Analyzing the impact of bicycle geometry and cargo loading on the rideability and safety of cargo bikes: An investigative study

Introduction

Electric cargo bikes have become popular for transporting goods and people due to their small size and strong carrying capacity. However, the way they perform, handle, and operate safely can be affected by the weight of the cargo, where it is placed on the bike, and the bike's design.

Method

This paper analyzes the rideability and safety of eight different cargo bikes representing three different design categories, Retrofitted, Long-john, and Long-tail bikes, also considering three different cargo loading locations. We quantitatively examined the rideability by computing the minimum speed for self-stability, the maximum possible acceleration and deceleration without losing wheel-ground contact, the handlebar torque for steady-state turning, and the force required to overcome obstacles. The effect of using powerful motorized wheels has also been discussed.

Results

Long-john cargo bikes are unstable for lightweight cargo loads, more sensitive to cargo loads, and therefore may not be suitable for riding in narrow, crowded spaces like footpaths. Moreover, retrofitted cargo bikes should only be used to carry lightweight cargo as a combination of heavy cargo load and a powerful rear wheel motor poses a potential risk of accidents. Long-tail cargo bikes are less affected by changes to the cargo load and are thus safer than retrofitted bikes. Their relatively compact length also makes for a smaller turning radius.

Conclusion

Rideability and safe handling of the cargo bikes strongly depend on the bike design and load and loading position. Retrofitted bikes are not suitable for carrying heavy loads and any load at the front has an adverse effect on the overall rideability and safety.

Practical application

The results highlight the benefits and limitations of different cargo bike designs and, therefore, could have implications for the cargo bike manufacturers, service providers, and policymakers.

A computational study on the basis for a safe speed limit for bicycles on shared paths considering the severity of pedestrian head injuries in bicyclist-pedestrian collisions

Bicyclists and pedestrians are two large vulnerable groups of road users. Many cities have allowed cyclists to share space with pedestrians on footpaths and off-road paths to reduce conflict with motor vehicles. The risk of bicyclist-pedestrian accidents is also increasing accordingly. Therefore, there is a need to understand the factors that affect the risk of injury in such accidents, especially to pedestrians who are considered more vulnerable. This paper presents a detailed investigation of bicyclist-pedestrian collisions and possible injury outcomes. The study has considered five levels of collision speed ranging from 10 km/h to 30 km/h, three pedestrian profiles (adult, child, and elderly) differentiated by their weight and height, three bicycles with different masses, and five impact directions. The bicyclist-pedestrian collision simulations have been analyzed based on four metrics: throw distance, peak head velocity on impact with the ground, head injury criterion (HIC) value, and the probability of severe head injury. For each simulation, the throw distance and peak head velocity on impact with the ground are extracted. Following that, the HIC and the probability of severe head injury to pedestrians are computed. The results show a significant effect of collision speed (p < 0.05) on all four metrics. The analysis has been further extended to study the effect of height and weight profile, bicycle mass, and impact directions on bicyclist-pedestrian collisions. According to the results, the impact directions largely influence the outcome of bicycle-pedestrian collisions. In general, direct impacts on pedestrian body center have been found to yield higher HIC values and probability of severe head injury to pedestrians than off-center impacts. Also, video analysis of simulated collisions has suggested that the accident mechanism depends on weight and height profiles (correlated with different age groups) and impact directions. Finally, recommendations have been proposed based on the study, including a speed limit of not more than 12 km/h for bicyclists on narrow shared paths and footpaths where risks of collisions with pedestrians are high. The results and analysis presented could be helpful for developing legislation to minimize conflicts between bicyclists and pedestrians on shared paths and to reduce potential injury to pedestrians.

Compliant Mechanism-Based Sensor for Large Strain Measurements Employing Fiber Optics

We propose a sensor design for measurement of large strains where direct application of a fiber optic strain gauge is impossible due to the stiffness mismatch between the optical fiber and the structure under test. The sensor design is based on a rhombus type compliant mechanism, which functions to attenuate input strain and transfer it to the ends of the sensing beam with the mounted optical strain gauge. We developed an analytical model of the sensor, which allows us to relate actuation forces, input displacement/strain, and output strain. The analytical model was verified with the finite element analysis and validated against an experimental prototype. The prototype sensor was able to handle input strains exceeding ±2.5 × 10⁵ µε. Potential application areas of the proposed sensor include compliant elastomeric structures, wearables, and soft robotics.

Implementation of a real-time, data-driven online Epidemic Calculator for tracking the spread of COVID-19 in Singapore and other countries

While there are many online data dashboards on COVID-19, there are few analytics available to the public and non-epidemiologists to help them gain a deeper insight into the COVID-19 pandemic and evaluate the effectiveness of social intervention measures. To address the issue, this study describes the methods underlying the development of a real-time, data-driven online Epidemic Calculator for tracking COVID-19 growth parameters. From publicly available infection case and death data, the calculator is used to estimate the effective reproduction number, final epidemic size, and death toll. As a case study, we analyzed the results for Singapore during the "Circuit Breaker" period from April 7, 2020 to the end of May 2020. The calculator shows that the stringent measures imposed have an immediate effect of rapidly slowing down the spread of the coronavirus. After about two weeks, the effective reproduction number reduced to about 1.0. Since then, the number has been fluctuating around 1.0 for more than a month. The COVID-19 Epidemic Calculator is available in the form of an online Google Sheet and the results are presented as Tableau Public dashboards at www.cv19.one. By making the calculator readily accessible online, the public can have a tool to assess the effectiveness of measures to control the pandemic meaningfully.