection as route selection criteria, in addition to the length of a route. Research from the vehicle navigation literature has also confirmed that successful vehicle navigation systems rely as much on clarity of route instructions as length of route [8,9]. Shortest path algorithms only minimize route efficiency, in terms of distance or travel cost, and not route description complexity.…”

Section: Introductionmentioning

confidence: 98%

“…Without yet defining precisely what is meant by "simplest," intuitively only two of these six routes seem to be optimal simplest routes. Only (i 1 , i 2 , i 3 , i 6 , i 9 ) and (i 1 , i 4 , i 7 , i 8 , i 9 ) avoid the more complex 4-way intersection i 5 , and only these two routes require just one "turn." We might describe the route (i 1 , i 2 , i 3 , i 6 , i 9 ) with the instruction sequence "orient yourself, go straight ahead, and turn right at the end of the road."…”

Section: Introductionmentioning

confidence: 99%

“…We might describe the route (i 1 , i 2 , i 3 , i 6 , i 9 ) with the instruction sequence "orient yourself, go straight ahead, and turn right at the end of the road." In contrast, the route (i 1 , i 2 , i 5 , i 8 , i 9 ) might require a longer instruction sequence to describe, such as "orient yourself, go straight ahead, turn right at the first intersection, then turn left at the second intersection. "…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

“Simplest” Paths: Automated Route Selection for Navigation

Duckham

Kulik

2003

Spatial Information Theory. Foundations of Geographic Information Science

160

155

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Abstract. Numerous cognitive studies have indicated that the form and complexity of route instructions may be as important to human navigators as the overall length of route. Most automated navigation systems rely on computing the solution to the shortest path problem, and not the problem of finding the "simplest" path. This paper addresses the issue of finding the "simplest" paths through a network, in terms of the instruction complexity. We propose a "simplest" paths algorithm that has quadratic computation time for a planar graph. An empirical study of the algorithm's performance, based on an established cognitive model of navigation instruction complexity, revealed that the length of a simplest path was on average only 16% longer than the length of the corresponding shortest path. In return for marginally longer routes, the simplest path algorithm seems to offer considerable advantages over shortest paths in terms of their ease of description and execution. The conclusions indicate several areas for future research: in particular cognitive studies are needed to verify these initial computational results. Potentially, the simplest paths algorithm could be used to replace shortest paths algorithms in any automated system for generating human navigation instructions, including in-car navigation systems, Internet driving direction servers, and other location-based services.

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Drivers' Information Requirements when Navigating in an Urban Environment

Cited by 32 publications

References 11 publications

Algorithms for Reliable Navigation and Wayfinding

Algorithms for Reliable Navigation and Wayfinding

Presence and Quality of Navigational Landmarks: Effect on Driver Performance and Implications for Design

“Simplest” Paths: Automated Route Selection for Navigation

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