Driver Navigation Research Articles

Evaluating the Effects of Motion Cues in Virtual Truck Driver Training

The integration of simulation technology into professional training has transformed learning in various sectors. Although prior research has explored motion cueing in simulators such as aviation training, driver navigation and performance, there is limited investigation into the impact of motion stimuli in VR-based truck driver training. This study investigates the driving performance of truck drivers in two virtual driving tasks, comparing conditions with and without motion cues. Participants wore virtual reality headsets and were situated within an immersive motion simulator. They completed two driving tasks involving truck docking and highway driving. Simulator sickness, stress, and user experience were assessed using the simulator sickness questionnaire, subjective unit of distress scale, and user experience questionnaire, respectively. Our findings suggest that motion cues hold potential to enhance subjective experiences, making driving more engaging, stimulating, and mitigating motion sickness. However, they did not significantly affect overall driving performance, except for steering behavior. Participants exhibited more engaged steering during highway driving when motion cues were present. Our findings suggest that the impact of motion cues is task-dependent, with their absence not showing a significant detrimental effect on driving performance in the simulated environment. Further validation with field-observed data is necessary to confirm these findings. These insights can guide future policies and regulations governing virtual truck driver training, ultimately ensuring improved safety and performance in the industry.

Detection of Highway Lane using Color Filtering and Line Determination

Traffic accidents are generally caused by human error as a driver. The main cause is that the vehicle shifts away from the driving lane without the driver realizing it. Usually, because the driver is sleepy or drunk. Therefore, it is necessary to have a system that functions to assist the driver's navigation to stay on the correct driving path, such as a driver assistance system (DAS). In this system, the driving lane detector is the main part. This system serves to assist the driver's navigation to stay on the correct driving path. Vehicles are installed with cameras to record video towards the road ahead. Computers are also installed for image processing, identifying left and right road lines, and forming ego-lane. This paper offers an image processing-based method for recognizing driving lanes and presenting visualizations in real-time. This method has been tested using a data set, that video driving on Indonesian highway on the Cipali and Palikanci sections using dashboard camera. The test results obtained an accuracy of 99.25%.

Do Digital Platforms Reduce Moral Hazard? The Case of Uber and Taxis

Digital platforms provide a variety of technology-enabled tools that enhance market transparency, such as real-time monitoring, ratings of buyers and sellers, and low-cost complaint channels. How do these innovations affect moral hazard and service quality? We investigate this problem by comparing driver routing choices and efficiency on a large digital platform, Uber, with traditional taxis. The identification is enabled by matching taxi and Uber trips at the origin-destination-time level so they are subject to the same underlying optimal route, by exploiting characteristics of the pricing schemes that differentially affect the incentives of taxi and Uber drivers in various circumstances, and by examining changes in behavior when drivers switch from taxis to Uber. We find that (1) taxi drivers route longer in distance than matched Uber drivers on metered airport routes by an average of 8%, with nonlocal passengers on airport routes experiencing even longer routing; (2) no such long routing is found for short trips in dense markets (e.g., within-Manhattan trips) or airport trips with a flat fare; and (3) long routing in general leads to longer travel time, instead of saving passengers time. These findings are consistent with digital platform designs reducing driver moral hazard, but not with competing explanations such as driver selection or differences in driver navigation technologies. We also find evidence of Uber drivers’ long routing on airport trips in times of surge pricing, suggesting that the tech-enabled market designs may not be binding in our setting. This paper was accepted by Chris Forman, information systems.

A 4G-Connected Micro-Rover With Infinite Range

The development of micro-rover technology could enable multiple applications. However, the range of control so far has been limited to the radio system used. If cellular (4G/5G) connectivity could be used, its control range would be practically infinite. This work describes the design of such a system. The micro-rover is controlled by an onboard GPS linked STM32 32-bit ARM-based microcontroller, which communicates with an onboard Linux computer. The control is over a 4G/LTE network, which can provide full manual (throttle and steering) or full autonomous (GPS waypoint controlled) navigation. A live HD video stream is used for driver awareness and navigation. With this approach, in this work, we demonstrate a 4G-connected micro-rover with semi-autonomous driving capability and a prototype command and control architecture with encryption that can punch through firewalls at the driver and rover end. At 0.3 m in length and 900-g weight, this is the smallest 4G-connected autonomous micro-rover ever demonstrated. Because of the 4G connectivity, its control range is practically infinite.

SPATIAL AND TEMPORAL COMMUNITY DETECTION OF CAR MOBILITY NETWORK IN METRO MANILA

Abstract. Transportation Network Companies (TNCs) like Uber utilize GPS and wireless connection for passenger pickup, driver navigation, and passenger drop off. Location-based information from Uber in aggregated form has been made publicly available. They capture instantaneous traffic situation of an area, which makes describing spatiotemporal traffic characteristics of the area possible. Such information is valuable, especially in highly urbanized areas like Manila that experience heavy traffic. In this research, a methodology for identifying the underlying city structure and traffic patterns in Metro Manila was developed from the Uber trip information. The trip information was modelled as a complex network and Infomap community detection was utilized to group areas with ease of access. From Uber trip dataset, the data was segregated into different hours-of-day and for each hour-of-day, a directed-weighted temporal network was generated. Hours-of-day with similar traffic characteristics were also grouped together to form hour groups. From the results of the network characterization, hours-of-day were grouped into six hour groups; 00 to 04 hours-of-day in hour group 1, 05 to 07 hours-of-day in group 2, 08 to 12 hours-of-day in group 3, 13 to 15 in group 4, 16 to 19 in group 5, and 20 to 23 in group 6. Major roads as well as river networks were observed to be the major skeleton and boundaries of the generated clusters.

Deep learning Convolutional Neural Network for Unconstrained License Plate Recognition

The evolve of neural networks algorithm into deep learning convolutional neural networks seems like the next generation for object detection. This algorithm works has a significantly better accuracy and did not tied to any particular aspect ratio. License plate and traffic signs detection and recognition have a number of different applications relevant for transportation systems, such as traffic monitoring, detection of stolen vehicles, driver navigation support or any statistical research. An exponential increase in number of vehicles necessitates the use of automated systems to maintain vehicle information. The information is highly required for both management of traffic as well as reduction of crime. Number plate recognition is an effective way for automatic vehicle identification. A number of methods have been proposed, but only for particular cases and working under constraints (e.g. known text direction or high resolution). Deep learning convolutional neural networks work well especially in handles occlusion/rotation better, therefore we believe this approach is able to provide a better solution to the unconstrained license plate recognition problem.

Do Digital Platforms Reduce Moral Hazard? The Case of Uber and Taxis

Digital platforms provide a variety of technology-enabled tools that enhance market transparency, such as real-time monitoring, ratings of buyers and sellers, and low-cost complaint channels. How do these innovations affect moral hazard and service quality? We investigate this problem by comparing driver routing choices and efficiency on a large digital platform, Uber, with traditional taxis. The identification is enabled by matching taxi and Uber trips at the origin-destination-time level so they are subject to the same underlying optimal route, by exploiting characteristics of the pricing schemes that differentially affect the incentives of taxi and Uber drivers in various circumstances, and by examining changes in behavior when drivers switch from taxis to Uber. We find that (1) taxi drivers route longer in distance than matched Uber drivers on metered airport routes by an average of 8%, with non-local passengers on airport routes experiencing even longer routing; (2) no such long routing is found for short trips in dense markets (e.g., within-Manhattan trips) or airport trips with a flat fare; and (3) long routing in general leads to longer travel time, instead of saving passengers time. These findings are consistent with digital platform designs reducing driver moral hazard, but not with competing explanations such as driver selection or differences in driver navigation technologies. We also find evidence of Uber drivers' long routing on airport trips in times of surge pricing, suggesting that the tech-enabled market designs may not be binding in our setting.

Comparison of Driver Navigation at Turbo Roundabouts and Modern Two-Lane Roundabouts: Simulation Study

Roundabouts can be a solution to safety concerns common to conventional intersections. Recently in the United States, there has been an increase in the conversion of problematic intersections to roundabouts to improve their safety. However, there are some important considerations and challenges to make roundabouts safe for all users, especially multilane roundabouts. There may also be challenges for drivers to navigate a newly built or a new type of roundabout. Roundabout features such as pavement markings and signage play an important role in driver navigational performance. This research was an effort to evaluate new roundabout design and existing roundabout safety and operational features such as signs and pavement markings. The focus was on how such features influenced the performance of drivers, specifically at multilane roundabouts. Two-lane roundabouts and rotor turbo roundabouts were evaluated. A driving simulator was employed to test various simulation scenarios in a virtual world. The results indicate that lane keeping and higher navigation speeds are still problems at multilane roundabouts. The rotor turbo roundabout outperforms the two-lane roundabout in enabling correct lane choice and navigation speed control by drivers. Furthermore, it was found that roundabout signs and pavement markings used in the United States can be adopted for turbo roundabouts.

Effects of spacing between items and view direction on errors in the perceived height of a rotated 3-D figure.

This study investigated the errors in the perceived height of virtual cones presented on the screen. 80 students (50 women, 30 men; M age = 18.8 yr., SD = 1.2 using a duodecimal system) participated in the study. They judged the height of virtual cones in several conditions: (a) different spaces between the items in the array (2, 4, and 6 cm); (b) different viewing directions - bottom-up or top-down; (c) cones presented in different forward-rotated angles (15, 30, and 45°). Results indicate that fewer errors in the perceived heights of virtual cones were made when: the space between items was 2 cm, judgment was made in a bottom-up view and at a 15° angle. These results may have implications for graphics-based interface design such as interior design, driver navigation systems, geological models, and flight-simulation systems.

Circle Fitting Based Pile Positioning and Machine Pose Estimation from Range Data for Pile Driver Navigation

Abstract In this research, we propose a pile driver navigation system for accurate and efficient pile driving in construction fields. In the system, a laser range finder is placed in the field and measures the position of a driving pile and pose of a pile driver. The measured pile position and the desired pile position are transformed to the pile driver coordinate system and provided to the operator of the driver to allow easy adjustment of the pile position. This paper focuses on pile position estimation and pile driver pose estimation from laser range finder data. We compare two pile position estimation methods based on circle fitting. One is maximum likelihood estimation under Gaussian noise in Cartesian coordinates whereas in another method Gaussian noise is added in polar coordinates. The pile driver pose estimation method uses markers attached to the machine and the pose is calculated from the measured marker positions in global coordinate system and the corresponding marker positions in the pile driver coordinate system.

Effects of e-map format and sub-windows on driving performance and glance behavior when using an in-vehicle navigation system

An on-road driving experiment was conducted to investigate the effects of e-map format and sub-windows on driving performance and glance behavior of navigation system users. Twenty-eight participants navigated an urban route using the navigation display with 2D or 3D e-maps and either with or without sub-windows. Driver navigation errors and visual glance data were gathered during the trials. The analytical results demonstrate no significant difference in driving performance between the 2D and 3D e-map conditions. However, use of a 3D e-map was associated with significantly more frequent glance behavior than the 2D display. Furthermore, subjects using the navigation display with a sub-window made significantly fewer navigation errors (50% less) compared to those using the navigation display without a sub-window. This investigation suggests that performance improves when using sub-windows. Finally, this study discusses wider implications in the design and use of navigation displays. Relevance to industry We found that the e-map format is related to driver glance behavior when using an in-vehicle navigation display. The sub-window also provides substantial influence on driving performance and glance behavior. The results of our study will assist in designing in-vehicle navigation systems and improving the performance of navigation e-maps for path-finding tasks.

경로유도정보와 방향지시등을 연동한 추가정보 제공 시스템 개발의 기초 연구

A car navigation system as an in-vehicle route guidance information (RGI) offers a state-of-the-art technological solution to driver navigation in an unfamiliar area. However, the RGI is provided by some pre-determined options in terms of the interface between a driver and a car navigation system. Drivers occasionally pass the target intersection owing to non- or late- recognizing it. This paper is examined the position of driver's turn signal operation and intersection recognition approaching at the target intersection which is difficult to identify, as a fundamental research on developing the additional RGI connecting with the turn signal control. The field experiment was conducted to measure distances of the turn signal operation and the intersection recognition from the target intersection according to left turns, right turns, and landmarks at adjacent intersection. And glance behavior to the car navigation display was evaluated by using an eye camera. The results of the field study indicate that, most case of driving, drivers operate the turn signal until 40m to 50m before coming to the target intersection. The driving simulator experiment was performed to examine the effectiveness of providing the additional RGI when drivers did not operate the turn signal approaching at the target intersection based on the results of the field study. To provide the additional RGI is effective for the intersection identification and recognition, and expected to improve the traffic safety and the comfort for drivers.

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

The objective of this study was to investigate the impact of landmark information of varying quality within drivers' navigation instructions on driving and navigation performance when navigating an unfamiliar route. Current vehicle navigation systems predominantly use distance-to-turn information to enable a driver to locate a forthcoming maneuver. Although it has been proposed that the design of driver navigation aids can be improved through the incorporation of landmarks as key navigation cues, little research has investigated how the quality of the landmark affects driver behavior. An empirical field trial in a real traffic environment was undertaken with 48 participants in order to assess the effect of landmark quality on driver behavior 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. Good landmarks offer significant safety and performance benefits to a driver navigating an unfamiliar route. Poor landmarks can result in driver performance worse than that obtained using distance to turn to locate forthcoming maneuvers. The design of future vehicle navigation systems should not rely on distance-to turn information alone to enable a driver to locate forthcoming maneuvers but, rather, should incorporate good landmarks within the navigation instructions they present to drivers.

2404 先進デマンドバスシステムの開発と実証(OS2-1 高速化・利便性,OS2 交通・物流システムの高速化,利便性,快適性の向上,TRANSLOG 2006)

An advanced on-demand bus system has been developed for regional public transportation using the advanced electric buses (WEB) as a part of NEDO's project. The on-demand system utilizes advanced ITS and associated technologies. It consists of three subsystems of a driver navigation system responding to demands by operations on mobile phones, a traffic running simulator for best routing and an estimation system for number of passengers. On-road proving tests were carried out using WEB in Honjo city, Saitama prefecture, and the reliability and the convenience for passengers' mobility have been clarified.

Incorporating Landmarks in Driver Navigation System Design: An Overview of Results from the REGIONAL Project

This paper presents an overview of results from the two year REGIONAL project. The aims of REGIONAL were to undertake research to enable landmarks to be an integral feature of future vehicle navigation systems. Results from the project, including five empirical road-based trials, are summarised. The main findings were: landmarks were widely used by drivers as key navigation cues; the incorporation of good landmarks within navigation instructions has the potential to considerably enhance vehicle navigation systems; although a wide range of landmarks are potentially useful to a driver, only a limited set, which displayed key characteristics, were consistently effective as navigation cues.

Driver Performance Results from the Travtek IVHS Camera Car Evaluation Study

The TravTek system constitutes a major Intelligent Vehicle-Highway System (IVHS) Advanced Traveler Information System (ATIS) demonstration project. The system provided in-vehicle information via color touchscreen CRT, steering wheel buttons, and synthesized voice. The TravTek driver interface was developed with the intent of providing navigation, service and attractions, and roadway incident and traffic information to the driver. The design of the TravTek interface had as its primary objectives: (1) more effective driver navigation providing the benefit of saving time, (2) easy access to valuable and convenient location information to alleviate stress and increase driving enjoyment, (3) maintenance of safe driving performance during system use and safety improvement facilitated by information for avoiding hazards and for emergency response, and (4) improvement of roadway efficiency to alleviate congestion. This paper provides detailed data regarding driver performance and behavioral interactions with four TravTek navigation configurations and two conventional methods of navigation: a paper map and a textual direction list. The results indicate that turn-by-turn information, regardless of its method of presentation, results in effective driving and navigation performance. A moving map display with no supplemental information required high visual attention relative to the other conditions. The other TravTek conditions resulted in lower workload superior navigation performance than the paper map control condition.