Sustainable urban mobility: Flexible bus service network design in the post-pandemic era.

The excessive traffic congestion in vehicles lowers the service quality of urban bus system, reduces the social distance of bus passengers, and thus, increases the spread speed of epidemics, such as coronavirus disease. In the post-pandemic era, it is one of the main concerns for the transportation agency to provide a sustainable urban bus service to balance the travel convenience in accessibility and the travel safety in social distance for bus passengers, which essentially reduces the in-vehicle passenger congestion or smooths the boarding-alighting unbalance of passengers. Incorporating the route choice behavior of passengers, this paper proposes a sustainable service network design strategy by selecting one subset of the stops to maximize the total passenger-distance (person × kilometers) with exogenously given loading factor and stop-spacing level, which can be captured by constrained non-linear programming model. The loading factor directly determines the in-vehicle social distance, and the stop-spacing level can efficiently reduce the ridership with short journey distance. Therefore, the sustainable service network design can be used to help the government minimize the spread of the virus while guaranteeing the service quality of transport patterns in the post-pandemic era. A real-world case study is adopted to illustrate the validity of the proposed scheme and model.

Understanding Current and Future Transport Needs of Older Australian Drivers to Guide Development of Sustainable and Smart Initiatives to Support Safe Mobility of Older Adults

Access to adequate and appropriate transport options enables older people to continue as thriving community participants, to reach services and to maintain social connections. While transport needs are diverse, and tend to change over time, there is little information on current and future transport patterns, and the awareness, acceptance and adoption of new technologies. A national online survey was administered to current drivers in Australia. A sample of 705 drivers provided information on available travel modes and use of these modes, awareness of in-vehicle technologies and future use of vehicle technologies. The findings revealed high use of private vehicles, walking and taxis but little use of other travel modes (bicycles, motorcycles, rideshare, community services and public transport). Age, gender and residential location influenced the availability and use/potential use of some transport options. Overall awareness of in-vehicle technologies was generally low and particularly so amongst older and female participants. There was some appetite to use emerging technologies in the future. The findings inform the development of effective strategies and initiatives aligned with healthy ageing and wellbeing targets, increased sustainability, resilience and connectedness, creation of healthier travel choices and healthier environments to promote acceptance and use of a range of transport options and uptake of safer vehicles equipped with in-vehicle technologies to ultimately enhance safe and sustainable mobility of older road users.

Enhancing mass transit passenger safety during a pandemic via in-vehicle time minimization

The risk of infection in a pandemic increases with duration of close contact with an infected person. Since the application of social distancing in public transit vehicles is challenging, minimization of in-vehicle time can help to protect passengers from getting infected. Skip-stop operation is a viable strategy to reduce in-vehicle time as opposed to the conventional all-stop operation, and therefore can provide safer mobility for passengers. In this paper, a mixed integer linear programming model is formulated to minimize the in-vehicle time of passengers while operating an A/B stopping pattern (one of the most popular skip-stop strategies in the literature and in practice). Since the number of direct trips is necessarily decreased when using such a skip-stop operation, this paper quantifies the tradeoff between the in-vehicle time of passengers as a pandemic-based safety measure and the number of direct trips as a measure of passenger satisfaction. In order to efficiently solve problems with a large number of transit stops, a multi-start genetic algorithm is developed. Rigorous numerical experiments indicate that the proposed approach can reduce in-vehicle time by up to 34%. Furthermore, Pareto optimal solutions are obtained to exhibit the tradeoff between in-vehicle time savings and percentage of direct trips.

Evidence for Human-Centric In-Vehicle Lighting: Part 1

Today, up to hundreds of RGB and W-LEDs are positioned in a vehicle’s interior context and are able to be individually controlled in intensity, color and sequence. However, which kind of illumination distracts or supports car occupants and how to define such a modern illumination system is still under discussion and unknown. For that, first a definition for an in-vehicle lighting system is introduced. Second, a globally distributed study was performed based on a free-access online survey to investigate in-vehicle lighting for visual signaling within 10 colors, eight positions and six dynamic patterns. In total, 238 participants from China and Europe rated color preferences, color moods, light-position preferences, differences between manual and autonomous driving and also different meanings for dynamic lighting patterns. Out of these, three strong significant (p < 0.05) color preference groups were identified with a polarized, accepted or merged character. For the important driving-signaling mood attention, we found a significant hue dependency for Europeans which was missing within the Chinese participants. In addition, we identified that light positioned at the door and foot area was globally favored. Furthermore, we evaluated qualitative results: men are primarily focusing on fast-forward, whereas women paid more attention on practical light usage. These findings conclude the need for a higher lighting-car-occupant adaptation in the future grounded by deeper in-vehicle human factors research to achieve a higher satisfaction level. In interdisciplinary terms, our findings might also be helpful for interior building or general modern cockpit designs for trains or airplanes.