Car navigation – computing routes that avoid complicated crossings

Krisp, Jukka M.; Keler, Andreas

doi:10.1080/13658816.2015.1053485

Cited by 27 publications

(33 citation statements)

References 31 publications

(20 reference statements)

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“…In our approach, we used only a derivation of the original OSM road network, which is represented by polylines. Similar to Krisp and Keler (2015), we propose the abstraction of high node density for complicated crossings. The idea is to compare the frequency of taxi visits in crossings and in other road segments with its defined complexity.…”

Section: Traffic Analysis Based On Taxi Tipmentioning

confidence: 99%

Detecting vehicle traffic patterns in urban environments using taxi trajectory intersection points

Keler

Krisp

Ding

2017

Geo-spatial Information Science

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Detecting and describing movement of vehicles in established transportation infrastructures is an important task. It helps to predict periodical traffic patterns for optimizing traffic regulations and extending the functions of established transportation infrastructures. The detection of traffic patterns consists not only of analyses of arrangement patterns of multiple vehicle trajectories, but also of the inspection of the embedded geographical context. In this paper, we introduce a method for intersecting vehicle trajectories and extracting their intersection points for selected rush hours in urban environments. Those vehicle trajectory intersection points (TIP) are frequently visited locations within urban road networks and are subsequently formed into density-connected clusters, which are then represented as polygons. For representing temporal variations of the created polygons, we enrich these with vehicle trajectories of other times of the day and additional road network information. In a case study, we test our approach on massive taxi Floating Car Data (FCD) from Shanghai and road network data from the OpenStreetMap (OSM) project. The first test results show strong correlations with periodical traffic events in Shanghai. Based on these results, we reason out the usefulness of polygons representing frequently visited locations for analyses in urban planning and traffic engineering.

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Section: Traffic Analysis Based On Taxi Tipmentioning

confidence: 99%

Detecting vehicle traffic patterns in urban environments using taxi trajectory intersection points

Keler

Krisp

Ding

2017

Geo-spatial Information Science

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“…Researchers put much effort to learn the needs from different drivers and try to provide them personalized navigation and way-finding solutions. For example, Krisp and Keler (2015) try to provide routes with less complicated crossings for inexperienced drivers. Jiang et al (2008) also argue that crossings and turning angles may be important in road network organization and human path selection behaviour.…”

Section: Betweenness Centrality and Traffic Patterns In Neighbouring mentioning

confidence: 99%

The Impact of Large Urban Structural Elements on Traffic Flow a Case Study of Danwei and Xiaoqu in Shanghai

Lyu

Ding

Fan

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Danwei (working unit) and Xiaoqu (residential community) are two typical and unique structural urban elements in China. The interior roads of Danwei and Xiaoqu are usually not accessible for the public. Recently, there is a call for opening these interior roads to the public to improve road network structure and optimize traffic flow. In this paper we investigate the impact of Danwei and Xiaoqu on their neighbouring traffic quantitatively. By taking into consideration of origins and destinations (ODs) distributions and route selection behaviours (e.g., shortest paths), we propose an extended betweenness centrality to investigate the traffic flow in two scenarios 1) the interior roads of Danwei and Xiaoqu are excluded from urban road network, 2) the interior roads are integrated into road network. A Danwei and a Xiaoqu in Shanghai are used as the study area. The preliminary results show the feasibility of our extended betweenness centrality in investigating the traffic flow patterns and reveal the quantitative changes of the traffic flow after opening interior roads.

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“…In general routing algorithms offer a number of different parameters that may provide users with different type of routes, including the shortest, fastest, safest, most beautiful, least fuel/energy consumption (Ranacher et al 2016), male/female (Häusler et al 2010), easiest (Duckham and Kulik 2003) or most difficult (to drive) route (Krisp, Keler, and Karrais 2014). As Krisp & Keler (2015) suggest, that may also include the 'most difficult to drive route', which might be useful for driver training purposes. Previous research (Krisp and Keler 2015) has investigated what is an "easy to drive" route?…”

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confidence: 99%

“…As Krisp & Keler (2015) suggest, that may also include the 'most difficult to drive route', which might be useful for driver training purposes. Previous research (Krisp and Keler 2015) has investigated what is an "easy to drive" route? and "what are the traffic situations that could be avoided for inexperienced drivers and/or driving beginners?".…”

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confidence: 99%

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Classifying complex road features in the context of car driver education

Krisp

Keler

2019

Abstr. Int. Cartogr. Assoc.

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Learning to drive a car is not easy. Therefore, in many countries, driving schools offer an education of how to drive a car. This is taught on a theoretical and practical level. Once a driving student has learned how to handle a car in real traffic, he / she will take a driving test exam. In Germany, for example, an authorized driving examiner telling the students to follow their instructions conducts the practical exam. Thereby the driving examiner guides the student to different situation (for example taking a highway, crossing a complicated intersection, backward parking etc.). The examiner selects the route according to the criteria set out in the test guidelines and incorporates the road and traffic conditions in his choice. The driver test guidelines include basic driving tasks (parking, danger braking, etc.), a route within closed villages, a route outside built-up areas and / or motorway sections and afterwards a feedback on student performance. The test is set for a period of 45 minutes (for driving class B). Currently mobile devices, which are able to record a number of parameters (location, speed etc.) are rarely used in these driving examinations. Additionally, the route the driving instructor follows can be somewhat arbitrary. Utilizing routing systems in these driving examinations may assist the driving examiner and may help to make the examination more transparent.

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Car navigation – computing routes that avoid complicated crossings

Cited by 27 publications

References 31 publications

Detecting vehicle traffic patterns in urban environments using taxi trajectory intersection points

Detecting vehicle traffic patterns in urban environments using taxi trajectory intersection points

The Impact of Large Urban Structural Elements on Traffic Flow a Case Study of Danwei and Xiaoqu in Shanghai

Classifying complex road features in the context of car driver education

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