A study of factors influencing the severity of road crashes involving drunk drivers and non drunk drivers

In this study, an attempt has been made to develop Multinomial Logit (MNL) model by analysing the drunken and non drunken drivers involved in road crashes on Indian highways. Multinomial Logit model has been deployed to assess the influence of various parameters like vehicular, environment and geometric factors on the set of drivers who were found to be drunk at the time of getting involved in the road crash and those who were not under the influence of alcohol at the time of meeting with the road crash. The total economic cost of road crashes in the case of non-drunk driver road crash is Rs. 1046.27 million whereas in the case of drunk driver road crashes it is estimated to be Rs. 204.50 million. Further, it can be observed that economic cost of drunk driver road crashes is varying from 13 to 19 % across different types of road crashes.     

Socioeconomic factors affecting the job satisfaction levels of self-employed container truck drivers: a case study from Shanghai Port

The job satisfaction level (JSL) of self-employed container truck drivers (SCTDs) is vital to the container trucking industry’s (CTI) stability in China. An anonymous field survey of 645 SCTDs was conducted at Shanghai Port. Three ordered probit models were, respectively, developed to analyze the drivers’ JSLs, their attitudes, and reactions to a CTI downturn. This study contributes to the literature that the demographic variables were not statistically significant for the SCTDs’ current JSLs, while higher income SCTDs with fewer expenses were expected to have higher JSLs. During an industry downturn, drivers with families in Shanghai showed more job dissatisfaction. More working hours, lower income, expensive diesel fuel, a high consumer price index (CPI), and a low freight-to-distance ratio (FDR) significantly lowered the JSLs. An increase in the price of diesel fuel and the CPI, and a lower FDR exposed the industry to risk and instability. Additionally, credible evidence indicated that as the dissatisfaction levels of SCTDs rise in a downturn, SCTDs implement more practical measures that may negatively affect the industry’s stability as well as society’s. Based on these findings, managerial or policy implications were proposed to efficiently improve SCTDs’ JSLs and CTI stability in Shanghai.     

Household Mobility Tool Ownership: Modeling Interactions between Cars and Season Tickets

This paper moves beyond traditional models of car ownership in that we propose a framework for modeling household-level decisions to acquire specific types and numbers of mobility tools to fulfill the mobility needs of household members. The framework is applied to a data set collected during the winter and spring of 2000/2001 in the German city Karlsruhe via an interactive web-based stated response survey in which respondents could optimize their household mobility tool sets through on-line feedback concerning the estimated costs of the sets. In our analysis, bivariate ordered probit models are estimated for three combinations of mobility tools: season tickets (i.e., transit passes) and cars, season tickets and small cars and season tickets and large cars. In all instances, strong substitution effects are found – that is, as the number of season tickets increases, the number of cars decreases. This finding underscores the need to move beyond simple models of car ownership to comprehensive models of mobility tool ownership. As demonstrated by our research, failure to do so is likely to lead to biased results.     

Hurricane evacuation demand models with a focus on use for prediction in future events

Although substantial literature exists on understanding hurricane evacuation behavior, few studies have developed models that can be used for predicting evacuation rates in future events. For this paper, we develop new ordered probit models for evacuation using survey data collected in the hurricane-prone state of North Carolina in 2011 and 2012. Since all covariates in the models are available from the census or based on location, the new models can be applied to predict evacuation rates for any future hurricane. The out-of-sample predictive power of the new models are evaluated at the individual household level using cross validation, and the aggregated level using available data from Hurricane Irene (2011), Hurricane Isabel (2003) and Hurricane Floyd (1999). Model results are also compared with an existing participation rate model, and a logistic regression model available from the literature. Results at the individual household level suggests approximately 70% of households’ evacuation behavior will be predicted correctly. Errors are evenly divided between false positives and false negatives, and with accuracy increasing to 100% as the percentage of people who actually evacuate goes to zero or all and decreasing to about 50% when the population is divided and about half of all households actually evacuate. Aggregate results suggest the new models compare favorably to the available ones, with average aggregate evacuation rate errors of five percentage points.     

Determinants of ground transport modal choice in long-distance trips in Spain

In transport economics, modeling modal choice is a fundamental key for policy makers trying to improve the sustainability of transportation systems. However, existing empirical literature has focused on short-distance travel within urban systems. This paper contributes to the limited number of investigations on mode choice in medium- and long-distance travel. The main objective of this research is to study the impacts of socio-demographic and economic variables, land-use features and trip attributes on long-distance travel mode choice. Using data from 2007 Spanish National Mobility Survey we apply a multilevel multinomial logit model that accounts for the potential problem of spatial heterogeneity in order to explain long-distance travel mode choice. This approach permits us to compute how the probability of choosing among private car, bus and train varies depending on the traveler spatial location at regional level. Results indicate that travelers characteristics, trip features, cost of usage of transport modes and geographical variables have significant impacts on long-distance mode choice.     

The residential parking rent price elasticity of car ownership in Japan

By using household-level micro data captured through the National Survey of Family Income and Expenditure for 2004, this study evaluates the residential parking rent price elasticity of car ownership in Japan. It analyzes the number of cars owned by a household, using various attributes including expenditure for renting a parking space on a monthly basis. The estimation results derived from the IV-ordered probit model show that the absolute value of parking rent price elasticity of car ownership is, at most, 0.48, which is fairly small (i.e., inelastic). The elasticity value varies depending on city size; for megacities, elasticity is always negative for car ownership, whereas for middle-sized or small cities, towns, and villages, elasticity is positive for one-car ownership and negative for the ownership of more than one car. Hence, when the price of parking increases, some people may switch from more than one car to one car and some people in megacities may switch from one to zero cars. Indeed, the net effect of a price increase may be that non-car ownership increases in megacities and one-car ownership increases in other cities.     

How do people respond to congestion mitigation policies? A multivariate probit model of the individual consideration of three travel-related strategy bundles

This study explores the relationships between adoption and consideration of three travel-related strategy bundles (travel maintaining/increasing, travel reducing, and major location/lifestyle change), linking them to a variety of explanatory variables. The data for this study are the responses to a fourteen-page survey returned by nearly 1,300 commuting workers living in three distinct San Francisco Bay area neighborhoods in May 1998. We first identified patterns of adoption and consideration among the bundles, using pairwise correlation tests. The test results indicate that those who have adopted coping strategies continue to seek for improvements across the spectrum of generalized cost, but perhaps most often repeating the consideration of a previously-adopted bundle. Furthermore, we developed a multivariate probit model for individuals’ simultaneous consideration of the three bundles. It is found that in addition to the previous adoption of the bundles, qualitative and quantitative Mobility-related variables, Travel Attitudes, Personality, Lifestyle, Travel Liking, and Sociodemographics significantly affect individual consideration of the strategy bundles. Overall, the results of this study give policy makers and planners insight into understanding the dynamic nature of individuals’ responses to travel-related strategies, as well as differences between the responses to congestion that are assumed by policy makers and those that are actually adopted by individuals.

基于活动的旅游出行链选择行为研究

通过对在京旅游的游客进行调查,以游客的个人属性和出游属性作为影响因素,将游客对不同类型活动的时间分配作为前提,对游客的出行链选择行为建立了Multinomial Logit模型。模型分析表明:年龄、职业、出游时间、是否本地游客、对景点是否熟悉以及游客对活动时间的分配等均对出行链选择有显著影响;模型具有较高的精度,为游客出行预测提供了理论依据。     

考虑汽车共享服务的出行方式选择影响因素研究

为了分析汽车共享服务对城市出行者出行方式选择行为的影响,基于随机效用理论,运用行为调查和意向调查数据,以汽车共享服务、出租车、地铁三种出行方式作为选择肢,构建多项Logit模型,并应用SPSS软件对模型进行拟合检验与参数估计。研究表明：性别、年龄、最常使用交通工具、日常通勤单程距离、出行距离和汽车共享服务收费标准均会对出行者的汽车共享服务选择行为产生显著影响;中青年男性更倾向于选择汽车共享服务出行,且随着出行距离的增加、汽车共享服务收费标准的降低,汽车共享服务被选择的概率会增大;相较于出租车,日常通勤单程距离为20~30km的出行者更倾向于选择汽车共享服务;相较于地铁,最常使用交通工具为私家车的出行者选择汽车共享服务的概率更大。因此,为提高汽车共享服务被选择概率,应提高用户体验、服务水平,合理设置收费标准。