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Three-wheeler performance optimization: Dynamics-based design of a first prototype
Published in Maksym Spiryagin, Timothy Gordon, Colin Cole, Tim McSweeney, The Dynamics of Vehicles on Roads and Tracks, 2018
As mentioned above, the vehicle developed in this work is a tilting three-wheeler. The selected morphology is the reverse trike type: Two wheels are mounted on the front suspension. The rear wheel is motorized and uses, in the manner of a motorbike, a swing-arm suspension. The front suspension is the most challenging part of the vehicle. It must satisfy severe dimensional constraints, especially a low width of 0.8m. Due to this low width, the vehicle stability requirement imposes to tilt the vehicle when it turns. Directly linked to the maximal lateral acceleration, the maximal tilting angle must be chosen as large as possible. Added to the suspension own motion, it leads to extremely large wheel travel and to bothersome geometrical interactions between different parts.
Level of service of urban roads based on user perception
Published in Sheela Evangeline, M.R. Rajkumar, Saritha G. Parambath, Recent Advances in Materials, Mechanics and Management, 2019
In IRC LOS categorization, mean free flow speed of vehicles were considered. But the free flow speeds of different vehicle categories were found to be different. Hence the use of mean free flow speed in assessing LOS is not suitable in heterogeneous traffic conditions. Free flow speeds of different vehicle categories (small car, big car, two wheeler, three wheeler, LCV, Bus and Lorry) were determined from the recorded videos. Percent Speed Reduction (PSR) from their FFS were calculated for every individual vehicle. PSR obtained from the selected roads were clustered into six groups by K-means clustering. Each of these groups represent one service level. Fig. 3 shows the K means clustering of PSR values obtained.
Frugal Engineering and Innovation
Published in John C. Camillus, Bopaya Bidanda, N. Chandra Mohan, The Business of Humanity, 2017
John C. Camillus, Bopaya Bidanda, N. Chandra Mohan
The competition to the Nano typically went about stripping a car down to its essentials to see if it could then be assembled at the lowest price point. Or even adding a fourth wheel to a three-wheeler! Japan’s Suzuki Motor Corporation, the leader in India’s car market, which till then produced the cheapest car, the Maruti 800, openly scoffed at Tata’s efforts, stating that there could be nothing cheaper than what it was already manufacturing. In the event, they were proved totally wrong. The Nano was far from a stripped-down version of any other small car in the world. Simply put, it was a breakthrough in frugal engineering and design.
Factors contributing to motorcycle fatal crashes on National Highways in India
Published in International Journal of Injury Control and Safety Promotion, 2018
Hasan Mehdi Naqvi, Geetam Tiwari
Tables 2–4 present percentage distribution of victims’ mode by striking (impacting) vehicle in fatal crash on each of the NHs: two-lane NH-8, four-lane NH-24 and six-lane NH-1, respectively. Up to three modes in a fatal crash are considered in this study (for example, modes involved in a fatal crash: case (1) a pedestrian, a cycle-rickshaw and a car; case (2) two cars and a truck; case (iii) a motorcycle and a pedestrian). Each horizontal row (figures in parenthesis) in Tables 2–4 depicts share (%) of striking vehicles against the respective victims’ vehicle. Figures in parenthesis of the last row: ‘Total’ show share (%) of striking vehicles. Each vertical column in Tables 2–4 depicts share (%) of victims’ vehicles against the respective striking vehicle. Figures in the last column: ‘Total’ show percentage share of victims’ vehicles involved in fatal crashes. In Tables 2–4, three-wheeler vehicle represents passenger auto-rickshaw/tempo. ‘Other vehicle’ in the cited Tables includes non-motorized vehicle. Single-vehicle crashes occur owing to vehicle hit by tree/pole/fixed object, roll over and so on.
Factors explaining pedestrian-involved fatality crashes on National Highways in India
Published in International Journal of Injury Control and Safety Promotion, 2022
Hasan Mehdi Naqvi, Geetam Tiwari
Table 4 presents the percentage distribution of pedestrian victims by striking vehicles in fatal crashes on each NH. Each horizontal row in Table 4 depicts the share in % of striking vehicles against fatal pedestrian victims. Here, truck represents light goods vehicles, truck/tanker, i.e., two-axle or more, and container truck-trailer. Three-wheeler auto-rickshaw represents passenger auto-rickshaw and tempo. Car represents car, jeep and SUV. Motorcycle represents two-wheeled motor vehicle, namely moped, scooty and motorcycle. ‘Unknown’ striking vehicle represents vehicle for which information related to ‘vehicle type’ are not available in fatal crash records.
Investigating dilemma zone boundaries for mixed traffic conditions using support vector machines
Published in Transportation Letters, 2022
Bharat Kumar Pathivada, Perumal Vedagiri
Study results indicate that the location of the dilemma zone varies with the type of vehicle. It is logical, as the vehicles vary in their physical and dynamic characteristics, which influences their manoeuvrability. 3-legged approaches were found to have larger dilemma zone compared to the 4-legged approaches, indicating drivers willing to take higher risk to cross at the 3-legged intersections. Dilemma zone for the truck and motorized three-wheeler was found to be closer to the stop line compared to other vehicle types. Passenger car and motorized two-wheeler had dilemma zone away from the stop line, indicating their aggressive and risk-taking behavior. Based on the study results, dilemma zone for mixed traffic conditions tends to be between 30 m to 80 m from the stop line. The accurate position of dilemma zone boundaries can help in developing various passive and active dilemma protection systems (such as additional road markings, road signs, advance warning systems etc.) to assist the drivers in their decision (stop/go) process and reducing the safety complications. Results from this study contribute to better understand the dilemma boundaries in developing countries with mixed traffic conditions, like India. Although results obtained from this study are only applicable to mixed traffic conditions, the defined methodology can be applied for a different dataset to obtain the desired results. Also, this study did not consider the effect of driver attributes such as age and gender, on the location of dilemma zone, as these details could not be extracted from the video data. Further research can be carried out to study the influence of turning movements on the driver behavior and the effect of driver attributes on the location of dilemma zone. Also, further studies are required to evaluate the dilemma boundaries using different percentile speeds and validate the dilemma zone boundaries.